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This paper describes the use of conventional and unconventional partial discharge tests by capacitive and inductive coupling in Instrument Transformers (IT). The objective of this work was to evaluate Phase-Resolveld Partial Discharge (PRPD) signatures features obtained during on-site (online) and laboratory (offline) measurements, by comparing results with state-of-the-art patterns and standard recommendations. The analysis of the results showed that is possible to obtain partial discharge (PD) patterns - corona, background noise, internal PD, free potential and surface PD - at on-site measurements but those are compromised by the pulse attenuation, difficulties in performing measuring system calibration and the absence of reference voltage. Suitable range of on-site measuring was above 1 MHz up to 5 MHz. The results reached in on-site measuring can be used as image preprocessing methodology to perform automatic pattern recognition of partial discharge signature. It is also described the parameterization of the HFCT for different frequency filter values though carrying out HFCT parameterization for different types of high voltage equipment was not objective of this work.
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     ProofCheck     
DE GRUYTER         
Douglas Aguiar do Nascimento1/ Yuzo Iano1/ Hermes José Loschi1/ Luiz Antonio de Sousa Ferreira1/
José Antônio Donizete Rossi1/ Clayton Duarte Pessoa2
Evaluation of Partial Discharge Signatures Using
Inductive Coupling at On-Site Measuring for
Instrument Transformers
            
       
   
  

                
     
Abstract:
This paper describes the use of conventional and unconventional partial discharge tests by capacitive and in-
ductive coupling in Instrument Transformers (IT). The objective of this work was to evaluate Phase-Resolveld
Partial Discharge (PRPD) signatures features obtained during on-site (online) and laboratory (oine) measure-
ments, by comparing results with state-of-the-art patterns and standard recommendations. The analysis of the
results showed that is possible to obtain partial discharge (PD) patterns - corona, background noise, internal
PD, free potential and surface PD - at on-site measurements but those are compromised by the pulse atten-
uation, diiculties in performing measuring system calibration and the absence of reference voltage. Suitable
range of on-site measuring was above 1 MHz up to 5 MHz. The results reached in on-site measuring can be used
as image preprocessing methodology to perform automatic pattern recognition of partial discharge signature.
It is also described the parameterization of the HFCT for dierent frequency lter values though carrying out
HFCT parameterization for dierent types of high voltage equipment was not objective of this work.
Keywords: Partial discharges, PRPD, Instrument transformers, Epoxy resin insulation, Oil insulation
DOI: 10.1515/ijeeps-2017-0160
Received: August 7, 2017; Revised: January 1, 2018; Accepted: January 2, 2018
1 Introduction
Instrument Transformers (IT) are fundamental electrical equipments for the Power Electric System (PES) con-
cerning to generation and transmission of electrical energy. As they convert the current and voltage - through
Current Transformer (CT) and Potential Transformer (PT), respectively, from high values to appropriate levels
of measurement, it is possible to monitor and control the quality and supply of electricity to consumers [13].
It is seen that when IT are exposed to the weather and to the manufacturing and logistic problems be-
tween supplier and installation site [4], these equipments are subject to defects caused by aging, overload, over
temperature [5], impact or mechanical stresses and cracks in its dielectric [6]. Those defects can be evidenced
through the analysis of the partial discharge (PD) intensity in equipment dielectrics and by assessment of the
deterioration of the insulation system [5]. For the eicient evaluation of these electrical equipment insulation, it
is necessary to verify PD activity and type in insulation dielectric by using preventive maintenance tests [79].
Partial discharges are electrical discharges located in an insulating system and limited to a part of the di-
electric of the electrical equipment and that only short circuit the part of the insulation between electrodes and
conductors [10, 11]. Those discharges are basically classied into three segments, in relation to the location
region and the discharge mechanisms: external discharges, surface discharges and internal discharges [12, 13].
The partial discharge tests can be performed on high voltage equipment such as power transformers, in-
strument transformers, medium, high and extra high voltage electrical cables, high voltage (HV) bushings and
rotating machines [1418].
Douglas Aguiar do Nascimento    
     
1
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     DE GRUYTER
The tests of partial discharge are classied according to the measurement methods: electric and non-electric.
Electrical methods are used to quantify the electrical charge resulting from partial discharges, whereas non-
electric methods are recommended for locating sources of PD [1921]. The electrical methods are divided into
conventional and non-conventional methods and they can be accomplished using capacitive coupling and in-
ductive coupling respectively [2224].
Conventional measurement methods, based on IEC 60270, with a frequency range up to 1 MHz, using
coupling capacitor and measurement impedance (quadripole) [24]. Unconventional methods are based on
the use of measurement sensors in the frequency bands: HF (330 MHz), VHF (30300 MHz) and UHF (300
MHz3GHz) [2426].
There are diiculties associated to the conventional method which requires the transport of measurement
equipment to the laboratory and the necessity for PES programmed shutdown in order to connect the coupling
devices. These diiculties represent obstacles in the use of the conventional electric method in measuring eld
operation [4, 9].
In order to overcome those diiculties and to achieve the sensitivity of the measuring device through tests
on energized and PES-connected equipment, unconventional methods can be used to carry out the PD test in
alternative to conventional tests [6, 9, 26]. By the non-conventional method of PD testing, the partial discharge
signals are coupled directly into the grounding system of the high voltage equipment, using the inductive
coupling by High Frequency Current Transformer (HFCT) and that center frequency of the measuring device
recommended is between 2 MHz to 10MHz [24]. Thus, tests can be perfomed outdoor without disconnecting
HV equipments from the PES. This study does not address the causes related to the sources of PD, therefore is
suggested to consult [5, 27, 28].
The HFCT transfer function is given by eq. 1 and it works according to Faradays Law of Induction [26]. The
induced voltage (𝑒) in the secondary circuit of the HFCT is proportional to the product of the mutual inductance
by the ratio between the current variation in the primary, and can be expressed by eq. 1 as follows [26, 2931]:
𝑒 = 𝑀 ⋅ 𝑑𝑖
𝑑𝑡 (1)
In this case, 𝑒can be obtained in the secondary circuit by coupling HFCT in a conductor, which works as the
primary circuit of the transformer.
According to IEC 60270 standards and references [13, 26, 32, 33], the capacitive coupling using measuring
impedance is suitable for laboratory measurement of PD (where calibration of the measuring instrument is
possible) whereas the inductive coupling can be used both in laboratory and in eld operation tests.
Thus, the PD test circuits presented in this paper are referred to as conventional electric method (capacitive
coupling and quadripole) and non-conventional electric test (inductive coupling).
2 Measurement circuits
Conventional indoor PD tests (i.e. laboratory) follow IEC 60,270 requirements which recommends the use of
coupling capacitor and quadripole connected to device under test (DUT). This work uses the impedance test
circuit connected in series with the coupling capacitor shown in Figure 1. The advantage of using conventional
method is that it is possible to obtain reference voltage and use calibrator to adjust the measuring system output
signal. The drawback is the DUT must be disconnected of the PES and brought to the laboratory so that to
perform the PD analysis.
Figure 1: Laboratory measuring circuit. a. Setting for CT. b. Setting for PT, adapted from [10, 11, 62].
In on-site measurements the HFCT should be used as non-conventional method, i.e. by using inductive
coupling, which allows carry out PD analysis on DUT connected to PES, as described in the studies of [4, 6,
24, 26, 32, 3437]. As shown in Figure 2, HFCT was connected to DUT grounding system as an alternative to
the conventional electrical test described above. Disadvantages of this method include absence of reference
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DE GRUYTER     
voltage and diiculties in using calibrator. Hence this method focuses on PD pattern (or signature) assessment
on Phase-resolved Partial Discharge (PRPD) diagram.
Figure 2: On-site PD measurement circuit using HFCT adapted from [38, 39, 51].
The procedure illustrated in Figure 2 is possible due to HFCT has articulated core which allows be coupled
to the grounding conductor (to be used as primary circuit) [24].
Besides the advantage of measuring PES-connected equipment [40, 41], there is no need to use the coupling
capacitor and measurement impedance (quadripole) because the signals are magnetically coupled to the HFCT
[26].
The eq. 2 shows a sensor model where Mis related to the geometry of the turn, 𝑙1and 𝑙2are the lengths of
the probe, and its separation, 𝛼, from the primary conductor and the turn. The turn has to be parallel and close
to that conductor, in order to obtain a proper sensitivity [29].
𝑀 = 𝜇0
2𝜋𝑙1log 𝑙2+ 𝑎
𝑎(2)
The sensitivity also depends on the signal measuring frequency, however, the increasing the frequency of the
signal is limited by the frequency response of the electric model of the HFCT [29].
3 PRPD signature background
Partial discharge sources can be represented under dierent geometric forms in PRPD diagrams [13, 19, 42, 43].
For each geometric form is associated a signature originated from the basic PD sources: internal, surface and
external. That method of analysis is referred here as qualitative analysis and diers from quantitative analysis
in terms of description of PD pattern as non-regular geometric format whereas the latter is related of PD phase
occurrence, discharge intensity and repetition rate also described as φ-q-n pattern. Then, according to [44],
PD pattern recognition can be provided using qualitative and quantitative features.
As reported by the measuring system manufacturer experts [45], there are basically four types of partial
discharge source patterns represented in Figure 3.
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     DE GRUYTER
Figure 3: a. electromagnetic external noise; b. void; c. gap; d. corona [35, 45].
Figure 4, Figure 5 and Figure 6 show signature variations for two types of transformer insulation: dry-type
and oil-lled.
Figure 4: Signatures of PD sources in epoxy insulation: void discharge (a., b.), surface discharge (c., d.) and corona (e., f.)
[19].
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     ProofCheck     
DE GRUYTER     
Figure 5: φ-q-n diagrams of measurement (a-c) and simulation (d-f) for dierent applied voltages at 50 Hz [46].
Figure 6: Signatures of PD sources in oil-lled insulation, adapted from [13].
In Figure 4, as described by [19], are shown signatures in epoxy insulation transformer:
a. and b. diagrams show signatures of void (internal PD) originated from insulation problem. The electric
eld in the void follows the applied voltage waveform curve, which is sinusoidal. Thus, the PRPD patterns
have a curvy shape which follows sinusoidal voltage waveform. Since the void is located in the middle of
the material, the electric eld on the surface of the void is symmetrical. Therefore, the PRPD patterns of
void discharge at positive and negative cycles of the applied voltage are symmetrical;
c. and d. indicate surface discharge signature. When the applied voltage is higher, the numbers of PDs per
cycle, total charge per cycle and the maximum magnitude of void discharge are higher. The maximum PD
charge magnitude is obtained around 270° phase [19];
e. and f. show negative corona signature. When the applied voltage is higher, the numbers of PDs per cycle,
total charge per cycle and the maximum magnitude of corona discharges are higher. This can be seen by an
increased number of PDs in each applied voltage cycle at voltage peaks.
In addition, Figure 5 shows results of PD activity from measurements and simulation as a function of amplitude
sinusoidal voltage applied of 14 to 20 kV at 50 Hz of frequency through a cavity within an epoxy resin sample.
The found patterns is described as rabbit-earand that occur after changing the Ucav (voltage across cavity)
polarity. When the voltage through cavity changes between PD, the voltage amplitude in cabity is increased.
This enhance the charge magnitude of the next PD event [46].
According to [13] in Figure 6 is shown:
a. a negative corona in the air, with occurrence phase along 270°, small intensity and repetition rate very high
at 10%;
b. shows positive corona in air, occurrence phase at 90°, high discharge intensity and high repetition rate;
5
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     DE GRUYTER
c. shows negative corona in oil, under 270° of phase occurrence, low intensity and small repetition rate;
d. is shown positive corona in oil, with occurrence phase around 90°, high discharge intensity; low repetition
rate;
e. shows surface discharge in air and occurrence phase is between 0 to 90° and 180° to 270°, intensity is small to
medium and repetition rate is rather high;
f. shows surface discharge in oil and phase occurrence is between 330° to 90° and 150° to 270°, small to medium
discharge intensity and very high repetition rate;
g. shows a pattern of free moving bubble in oil, characterized as concentration at sinusoidal voltage peak with
symmetric on both half cycles, small to large intensity (dependent of quantity of bubbles), repetition rate
related to the number of bubbles;
h. shows cavity between layer of paper 330° to 90° and 150° to 270° of phase occurrence, small to large intensity,
very high repetition rate;
i. shows metallic particle in oil concentrated around sinusoidal voltage peaks, small to medium intensity and
low repetition rate;
j. shows metal object at oating potential, occurrence phase between 0° to 90° and 180° to 270°, highly large
intensity and low repetition rate.
In on-site measurement the partial discharge signatures are subject to electromagnetic (EM) noises such as
harmonics, radio frequency (RF), corona and sparking [1]. This leads to loss of sensitivity which it is aggravated
by the low energy of PD pulses in high voltage systems [26] and results in low accuracy measurement.
In Figure 7 are described noise signature: Figure 7a. and Figure 6b. show corona in ambient air; Figure 7c.
and Figure 7d. show between metallic parts; in Figure 7e. e 7f. are shown external interferences.
Figure 7: Signatures of electromagnetic interferences in on-site measuring, adapted from [48][1].
Those disturbances are caused for non-impulsive and impulsive interferences. Impulsive interferences are
repetitive and random pulses caused by corona and switching devices (e.g. AC/DC converters), switching
operations, welding, sparking, etc. and they are diicult to remove due to similarities with partial discharge
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     ProofCheck     
DE GRUYTER     
pulses. Non-impulsive interference is characterized as white noise, generated from electrical equipment and
harmonic signal [1, 49].
The aim of the present work is not to perform pattern recognition, which includes feature extraction and
classication, as it is a later investigation to the description of the setup and congurations of using HFCT in
on-site measuring. However, the main methods found during pattern recognition research in partial discharges
are described.
Partial discharges have unique discriminatory attributes that allow them to be recognized. To do so, they
must be properly classied so that such attributes are extracted using feature extraction methods. Subsequently
those features of pre-processed PD data are used as input data in classiers during the training process. The
extraction methods commonly used in classication of partial discharges are described as statistical characteris-
tics, fractals and principal component analysis (PCA). As classiers, it is mentioned Articial Neural Networks
(ANN), Adaptive Neuro-Fuzzy Inference Systems (ANFIS) and Vector Support Machine (SVM). Then classiers
are trained to later classify the PD pulses [20].
4 Metodology and measurement setup
Partial discharges tests were performed in two tests: in laboratory - Test A - and in eld operation - Test B, with
the test congurations shown in Table 1. Test A was performed to: compare PD pattern data between inductive
and capacitive coupling using standardized oine setup; and parameterize the measuring device in order to
use HFCT at on-site measurements. The objectives of the Test B were: to carry out eld operation test according
to the setup found in the state-of-art; and to compare standards from established studies and related to the test
parameters.
Table 1: Tests perfomed during survey.
Test Coupling Insulation Level IT Insulation
A Quadripole/HFCT 69 kV CT Epoxy
B HFCT 362 kV CT Oil
In Test A PD tests were performed at the Furnas Centrais Elétricas SA, The High Voltage Laboratory. A
Balteau Current Transformer (CT) was used as DUT, manufactured in 1983, - 69 kV insulation level, model
SDB-69, solid epoxy insulation. It was used both conventional and non-conventional electrical measurement
methods, respectively, through quadripole series to the coupling capacitor and by HFCT. That equipment came
from eld where was placed near to a same model-CT defective which exploded.
In test B partial discharge tests were carried out on BBC CT, 362kV insulation level, model AOK362, manu-
facture in 1989, liquid insulation in mineral oil, installed in SE TijucoPreto, city of São Paulo, Brazil. By means of
Test B results analysis it was possible to perform a comparison of PD from studies performed in eld operation
and to verify the need for maintenance in the IT.
Test A follows the recommendations of the IEC 60270 standard for high voltage application of Alternating
Current (AC) in DUT to determine partial discharge inception voltage (PDIV) and extinction voltage (PDEV),
measurement of the charge intensity, repetition rate and phase of occurrence. The achievement of Test B fol-
lowed recommendations found in the studies [4, 6, 26, 40, 45, 50], for the evaluation of the measurement setup
and PD pattern. In this test the use of IEC TS 62,478: 2016 was not considered, due to its recent publication and
due to the realization of the tests performed before the publication.
Although the equipments dielectrics are not the same in laboratory and on-site measuring (due to the re-
quirement of analysis by the company that provided the data), the authors understand the need to carry out
such tests in the future.
The measuring system used were: Personal Computer: Personal Computer LAPTOP DELL SO Windows 8,
digital signal processor OMICRON MCU 502, computational tool OMICRON MPD & MI v. 1.6, acquisition unit
OMICRON MPD 600 and TechImp Clamp HF 39mm HFCT was used both in Test A and Test B (Table 1).
4.1 Analysis method through partial discharge phase-resolved partial discharge (PRPD)
The results were analyzed in the form of Phase-Resolved Partial Discharge (PRPD) colored diagrams were
is displayed charge intensity (𝑞), repetition rate (𝑛), phase angle (𝜑) and signature. The PRPD diagrams are
7
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     DE GRUYTER
produced and choose through cluster from Three-phase Amplitude Ratio Diagrams (3PARD) of measuring
system software.
By means of a PRPD analyzer instrument, the partial discharges are presented as a three-dimensional pat-
tern diagram of PD: apparent charge, occurrence phase and repetition rate, indicated by color [34, 51], in which
red shows high repetition rate and blue indicates low repetition rate.
4.2 Test a setup (Laboratory measurements)
In Test A was used inductive and capacitive coupling with measuring instrument adjusted. The measuring
circuit was calibrated with a calibration device in parallel to the DUT, as recommended by IEC 60,270 standard.
It was applied 100 pC of apparent charge in measuring system by calibrator. This procedure could not be carried
out in the eld due to the intrinsic diiculties of installing the circuit conguration, as also described in [9, 52].
Then CT was submitted to corona, through the insertion of two needles electrodes near the primary circuit
terminal and after the electrodes were removed in order to measure PD in absence of corona, for the evaluation
of partial internal discharges. The test setup is shown in the Figure 8. The voltage applied for pre-stress reached
60 kV (magnitude of PD in 700 pC to 1000 pC), with PDIV 32 kV (30 pC to 300 pC) and PDEV in 14 kV (lower
than 10 pC).
Figure 8: Setup of Test A (laboratory environment).
To perform the study, the items used in the measurement circuit are: OMICRON CPL 542 quadripole, OMI-
CRON MPP 600 DC (Discrete Continuous) voltage source, OMICRON CAL 542 calibration device, Haefely HV
AC (Alternate Current) 350 kV Mod. 735060 AC High Voltage non-resonant source, Haefely 185 kV - 600 F,
Mod. 190.014 coupling capacitor and anticorona rings.
To achieve the HFCT parameterization for epoxy CT, congurations were set up for measurements, accord-
ing to the type of coupling used, were:
Quadripole:𝑓1(phase 1) set to 349.5 kHz, 𝑓2(phase 2) set to 3.585 MHz, 𝑓3(phase 3) set to 7.031 MHz. 160
kHz-bandwidth, divider factor of 3.107 and 60 Hz trigger line.
HFCT:𝑓1(phase 1) set up to 4.959 MHz, 𝑓2(phase 2) set to 326 kHz, 𝑓3(phase 3) set to 11.27 MHz, 160 kH-
bandwidth, divider factor of 5.899 and 60 Hz trigger line.
Those HFCT frequencies values were dened regarding sensor frequency response that is clearly higher than
quadripole (20 kHz 10 MHz).
Regarding to the IEC 60,270 standard, as the measuring instrument has higher frequency response than
500 kHz recommended for narrow band instrument, the IEC 60,270 standard describes that a higher central
frequency (recommended up to 1 MHz). In this case, the narrow bandwidth must be used because the noise,
coupled in this frequency range, has a larger amplitude and, using smaller narrow bandwidth, the amount of
electromagnetic coupled noise to the HFCT is attenuated.
Dierent values of divider factor (relation between real and apparent charges) are obtained indicating the
quadripole is more accurate than HFCT (52,67%) due direct coupling of quadripole in IT whereas HFCT is
coupled in grounding system. It occurs because the components of the device under test (e.g. cables, dielectrics,
etc.) acts as low-pass lter and the dispersion eect due to distance that do attenuation of signal cutting out the
high frequency components of PD pulse, like shows in Figure 9 [53, 54].
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     ProofCheck     
DE GRUYTER     
Figure 9: Attenuation eect from distance and material. Adapted from [53].
So the system uses the scale factor to compensates the output values according to the calibration.
The characteristics of the measurement impedance were: maximum current 2 A, frequency range 20 kHz to
6 MHz. The specications of the HFCT were: bandwidth 2 MHz at 100 MHz, maximum sensitivity 21 mV/mA
(impedance transfer), impedance of 50 Ωload.
Those lter congurations were used to perform PRPD analysis and resulted in Figure 10 data.
Figure 10: Image parameterization of HFCT for epoxy CT for dierent frequencies. a. 𝑓1- 4.959 MHz; b. 𝑓2- 326 kHz; c. 𝑓3-
11.27 MHz.
It was observed that 4.959 MHz was the most tted frequency in relation to 326 kHz and 11.27 MHz. The
HFCT measuring then does not meet IEC 60270 requirements due to frequency range is above the standard
recommendation. This is because in 𝑓2HF pulses are cut o and the noise level is attenuated because they are
above the cut frequency. In 𝑓3however the pulse frequencies are below the cut frequency and the noise level is
pronounced blue dots scattered along the diagram.
The objective of this test was to compare the electrical parameters between capacitive and inductive cou-
plings, in order to use these ones in Test B afterwards.
4.3 Test B setup (On-site measurements)
By taking into account the parameters used in in Test A was performed eld operation test. So the HFCTs were
coupled to 345 kV bus-connected CTs grounding systems in A, B and C phases (Figure 11).
9
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     ProofCheck     
     DE GRUYTER
Figure 11: Setup of Test B (on-site measurement).
The used congurations were: 𝑓1at 3.749 MHz, 𝑓2at 6.24 MHz, 𝑓3at 10.94 MHz, 160 kHz-bandwidth, unmea-
sured divider factor (due reference voltage absence) and 60 Hz trigger. A high central frequency is obtained
because the greater gain of the HFCT is above 1 MHz (Figure 12) and best frequency range was found between 1
MHz to 5 MHz during Test A). Above that range, the partial discharge patterns were disturbed and attenuated
(Figure 10).
Figure 12: Frequency response of TechImp Clamp HF 39mm HFCT [39].
5 Results
The analysis of the results obtained in the tests performed both by conventional electric method and by non-
conventional electric method, was based on the studies of [1, 4, 13, 17, 21, 30, 32, 5562].
In occurrence phase evaluation the applied voltage should be taken as reference (sinusoidal-line in blue
on the diagrams). Its displacement with respect to the beginning of the PRPD diagram occurred due to the
horizontal oset so that the PD patterns could be better visualized. The sinusoidal gray line is used to evaluate
the displacement of the reference voltage with respect to the beginning of the diagram.
In test B, for the analysis of partial discharge patterns, one must take into account the geometric format of
signature cluster, since there is no applied voltage reference (due to the absence of calibration).
5.1 Test A Laboratory measurements
The setup and process used in this test can be observed in item 4.2 Test A Setup (Laboratory Measurements).
The data obtained with the tests using capacitor and HFCT as coupling devices are shown in Table 2. All
clusters shown in PRPD diagram of Figure 13, Figure 14, Figure 15 and Figure 16 are related to that table.
Table 2: Parameters obtained in laboratory measurements.
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     ProofCheck     
DE GRUYTER     
Coupling Cluster Qwdt [pC] Qpeak [pC] Qavg [pC] N [kPD/s]
Quadripole
1 10.8 15.8 10.52 7.104
2 21.27 53.71 21.18 8.819
3 237.1 273.8 211.9 2.743
4 7.11 12.02 7.143 2.033
5 16.01 31.2 15.91 2.527
HFCT
1 16.39 22.65 16.26 6.791
2 29.95 41.08 29.95 13.8
3 357.2 467.6 351.3 1.494
4 30.94 71.42 30.13 0.9599
5 27.95 38.43 27.92 1.639
Figure 13: PRPD diagrams obtained with quadripole, clusters 1, 2, 4 and 5.
Figure 14: PRPD diagram obtained with quadripole, cluster 3.
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     ProofCheck     
     DE GRUYTER
Figure 15: PRPD diagrams obtained with HFCT, clusters 1, 2 e 5.
Figure 16: PRPR diagrams obtained with HFCT, clusters 3 and 4.
In Table 2 were found measurements values in both couplings that have a high PD level (Qwdt above 10 pC).
The cluster 3 in quadripole and HFCT have PD charge intensity at 237.1 pC and 357.2 pC, respectively, showing
an irregular behavior of charge intensity. According to the PRPD diagrams presented in Figure 13 (cluster 2)
and Figure 14 (cluster 3), these clusters are signature of internal PD, evidencing the presence of cavity and hence
defect in the solid insulation CT. These PD sources were obtained with quadripole.
The Figure 14, cluster 3, indicates the presence of internal PD. The pattern is characterized by curves between
90° to 180° and 270° - 360°, of occurrence phase and curved shapes that accompany the sinusoidal voltage
signal. It is veried that the partial discharges occur during the inversion of positive half-cycle in negative and
of negative in positive.
It is noted that the PD source type illustrated in cluster 3 are internal voids within solid insulation. Values
higher than 300 pC are associated to this pattern in Table 2 (capacitive and inductive coupling, clusters 3).
Then tests were performed using HFCT and the results are shown in Figure 15 and Figure 16. There are
clusters related to background and corona noise also, mostly indicated in Figure 15, clusters 1, 2 and 5 and
internal partial discharge shown in Figure 16, clusters 3 and 4.
The cluster 3 of Figure 16 indicates patterns of partial internal discharge (void), sinusoidal curves represen-
tation between 90°-180° and 270°-360°, as presented in quadripole results (Figure 14).
Besides those, it was observed presence of partial discharge echo-like pattern in Figure 16, which can be at-
tributed to the uctuation voltage applied in DUT and to the surface discharge caused by poor contact between
electrodes.
5.2 Test B On-site measurements
These measurements follows the setup and process described in item 4.3 Test B Setup (On-site Measure-
ments).
The clusters 1, 2, 3 and 4 in PRPD diagrams of Figure 17, pointed out EM noise activity (low repetition rate
points scattered throughout the diagram) and internal PD source (sinusoidal behavior curves during phase
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     ProofCheck     
DE GRUYTER     
inversion in the semicycles). Surface partial discharge (related to free potential) is observed, probably caused
by poor contact between electrodes in the circuit under measurement or of mechanical origin, e.g. loose screw
in the metal structure of the device under measurement.
Figure 17: PRPD diagrams obtained with HFCT in site, clusters 1, 2, 3 and 4.
In Figure 18 are shown the background noise source patterns (low repetition rate points throughout the
diagram) and the surface PD source (contact discharge type or gap) - line pattern in the phase inversion region
(0°, 180° and 360°).
Figure 18: PRPD diagrams obtained using HFCT in-site, clusters 5, 6 and 7.
Through the data obtained and shown in the Table 3 is observed that the charge intensity ranges from 28.4
pC to 49.87 pC and having a high repeat rate value (𝑛) ranges from 210.6 PD/s to 5.62 kPD/s.
Table 3: Parameters obtained in-site measurements.
Coupling Cluster Qwdt [pC] Qpeak [pC] Qavg [pC] n [kPD/s]
HFCT
1 28.4 46.49 28.34 5.62
2 29.58 50.61 29.35 1.133
3 42.41 71.12 47.48 5.235
4 49.87 60.02 33.38 0.6273
5 33.78 59.39 34.84 0.5275
6 43.04 66.82 42.03 0.3386
7 30.69 59.72 32.11 0.2106
So it is not possible to describe, only analyzing the charge intensity and the repetition rate of partial discharge
(shown in Table 3), the state of the DUT insulation since no adjustment was made on the measuring instrument
using calibrator (as shown in 4.2).
In spite of that, is possible to point out, based on the PD patterns clusters 1 and 3 (Figure 17), that the
isolation of the equipment has internal PD source activity, requiring its removal from the PES for further and
detailed PD analysis the execution of a PD analysis in the laboratory.
13
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     DE GRUYTER
6 Data analysis and discussion
All signatures in 5.1 e 5.2 were also found in the state-of-the-art and in references described in 4.1 and studies
using DUT with solid or liquid dielectrics.
In Test A results it is shown characteristic patterns of corona, background noise, cavity and echo in epoxy
resin of CT insulation system.
According to the Brazilian standards that determine the level of PD in IT [64, 65], the level of partial dis-
charges in CT of solid insulation, with maximum voltage greater than 36.2 kV, varies between 20 pC to 50 pC.
This shows a magnitude of irregular PD and points to defect in the solid dielectric of the insulation system
of the equipment. Furthermore, it was observed that the PD intensity obtained with HFCT was close to the
quadripole measurements and the dierence can be attributed due to the chosen frequency range and dis-
tance, which attenuates the partial discharge intensities, to the magnetic losses in the inductive coupling and
to the errors intrinsic to measuring system and random errors compensated by divider factor (value between).
The PD signatures presented in Figure 13, Figure 14, Figure 15 and Figure 16 area also described by [8, 16,
5557, 60, 6669]. The same patterns were found for both HFCT (inductive coupling) and quadripole (capacitive
coupling) and show:
1. Voids Found in Figure 13 (cluster 2), Figure 14 (cluster 3), Figure 15 (cluster 5) and Figure 16 (clusters
3 and 4). It is observed that the patterns start with the increasing amplitude of the applied voltage (blue
line), typically at 0 and 180°, due to phase inversion, similar to that described by [16, 68], e [55]. This PD
pattern is characterized by the clouds of PD pulses sweeping up forming arcs in the resolved phase dia-
gram [4]. The electric eld in the vacuum follows the waveform of the applied voltage waveform, which is
sinusoidal. Thus, the PRPD standards have a curvilinear shape following sinusoidal voltage waveform [60].
As presented in [60, 63], the voids have an occurrence phase between 0° to 90° (positive phase peak) and
180° to 270° (negative phase peak). These standards are demonstrated by [28, 69], and [70], with occurrence
between 0 to 90° e 180 to 270°, with greater amplitude in 90° and 270°. In this case the phases of occurrence
found in the gures are similar to those of studies on solid dielectric in CT.
2. CoronaFigure 13 (cluster 2, cluster 5), Figure 14 (cluster 3), Figure 15 (cluster 2, cluster 5) and Figure 16
(cluster 3). These patterns occurred due to needle insertion near the primary CT terminal. The corona are
positive or negative streamers formed, depending on the polarity of voltage applied, on the positive and
negative cycles of the applied voltage and are not [60]. These form at 90° (positive corona) or at 270° (negative
corona), as shown in [27, 60, 63].
3. Background noiseAll Test A gures. The background noise was between 10 pC to 20 pC and is mostly
derived from the voltage source and the electric power signal.
4. PD echo: In Figure 16, cluster 4, phenomenon similar to that described by [57], named partial discharge echo
(PDE), Which can be attributed to the failure of the insulation system of the equipment being tested. This
is due to an accumulation of charge in the void and the accumulation of an internal electric eld which,
because of the capacitance, remains after removal of the external voltage, as well as the decay processes of
charge related to the conductivity of the surface material [57].
The results obtained during the laboratory tests were consistent with the studies of the references and provided
the parameters (selection of frequency bands and partial discharge patterns) necessary for the eld tests and
evaluation of the results.
In Test B results internal discharge, surface discharge and background noise of partial discharge signatures
were found in mineral oil (liquid insulation). A signicant feature found, in relation to the laboratory mea-
surement, was the inuence of EM noise of the environment due to radio transmissions, power electronics
components, random noise from switching, lightning, arcing, harmonics and interferences from ground con-
nections [20, 71], represented by points scattered throughout the diagram. The discharge amplitude was not
taken into account due to the lack of calibration.
The PD signatures found were:
1. Voids Figure 17 (clusters 1, 2 and 3). The PD sequence under AC conditions shows a well-observed behav-
ior in that the discharge patterns consist mainly of relatively regular recurrent discharge pulses along the
upstream and downstream portions of the applied sinusoidal voltage wave [72]. The PD patterns shown in
cluster 1 and cluster 3, increasing at beginning of each half cycle followed by decreasing like bell-shaped
curve are presented by [1, 4, 13, 61, 7375]. In [4] this pattern represents internal partial discharge in CT
oil-paper system insulation [1]. describes as a pattern in bell shape. That kind of pattern was isolated in
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     ProofCheck     
DE GRUYTER     
[73] from environment noisy and is shown as bell shaped curve. The source of this type of pattern is de-
scribed in [61] as void inside the pressboard sample. In [74] those pattern curves are simulated as result
of air-gap discharge defect sample modeled in oil by a pair of sphere-plane electrode. In [13] is expressed
as cavity between layers of paper in oil-impregnated paper insulation [75]. describes those patterns as at
void between pressboard layers in paper-oil insulation.
2. Surface discharge Figure 17 (cluster 4) and Figure 18 (cluster 6). Accordingly to [13] it is presented as surface
discharge in oil. In [75] those pattern are described as PD pattern recorded from an electrode conguration
consisting of a cylindrical electrode placed on a 6-kraft paper sheets and at an air/oil interface, and is shown
a mixture of internal and surface partial discharge. Those patterns from cluster 2 is shown by [76] as oating
part and contact noise. In [35] that is shown as a line of PD cluster points throughout the diagram.
3. Background noise All Test B gures. In [1] was shown as repetitive (e.g. corona and switching systems)
and random noise (from lightning impulses, switching operations, welding, and sparking). Those patterns
is characterized by continuous line of PD scattered points along the PRPD diagram. In [61] and [73] such
patterns were described as ambient noise and appear as continuous line of low repetition rate and low
amplitude of discharge.
According to [20], a standard method of denoising PD was not found yet despite have been improved over
time. This is attributed to the intrinsic noise features and similar to PD pattern in some cases - as those ones
described by [26] - which consists of radio transmissions, power electronics components, random noise from
switching, lightning, arcing, harmonics and interferences from ground connections [71] and contributes to the
lower detection sensitivity of the measurement system [20, 77]. Despite of that it can be attenuated using tech-
niques of measurement (such using optical ber, measurement cable, bridge circuit, software gating, 3PARD
and 3FREQ) and following the PD recognition procedures of separation for noise rejection and source separa-
tion), identication (evaluation of potential defect harmfulness); and diagnosis (allowing assess risks, establish
maintenance program and analysis the equipment life extension) [78]. Thus, the PD patterns can be classied
through analysis of specic combination of PD phase distribution, pulse magnitude and changing in the time
[77]. However, the PD measuring is challenging due to external noise disturbance which decrease the sensitiv-
ity of PD detection. Major disturbances found in PD measuring are produced by discrete spectral disturbances,
stochastic pulse shaped disturbances and periodic pulses shaped disturbances [79]. Therefore, a successful de-
noising is reached with low amplitude, minimum pulse shaped distortion and high SNR (signal-noise ratio)
[71]. According to study done by [20] using the PD identication methods pointed by the state-of-the-art, if
the computational processing time is not a relevant factor stochastic features, fractal feature and principal com-
ponent analysis can be used in as complement set of input features. However, if just one classier and input
feature must be used in high noised environment PCA features and SVM or ANN are recommended to PD
classication.
In this study was possible to select the center frequency and bandwidth in order to reach a high SNR and
low background level noise for obtain trustworthy PD analysis by using MPD 600. Therefore it demonstrates
the best noise cut-o frequency for our purpose and is shown in Figure 11 at 𝑓1, 4.959 MHz.
It was observed that the ferromagnetic material that composes the core determines the sensitivity of the
HFTC. In this case, the current sensor has a transfer function dependent on nonlinear factors such as frequency,
temperature and ux density, as described in [26]. Therefore, the HFCT core must be specied according to
the working frequency characteristics, up to 5 MHz, as observed with the obtained data. During research for
the best HFCT characteristics to the tests performed, it was found IPEC 140/100 HFCT [80], Figure 19, with
suitable frequency range for measurement purposes with the obtained data: transfer impedance (sensitivity):
5 mV/mA; Frequency response (-3dB): 50 kHz up to 20 MHz; Resistance: 50 Ω.
Figure 19: IPEC HFCT 140/100 transfer impedance [80].
15
Unauthenticated
Download Date | 4/13/18 12:08 AM
     ProofCheck     
     DE GRUYTER
According to results obtained by on-site measurements was observed that is possible to assess patterns of
partial discharge in eld equipments but the patterns must be separated from noises due to results are strongly
inuenced by environment disturbances.
Although the sensitivity of the IPEC 140/100 HFCT (5 mV/mA) is lower than that of the TechImp 39 HFCT
(21 mV/mA), observing the frequency response of the IPEC HFCT sensor, the lower and upper cut frequen-
cies are reduced to 50 kHz (lower frequency) and 20 MHz (higher frequency), respectively, which causes an
amplication of coupled signal in relation to the HFCT TechImp, because the values closest to those found to
be adequate for inductive coupling frequency response. It is recommended that measurements be taken with
other HFCTs with the appropriate frequencies and with the highest possible sensitivity. In addition, referring
to the diagram of the assignment of frequency bands in Brazil [81], the best frequency tuning range is above
1,705 MHz (frequency allocated to broadcasting stations of MW Medium Wave) and according to the results
found attenuation occurs for coupled signals above 5 MHz (Figure 11). I.e. the best tuning range for central
measuring frequency to be used as conguration of the measuring instrument is between 1,705 MHz and 5
MHz.
7 Conclusion
This paper shows comparisons between laboratory and eld tests results of PD signatures, charge intensity,
repetition rate, and occurrence phase. It was veried that the inductive coupling can be used both in eld test
(to be performed on instrument transformers) and in the laboratory measurements, by comparing signatures
in PRPD diagrams.
It was observed that the inductive coupling has advantages and disadvantages depending on the purpose
of use (eld or laboratory test), type of conguration (central frequency tuning and triggering), precision, mea-
surement time and cost of investment, in addition to requiring training of operators to analyze the results of
partial discharges - a comparative table can be found in [25]. By means of the laboratory test it was possible
to parameterize the HFCT for use in eld operation. It was found that using inductive coupling, the charge
strength was attenuated, relative to the quadripole coupling. This occurred because magnetic losses occur dur-
ing coupled induction and due to noise coming from the environment.
In spite of the signal attenuation of the HFCT, the inductive coupling had a satisfactory response to the
partial discharge pulses, allowing to obtain solved phase diagrams identical to those obtained with inductive
coupling, evidencing sources of internal partial discharge, electromagnetic noise and corona. However, the
values of repetition rate (𝑛) and charge intensity (𝑞) were considerably attenuated by means of HFCT (see Table
2), regarding to the data obtained with a measurement quadripole. Thus, it can be stated that HFCT can be used
as an inductive coupling for PD eld tests in order to be coupled to the grounding systems of the energized
equipment.
These geometrical analysis and description should be used as monochromatic image to mathematical mor-
phology and segmentation through edge detection and cluster analysis and segmentation, like shown by [36,
42, 82, 83] in order to perform image processing to automatic PD pattern recognition as suggested by [44, 84,
85].
As future work it is suggested, during the eld PD test, an analysis of the noise environment must be per-
formed as pointed out in [20]. It will be considered HFCT parameterization for dierent materials and type of
HV equipments. Also, studies should be carried out involving automatic recognition of patterns using PRPD
and statistical methods, with inductive coupling measurement, to obtain correlation between the data and eval-
uation of the best method to be used for eld operation testing. It will be considered in future publications the
use of the IEC 62,478 (High voltage test techniques) to perform the tests using the unconventional electromag-
netic method by HFCT.
Acknowledgements
The authors are grateful to the: Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES); Con-
selho Nacional de Desenvolvimento Cientíco e Tecnológico (CNPq); Fundação de Amparo à Pesquisa do Es-
tado de São Paulo (FAPESP); Departamento de Comunicações (DECOM); Faculdade de Engenharia Elétrica e
de Computação (FEEC); Universidade Estadual de Campinas (UNICAMP); and Facti (Fundação de Apoio à
Capacitação em Tecnologia da Informação) for their support to the development of this research. We are also
grateful to Furnas Centrais Elétricas S.A., in particular DEAM.O (Divisão de Ensaios e Apoio à Manutenção).
16 Unauthenticated
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     ProofCheck     
DE GRUYTER     
References
                  
           
             
           
               
               

                     
     
                
        
                   
      
              
                 
              

                       
  
              
               
                    
     
                   
        
            
                      
    
                    
       
                  
 
                     
     
                  
   
              
                   
        
                    
             
                 
         
                   
      
                   
       
              
                   

                 
     
                 

                
       
                   
   
                  
           
               

17
Unauthenticated
Download Date | 4/13/18 12:08 AM
     ProofCheck     
     DE GRUYTER
         
                    
           
                  
 
           
            
                   
                
  
                     ą 
 
                    
        
                     
   
             
                  
                
           
                      
          
               
        
                  
    
                  
               
    
                  
      
             
                

                     
             
                  
          
                     
      
                      
           
                
         
            
             
                   
                 
  
                

             
                
     
               
   
              
                        
  
                    

                  
         
                       
    
18 Unauthenticated
Download Date | 4/13/18 12:08 AM
     ProofCheck     
DE GRUYTER     
                  
  
                     
 
                    
                 
   
                      
       
                    
            
               
  
                   

                
  
                 
    
               

                
           
                   
        
                  
           
                  

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... The dielectric material degradation in electrical systems is generally associated with the partial discharges (PD) [1], unleashed within voids, and cracks in conductor-dielectric interfaces in solid insulation systems (bubbles), in the case of liquid dielectrics or corona, in gaseous [2]. Under the electric insulation system's operating stress conditions, the voltage across the damaged insulation, within bubbles, cracks, voids, may exceed its dielectric strength leading to electric discharges in the dielectric, reducing the stiffness and finally leading to total or partial failure of the insulation [3]. ...
... [4]), the analysis of PD can be extrapolated as an redundant component of power systems on alerting the active agents (electrical utilities, stakeholders, power system companies) in advance when any component it is about to collapse due to PD. The PD tests are classified according to the measuring technique, and electric methods are widely used [1]. Electrical methods can be performed on high voltage electrical equipment such as power transformers, instrument transformers, medium, high and extrahigh voltage cables, high voltage bushings and rotary machines [5]. ...
... Step 1 comprises the PD signal generation, modeled by traveling waves method [15] and application of characteristic background noise through AWGN to the signal generated [1]. In step 2, HFCT sensor modelling was performed, based on the Electromagnetism Laws, according to [16], whereas the frequency responses were carried out based on [14]. ...
Article
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The time measurement efficiency of the partial discharge (PD) relies on the signal-to-noise ratio (SNR) and gain of the high-frequency current transformer (HFCT) sensor. However, the PD's time measurement efficiency decreases with the noise coupled to the HFCT in onsite measurements. To overcome that setback, this paper proposes one pre-processing, through modelling and simulation, considering the physical effects, features of the electrical circuit and coil construction parameters of the HFCT. The main goal is to reach reasonable high SNR under the strong influence of background noises. This investigation aims to validate the hypothesis of improvement or deterioration of the HFCT signal response through a transfer function optimization. This research effort's contributions are threefold: 1. Generation of PD pulse signal and noise addition; 2. HFCT modelling, simulation, and frequency response analysis; and 3. Models performance evaluation and validation of hypothesis. In conclusion, the pre-processing approach stands out as a means to robustify and provide freedom to the electric utility, making up for an eventual need to redefine the physical and geometrical parameters of the HFCT sensor under specific background noise for maintenance tests purpose. According to a cyber-physical system framework, experiments corroborate the project's goals to contribute to the PD pattern monitoring in onsite measurements and incorporate robustness to signals with low SNRs.
... Depending on the source of the defect, its location, and the electrical discharge pattern, the PD discharges in power cables can be divided into internal discharges, surface discharges and corona discharge [17]. In the case of cavitydefect within power cables, partial discharges are governed by three processes [3]: 1. Gas composition; 2. Electronegative gases initiation; 3. Surface erosion. ...
... Depending on the source of the defect, its location, and the electrical discharge pattern, the PD discharges in power cables can be divided into internal discharges, surface discharges and corona discharge [17]. In the case of cavitydefect within power cables, partial discharges are governed by three processes [3]: 1. Gas composition; 2. Electronegative gases initiation; 3. Surface erosion. ...
Conference Paper
The cables failures in power systems utilities have been given great attention for reliability, economic aspects and safety of power utility operation. Such failures are caused by electrical, mechanical, and environmental stresses. Power cables might experience some serious damages particularly during the partial discharge activities. Therefore, the early localization of the exact defective cable section has become of extreme importance. The contribution of this study is to analyze electrical parameters behavior and its effects caused by a spheroidal cavity within the high voltage Cross-Linked Polyethylene (XLPE) cables. Also it investigates the correlation between electrical parameters and the size and location of voids inside the dielectric insulator using Finite Elements Analysis (FEA) environment. The results is intended to show that the location of the void inside the XLPE insulated power cables has a higher impact on the electric field and current density distribution than the void size.
... The difference in discharge activity could be attributed to the strong inhomogeneity of the internal structure or imperfect adhesion between the various parts of commonly used composite materials. Here, small, gas-filled areas near fibres, film or mica paper could occur during the process of producing the insulating system [72][73][74]. ...
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This paper deals with the topic of composite insulation materials for rotating machines and it is primarily pointed to the synthesis of new three-component insulation system. In connection with this research, the basic components of the insulation system are selected and described by different diagnostic methods. The proposed insulation material is composed of epoxy resin based on bisphenol-A diglycidyl ether, magnesium oxide nanofiller (1 wt %) with its own surface treatment technology using epoxysilane coupling agent ( γ -glycidoxypropyltrimethoxysilane) and polyethylene naphthalate as a reinforcing component. Following the defined topic of the paper, the proposed three-component insulation system is confronted with commonly used insulating systems (PET reinforced and Glass reinforced mica composites) in order to verify the basic dielectric properties (dielectric strength, volume resistivity, dissipation factor) and other parameters determined from phenomenological voltage and current signals, respectively.
... The insulation systems comprises air spacings, solid insulation and immersion in insulating liquid and are classified, according to their intended purpose, as being of external use or internal use. In addition, they can still be classified as self-regenerative (they have the capacity to recover the electrical rigidity, after occurrence of discharge caused by the application of the test voltage) and non-regenerative (Frontin, 2013).The present analysis takes into consideration only non-regenerative insulation systems since they form equipments those requires continuous dielectric state assessment as described by (Aguiar do Nascimento et al., 2018) in which demonstrates maintenance tests of instrument transformers' dielectrics. Furthermore, it was investigated the insulating replacement for sustainable procedures by energy concessionaires power. ...
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This paper presents design approach and performance analysis of different types of digital compensators for arobot arm joint control system which involves a sensor feedback. The design procedure incorporates discrete (z-plane) and continuous time (warped s-plane or w-plane) domain parameters. The design techniques of frequency response characteristics have been investigated and four basic types of controllers-phase-lag, phase-lead, proportional-integral (PI) and proportional-integral derivative (PID) have been designed and simulated on MATLAB. All the controllers have been implemented to achieve a phase margin of 40 deg. and open loop bode plots and closed loop step responses have been evaluated. Comparison among the controllers on the basis of step response characteristics has been presented in this paper.
... The insulation systems comprises air spacings, solid insulation and immersion in insulating liquid and are classified, according to their intended purpose, as being of external use or internal use. In addition, they can still be classified as self-regenerative (they have the capacity to recover the electrical rigidity, after occurrence of discharge caused by the application of the test voltage) and non-regenerative (Frontin, 2013).The present analysis takes into consideration only non-regenerative insulation systems since they form equipments those requires continuous dielectric state assessment as described by (Aguiar do Nascimento et al., 2018) in which demonstrates maintenance tests of instrument transformers' dielectrics. Furthermore, it was investigated the insulating replacement for sustainable procedures by energy concessionaires power. ...
Article
Full-text available
All economic activities that affect the environment should be submitted to environmental licensing, being mandatory throughout the Brazilian territory. The National Environment Policy (PNMA) and National Solid Waste Policy (PNRS), established by Law No. 12,305/2010 and regulated by Decree No. 7,404/2010, establishes the need for compliance with socio-environmental principles through prevention and precaution, eco-efficiency, among others. Considering that most of the electrical equipment – e.g. power transformers, capacitor banks, circuit breakers, reactors, switches, Gas-insullated Switchgear - present in the plant of the electricity distribution companies use mineral oil insulating, Sulfur Hexafluoride (SF 6 ) and non-biodegradable solid materials, and given the complexity and extension national electric grid, it is evident the concerning with the methods of protection to the environment. So the appropriate treatment and disposal of waste, generated by energetic companies, brings benefits such as the improvement of socio-environmental indicators of the company and provides control and monitoring of its assets. Along with the usage of sustainable materials in high voltage equipments could provide a greater electrical equipment lifespan and shorten time and maintenance costs associated to. Therefore, this prospective review, initially describes the use of sustainable of non-regenerative insulating system in electrical equipment used by Brazilian energetic companies and presents a conclusion in order to demonstrate improvement in maintenance actions of electric energy assets in compliance with national sustainability policies.
Article
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Cable joint insulation breakdown may cause a huge loss to power companies. Therefore, it is vital to diagnose the insulation quality to detect early signs of insulation failure. It is well known that there is a correlation between Partial discharge (PD) and the insulation quality. Although many works have been done on PD pattern recognition, it is usually performed in a noise free environment. Also, works on PD pattern recognition in actual cable joint are less likely to be found in literature. Therefore, in this work, classifications of actual cable joint defect types from partial discharge data contaminated by noise were performed. Five cross-linked polyethylene (XLPE) cable joints with artificially created defects were prepared based on the defects commonly encountered on site. Three different types of input feature were extracted from the PD pattern under artificially created noisy environment. These include statistical features, fractal features and principal component analysis (PCA) features. These input features were used to train the classifiers to classify each PD defect types. Classifications were performed using three different artificial intelligence classifiers, which include Artificial Neural Networks (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS) and Support Vector Machine (SVM). It was found that the classification accuracy decreases with higher noise level but PCA features used in SVM and ANN showed the strongest tolerance against noise contamination.
Conference Paper
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Partial Discharges PD are events that must be regarded in order to avoid many problems with high voltage equipments. There are different types of discharges and different factors that affect the nature of these discharges that will be discussed in this paper. In addition, analysis of the PD modelling is included. Frequency dependence of PD is included and the effect of some time constants on PD magnitude and number of PDs per cycle is discussed. In addition, a developed model is established in order to study the effect of applying higher frequency on the behaviour of PDs. The magnitude of frequency of the applied voltage was studied as well as cavity size and location in the dielectric. The model can be used to study samples of different types of dielectrics and a complete H.V. equipment can be investigated.
Article
The pattern recognition of partial discharge (PD) is critical to evaluate the insulation condition and locate the defect of a power transformer. The existing pattern recognition methods fail to make use of the inter-relations of the extracted features of PD signals. In fact, the inter-relations can show distinct dissimilarities between different classes of the signals. To overcome the defect of existing pattern recognition methods, the variable predictive model-based class discrimination (VPMCD), a new pattern recognition method, is introduced for the pattern recognition of PD in this study. However, the original VPMCD lacks general expression ability of the inter-relations of extracted features and inherits the shortcomings of least squares (LS) regression. To overcome the above defects, an improved VPMCD based on kernel partial LS (KPLS) regression, which is called as KPLSVPMCD, is proposed in this study. Experiments and analyses are implemented using both UCI datasets and the extracted features of PD signals. The experiments show that the performance of the proposed KPLS-VPMCD is better than those of the existing methods such as VPMCD, back propagation neural networks, and support vector machines. The conclusion is that KPLS-VPMCD is an efficient supervised learning algorithm with consistency and good performance for PD pattern recognition.
Conference Paper
Considering the effect of the surface resistance of void in the actual discharge process, on the basis of the Partial discharge (PD) model based on the theory of plasma, the physical model of PD in voids was modified in this paper. The influence of the change to surface resistance in the void discharge process has been considered in this model. Based on this model, the simulations of PD were investigated by using SIMULINK. The discharge waveform obtained by simulation is very similar to the measured ones in the same condition. It can be seen from the results that the modified model simulation waveform is superior to the traditional proposed, and closer to the actual waveform. This indicates that the simulation model is effective and the simulation results are reliable.
Article
Transformer is an expensive and vital component in electric power transmission and distribution system. Most of the failures of transformers occurs due to the failure of insulation. Hence electrical utilities are spending a large amount of money in the early prediction of insulation problems inside the transformers. In recent times, partial discharge (PD) detection and analysis is a well recognized insulation condition monitoring technique for power equipments. However, accurate classification of PD signals originating from different PD sources is always a vital and hot research issue. This paper attempts to use PRPD pattern features and artificial neural network approach, which produces accurate results on large data bases, to deal with partial discharge classification. In this work, corona discharges, internal discharges and surface discharges, which are the major sources of PD activities inside the transformer, were simulated in the laboratory using different electrode configurations and the corresponding PD signals were acquired using wide band detection system. Phase resolved PD pattern and time-frequency characteristics of PD pulses were analyzed and important statistical features were extracted. Artificial neural network model was trained and tested using the extracted statistical features of PRPD patterns of PD signals and reported results show that the proposed ANN based PD source classifier is efficient and useful for understanding single PD sources of transformers.
Article
Both the feature extraction method and pattern recognition method are of great importance to assess the healthcondition of a power transformer. Since the partial discharge (PD) signals of the transformer are non-stationary andnon-linear, and the existing pattern recognition methods fail to capitalise on the inter-relations between the extractedfeatures of the signals, a novel pattern recognition method, namely variable predictive model based classdiscrimination (VPMCD) is introduced for the PD pattern recognition in this research. However, the parameters ofVPMCD are estimated by using least squares (LS) regression which is sensitive to multiple correlations betweenindependent variables. Fortunately, partial LS (PLS) regression is usable even if features are highly correlated or thenumber of trained samples is very small. It is novelly adopted to overcome the defects of LS regression. Therefore, anautomatic PD source classifier based on PLS and VPMCD, i.e. PLS-VPMCD, is put forward in this study. PD signalfeatures from either pulse shape characterisations or phase-resolved PD are extracted. Then, the features are used asthe input vectors of PLS-VPMCD classifier. PD signals sampled from four artificial defect models are adopted for thealgorithms testing. Compared with the original VPMCD and back propagation recognition methods, PLS-VPMCD hasmuch higher recognition accuracy.
Conference Paper
Partial discharge (PD) measurement is one of the most important diagnostic methods to detect local faults in high voltage cable. This requires effective means of PD detection and recognition. The paper describes a method of PD recognition by image processing. Three kinds of cable-joint fault models are made for PD test with high voltage. Large amounts of test data are got for drawing scatter map or spectrum that can reflect the characteristic of PD. There is a certain extent difference in various types of PD spectrum. Spectrums of ?-q and TF are converted to gray scale. The edge detection by mathematical morphology is used for cluster analysis. Different types of PD signal and interference signal are separated. Higher recognition accuracy rate is obtained when judging the separated signal.