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This paper presents a new approach for the current acquisition system in motor fault detection applications. This paper includes the study, design, and implementation of a Rogowski-coil current sensor without the integrator circuit that is typically used. The circuit includes an autotuning block able to adjust to different motor speeds. Equalizing the amplitudes of the fundamental and fault harmonics leads to higher precision current measurements. The resulting compact sensor is used as a current probe for fault detection in induction motors through motor current signal analysis. The use of a Rogowski coil without an integrator allows a better discrimination of the fault harmonics around the third and fifth main harmonics. Finally, the adaptive conditioning circuit is tested over an induction machine drive. Results are presented, and quantitative comparisons are carried out.
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4062 IEEE TRA NSACTI ONS ON INDUSTRIAL ELECTRONICS, VOL. 56, NO. 10, OCTOBER 2009
Motor Fault Detection Using a Rogowski Sensor
Without an Integrator
Oscar Poncelas, Javier A. Rosero, Jordi Cusidó, Member, IEEE,
Juan Antonio Ortega, Member, IEEE, and Luis Romeral, Member, IEEE
Abstract—This paper presents a new approach for the current
acquisition system in motor fault detection applications. This pa-
per includes the study, design, and implementation of a Rogowski-
coil current sensor without the integrator circuit that is typically
used. The circuit includes an autotuning block able to adjust to dif-
ferent motor speeds. Equalizing the amplitudes of the fundamental
and fault harmonics leads to higher precision current measure-
ments. The resulting compact sensor is used as a current probe for
fault detection in induction motors through motor current signal
analysis. The use of a Rogowski coil without an integrator allows a
better discrimination of the fault harmonics around the third and
fifth main harmonics. Finally, the adaptive conditioning circuit is
tested over an induction machine drive. Results are presented, and
quantitative comparisons are carried out.
Index Terms—Current sensor, motor current signal analysis
(MCSA), motor drive, Rogowski.
I. INTRODUCTION
ELECTRICAL motors are the most common way to convert
electrical power to mechanical power in the industry.
Among them, induction motor (IM) and permanent magnet
(PM) motor are the most widely used. Of the industrial ap-
plications, 70% use induction machines, but PM ac machines
are increasingly used due to their high performance. Many
industrial applications require high reliability and availability,
which have become the major concerns in processes such as
aeronautics, robotics, machine positioning, and automobiles,
among others. Efficient condition monitoring and accurate
machine fault diagnosis are, thus, desirable in order to reduce
the impact of damage and to improve operational efficiency.
Motor faults can be classified as electrical and mechanical
faults [1], [2]. Among these: 1) bearing; 2) stator or armature
faults; 3) eccentricity-related faults; and 4) broken rotor bar and
end ring faults of induction machines are the most prevalent
ones and, thus, demand special attention.
Quantification of faults is as follows: 41% bearings, 37%
stator faults, 12% eccentricities, and 10% broken rotor bars.
Manuscript received October 31, 2008; revised June 12, 2009. First pub-
lished June 26, 2009; current version published September 16, 2009. This work
was supported in part by the Spanish Ministry of Education and Science under
the DPI2007-66688-C02-01 Research Project.
The authors are with the Motion Control and Industrial Applications Group,
Department of Electronic Engineering, Universitat Politècnica de Catalunya,
08222 Terrassa, Spain (e-mail: oscar.poncelas@upc.edu; jcusido@eel.upc.edu;
jaortega@eel.upc.edu; romeral@eel.upc.edu;).
Color versions of one or more of the figures in this paper are available online
at http://ieeexplore.ieee.org.
Digital Object Identifier 10.1109/TIE.2009.2025715
Significant efforts have been invested in the diagnosis of
motor faults during the last decades, and many techniques have
been proposed [3]–[19]. Several of these fault detection and
identification techniques are based on physical phenomena like
vibration monitoring [4], electromagnetic field monitoring by
means of search coils [5], electrical measurements [6], machine
models [7], or even a combination of different diagnostic
methods, such as mechanical, chemical, and thermal [8].
Although manufacturers and users of electrical machines
initially relied on simple protection against overcurrent, over-
voltage, and earth faults to ensure safe and reliable operation,
nowadays, the tasks performed by these machines have become
increasingly complex, and improvements have also been sought
in the field of fault diagnosis. Recently, new techniques based
on artificial intelligence approaches have been introduced [9],
which use concepts such as fuzzy logic [10], [11], genetic
algorithms [12], and neural networks [13]–[15] to detect, iden-
tify, and diagnose the state of the motor.
Among the different motor fault detection methods, the spec-
tral signature analysis of the stator current known as motor cur-
rent signal analysis (MCSA) is currently considered to be the
most popular fault detection method for online diagnosis [16].
The basis of the MCSA is that the stator current contains
current components directly linked to rotating flux components
caused by electrical or mechanical faults. These harmonic cur-
rent components caused by faults can be used for early failure
detection.
Condition monitoring based on stator currents is advanta-
geous due to its easy and cost-effective implementation. It is
nonintrusive and uses the stator winding as the search coil, and
it is not affected by the type of load and other asymmetries.
The monitoring is usually done in a steady operation state using
classical fast Fourier transform (FFT). However, many drives
are adjustable speed drives, where mechanical speed transients
may be present during a long period of time. The resulting
time-varying supply frequency prevents the use of classical
spectral analysis, and other signal processing methods such as
time–frequency analysis must be used [17]–[19].
All of these techniques share the need for data acquisition.
To perform the MCSA, stator currents are measured by current
meters, digitalized, and stored by time domain. The time do-
main is not suitable for the representation of current signals;
thus, frequency or time–frequency domains are applied to the
analysis of signals. After signal decomposition, signal features
must be extracted and entered into a pattern classification
model, which performs diagnosis and prognosis to detect a
failure in advance.
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PONCELAS et al.: MOTOR FAULT DETECTION USING ROGOWSKI SENSOR 4063
Different current sensing methods can be used to obtain a
signal equivalent to the current. Among them, shunt techniques,
Hall effect sensors, and current transformers are the most
frequently used.
Another possible sensor used to measure the current is the
Rogowski coil, which was first introduced in 1912 to measure
magnetic fields. Lately, Rogowski coils have been proposed to
measure acs [20]–[22] and for fault detection [23].
A Rogowski coil, named after its inventor, is a uniformly
wound coil on a nonmagnetic former of constant cross-sectional
area formed in a closed loop. The coil surrounds the primary
current to produce a voltage that is proportional to the time
derivative of the primary current and the mutual inductance of
the coil. The coil output is then integrated by an integrator to
recover the primary current signal. It can be used to measure acs
of tens of amperes or greater through the principles described
by Faraday’s law.
Signals from the transducer have a high signal-to-noise ratio
at these values, allowing the use of simple amplification and
filtering techniques and resulting in ac measurement systems
with better linearity, versatility, and cost compared to con-
ventional instruments. Moreover, Rogowski coils do not have
ferromagnetic material in their cores, which means that the
coils will never be saturated. Other advantages of Rogowski
transducers include the following: nonintrusiveness, full isola-
tion, good linearity, high bandwidth, ease of use (can be thin
and flexible), no consequences from dc saturation effects, and
relative simplicity and inexpensiveness to manufacture.
When a Rogowski coil is placed around a current-carrying
conductor, according to Faraday’s law, the output signal is
proportional to the time derivative of the measured current.
To obtain a signal that is proportional to the monitored
current, the output signal of the coil must be integrated. This
is the reason why it is necessary to use an integrator circuit to
obtain the stator current with the traditional Rogowski current
transducer [24]. This is a disadvantage when measurements are
carried out in an inverter drive. Due to modulation, the inverter
can introduce a dc component on common mode that causes
saturation in the integrator circuit. Also, in the case of active
analog integration, the integrator adds a dc offset component
that generates a ramp which will ultimately increase to be a
significant error in the output signal, demanding either the use
of a high-pass filter that needs to be well tuned in order not
to alter signal data [25] or an additional circuit to reset the
integrator to zero when the current through the Rogowski coil
is equal to zero [26], which complicates the sensor and makes
it more expensive.
This paper presents the study, design, and implementation
of a Rogowski-coil current sensor as a sensor for MCSA fault
detection without the integration block that is typically used.
Instead of using analog or digital integration, the sensor directly
provides the derivative of the measured current. In this way, the
current acquisition system can take advantage of the inherent
Rogowski coil characteristic: amplification of the current har-
monics by a frequency.
By using a bandpass filter to diminish main harmonic and
cutoff switching high frequencies, the acquisition system can be
tuned to the frequency range that contains the more interesting
fault harmonics. This compact sensor can be used as a current
probe for MCSA fault detection in electrical motors. This paper
is an extended version of another one presented at the 2008
IEEE International Symposium on Industrial Electronics [27].
It has been enhanced with the following elements.
1) The introduction has been updated with the most recent
journal references.
2) A theoretical background of fault currents has been in-
cluded.
3) Adaptive electronics have been developed to tune the
sensor operation to the motor speed.
4) Experimental results are now clearer and more accurate.
5) Conclusions of this paper have been reviewed and
improved.
Following this introduction, Section II presents the sensor
block details and sensor characterization. Section III deals with
the experimental results obtained from the faults staged on the
IM tested by measuring the currents with the proposed sensor.
Finally, in Section IV, the summary and conclusions drawn
from this study are presented.
II. MOTO R CURRENT ACQUISITION SYSTEM
As stated in Section I, MCSA is considered as the most
promising noninvasive fault detection method, as it allows the
detection of several common machine faults through simple
measurements and the processing of the stator current under
normal operation of the machine.
Generally speaking, three-phase currents under fault condi-
tions can be expressed as follows:
iR(t)=2IRsin 2πf1t+2
N
n=0
IRn sin(2πfntϕRn)
iS(t)=2ISsin(2πf1t2π/3)
+2
N
n=0
ISn sin(2πfntϕSn 2π/3)
iT(t)=2ITsin(2πf1t4π/3)
+2
N
n=0
ITn sin(2πfntϕTn 4π/3) (1)
where IR=IS=IT=Iare the rms values of the fundamental
component of the line current; IRn,ISn, and ITn are the rms
values of the fault components; and ϕRn,ϕSn, and ϕTn are the
angular displacements of the fault components.
The space vector
isreferring to the stator reference frame
is obtained by applying the transformation of the symmetrical
components
is=2
3iR+iSej2π/3+iTej2π/3
=3Iej2πfst+I1ej[2πf1tϕ1]
+I2ej[2πf2tϕ2]+···+Inej[2πfntϕn].(2)
Fault frequencies f1,...,n are related to different faults in
the induction machine [2], such as air-gap eccentricity (3),
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4064 IEEE TRA NSACTI ONS ON INDUSTRIAL ELECTRONICS, VOL. 56, NO. 10, OCTOBER 2009
shorted turns (4), and broken rotor bars
fecc =f11±m1s
p (3)
fst =f1m
p(1 s)±k(4)
fbrb =f1m1s
p±s(5)
where mis the harmonic order, f1is the main frequency, sis
the slip, pis the number of paired poles, and k=0,1,3,5....
Fault harmonic position is directly dependent on the slip value,
and slip is directly dependent on the motor load. Higher load
produces higher slip, and, hence, a fault harmonic could be
easier distinguished.
Shorted turns could also be detected, analyzing additional
harmonics at the medium band of the spectra [28], which
depend on the number of rotor slots Z2
fsth =f11±mZ21s
p.(6)
As stated, abnormal harmonics fn, which appear in a stator
current, are functions of a number of variables due to the
magnetomotiveforce distribution and the permeance-wave rep-
resentation of the air gap. In a variable speed drive, a current
control algorithm may exist that tries to provide symmetric
stator currents through the application of asymmetrical stator
voltages in order to reach this goal in spite of the fault’s ab-
normal harmonics. Therefore, it is important to assure that the
abnormal harmonic frequencies considered in fault detection
are beyond the cutoff frequency of the drive’s control transfer
function.
The stator current of the IM machine under fault conditions
is a combination of different frequency components as it can
be seen in (2). If this current is measured with the proposed
Rogowski sensor, without the integrator, (2) will take the fol-
lowing form:
diR(t)
dt =2πf12IRcos 2πf1t
+2
N
n=0
[2πfnIRn cos(2πfntϕRn)]
diS(t)
dt =2πf12IScos (2πf1t2π/3)
+2
N
n=0
[2πfnISn cos(2πfntϕSn 2π/3)]
diT(t)
dt =2πf12ITcos(2πf1t4π/3)
+2
N
n=0
[2πfnITncos(2πfntϕTn 4π/3)] .
(7)
The derivative operator is linear, i.e., it changes the modules
and phases of the sine components, but it does not create new
frequencies.
Fig. 1. (a) Block diagram of the traditional acquisition system. (b) Block
diagram of the proposed acquisition system.
For the purpose of fault detection with MCSA, we have
considered the spectral analysis of the stator current, and the
phase has not been relevant. The difference with the traditional
transducer is that, with the proposed Rogowski sensor, the
frequency harmonics increase their amplitude since they are
scaled by their respective ω(2πf). This helps the harmonic in
the presence of noise, particularly at high frequencies.
It must be noted that fault detection is usually better per-
formed at high frequencies, either by analyzing the spectra
around the main harmonics or by injecting high-frequency
voltage test frequencies or by reading the corresponding current
harmonics [29], [30]. In conclusion, a Rogowski coil without an
integrator enhances high current frequencies, which aids fault
detection through MCSA.
The traditional block diagram for current measurement with
a Rogowski coil is shown in Fig. 1(a). This paper’s pro-
posal uses a Rogowski coil without the integrator circuit
[Fig. 1(b)].
A. Rogowski Without Integrator Transducer
As we have seen before, the use of an integrator is prob-
lematic since it is difficult to adjust and it shows a tendency
to saturation. The power supply of the induction machine
usually comes from a power inverter. This type of power source
generates high-frequency signals that may be nonsymmetrical,
i.e., signals have different negative and positive parts, and the
nonzero average can saturate the integrator circuit.
At the output of the Rogowski coil, we obtain an output
signal that is proportional to current changes
Vo=μ0nA
2πr
di
dt =Mdi
dt (8)
where μ0=4π×107H/m is the permeability of free space,
nis the number of turns, Ais the cross-sectional area in square
meters, and ris the radius of the coil in meters. The constant
term Mrepresents the mutual inductance of the Rogowski coil.
The output voltage of the coil must be integrated to provide
the current. For our purpose, the Rogowski coil is designed
with the shape of a polyethylene toroid core with n= 500,
A=64mm2, and r=10mm. With these values, the mutual
inductance is about M= 640 nH. Axial return wire design is
used, and gaps and overlaps in the winding have been mini-
mized to reduce sensitivity to external disturbances. The signal
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PONCELAS et al.: MOTOR FAULT DETECTION USING ROGOWSKI SENSOR 4065
Fig. 2. Sensor output. (a) Output voltage of (+) a commercial transducer and
(o) a traditional Rogowski-coil transducer. (b) Output voltage of the Rogowski-
coil transducer without an integrator, (+) theoretical and (o) measured.
gain block is a noninverting amplifier with a gain of 60 dB. The
bandpass filter block is discussed in detail in Section II-B.
The bandpass filter block is discussed in detail in
Section II-B, and the analog-to-digital converter (ADC) block
is a standard microprocessor-based signal acquisition with 12-b
resolutions, with a sample frequency of fs= 10 000 Hz.
Several tests have been performed to evaluate the operation
of the transducer. The value of Mhas been obtained by mea-
suring Zparameters with a Rohde & Schwarz ZVRE network
analyzer. A value of 669.4 nH is obtained. The whole current
transducer proposed has been tested with a conductor carrying
a current of 0.2 A obtained through a function generator in-
strument. The output of the Rogowski transducer without an
integrator has been compared with the outputs of a commercial
transducer and a traditional Rogowski transducer.
The commercial transducer is the Tektronix A622 that uses
a Hall effect current sensor to provide a voltage output. It can
measure acs/dcs from 50 mA to 100 A peak over a frequency
range of dc to 100 kHz.
The traditional Rogowski transducer was manufactured us-
ing the same coil as the Rogowski transducer without an
integrator. It is designed to measure currents up to 10 Arms over
a frequency range from 10 up to 500 Hz.
Fig. 2(a) shows the output voltage of the commercial trans-
ducer and the traditional Rogowski coil with an integrator. We
can see that, at frequencies higher than 500 Hz, the traditional
Rogowski coil acts as a low-pass filter. This is done by the
integrator circuit.
Fig. 2(b) shows the output of the Rogowski coil without an
integrator, with its theoretical and experimental results. One
can see how the harmonics increase its amplitude with the
frequency.
Another test to validate the transducer is to put a conductor
carrying a square current through the coil. At the output of the
transducer, all the harmonics must have the same amplitude.
The harmonic decomposition of the square signal is
i(t)=4V
π
n=1 1
nsin(n·ωot)(9)
where Vis the amplitude of the square signal, ω0is the
fundamental frequency, and nare the odd numbers.
Fig. 3. Current spectrum of a square signal measured with a commercial
transducer and with the proposed Rogowski transducer.
Fig. 4. Block diagram of the bandpass filter.
The harmonic decomposition at the output of the Rogowski
transducer is
y(t)=Mdi
dt =M4V
π
n=1
(ωocos(n·ωot)) .(10)
This should be corroborated by the results obtained in Fig. 3.
To the left, we can see the output of a commercial current
transducer, and, to the right, we can see the output of the
suggested Rogowski transducer.
Using the proposed Rogowski transducer is a good solution
to monitor the harmonics at frequencies above the main har-
monic since the harmonics take more amplitude regarding the
main harmonic.
A combination of the reduced main harmonic (due to the
filter) and the amplified fault harmonics (due to lack of integra-
tion) will produce a similar amplitude for all harmonics passing
the filter and, thus, better use of the acquisition system dynamic
range.
B. Proposed Acquisition Circuit for Variable
Operating Conditions
When we consider variable conditions, the bandpass filter
block is comprised by the blocks in Fig. 4. The main part is
an adaptive filter using a switched-capacitor filter.
The idea is to measure the first harmonic as well as the
harmonics that appear due to the fault near the fifth harmonic.
The magnitude of the fault harmonics near the fifth harmonic
with respect to the fundamental harmonics is about 40 dB
below.
The proposed method is based on the attenuation of the
fundamental harmonic and the amplification of the band of the
fault harmonics, obtaining a theoretically similar amplitude for
the fundamental and the fifth harmonics.
In this paper, we want to measure the fault harmonics due
to broken rotor bar faults and eccentricity faults. In order
to detect broken bar faults, the classical method of analysis
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4066 IEEE TRA NSACTI ONS ON INDUSTRIAL ELECTRONICS, VOL. 56, NO. 10, OCTOBER 2009
Fig. 5. Proposed Rogowski sensor with the adaptive filter.
through MCSA uses the first harmonic, observing the fault
near f1(1 ±2s). Other studies propose evaluating the side
of the fifth harmonic, finding the fault near f1(5 4s)and
f1(5 6s).
To detect eccentricities, any harmonic given by the expres-
sion can be evaluated (3). In this paper, we have considered the
side of the third harmonic.
The high-pass switched-capacitor filter selects the analyzed
frequency band. Additionally, this filter equalizes the amplitude
of the main harmonic which, then, has similar amplitude to the
fifth harmonic. With these requirements, the cutoff frequency
of the switched-capacitor filter is 2f1(f1is the fundamental
frequency of the stator current). This cutoff frequency is ad-
justed externally by a clock signal. With a fourth-order filter
and 2f1cutoff frequency, the attenuation at f1is always one
octave. Resolution of the proposed sensor is enough to detect
the fault harmonics with the amplitude lower than the threshold
arbitrarily established in 40 dB below the main harmonic.
As we can see in Fig. 4, the main part of the adaptive
system is the switched-capacitor filter. This is comprised by two
second-order parts based on the LTC1068 component of Linear
Technology, comprising a fourth-order high-pass filter.
An RC network is used to avoid aliasing in the switched-
capacitor filter. Before ADC, a low-pass filter is used to avoid
aliasing in the digital acquisition system. The cutoff frequency
of an antialiasing filter is 400 Hz.
Fig. 5 shows a picture of the developed Rogowski sensor.
With the method that has been proposed, the MCSA is per-
formed by comparing the fundamental frequency to the fault
harmonics and observing the time evolution. Fig. 6 depicts
the frequency response of the bandpass filter for two different
working points.
III. EXPERIMENTAL RESULTS
A. Test Bench
To check the transducer for fault detection in an IM, several
tests have been done with a three-phase 1.1-kW 400/230-V
50-Hz 1410-r/min four-pole IM.
First, the behavior of the healthy motor was studied, and,
after motors with eight rotor bars, damaged and eccentricity
faults were analyzed. The motor nameplate is shown in Table I.
The motor under test is controlled with a voltage–frequency
control implemented in a TMS320F2812 digital signal proces-
sor manufactured by Texas Instruments.
The current has been measured by two transducers: a tra-
ditional Rogowski sensor with the integrator hardware and
Fig. 6. Frequency response of the bandpass filter for a main stator current
harmonic of 50 and 33 Hz, (+) theoretical and (o) measured.
TAB L E I
SPECIFICATIONS OF IM-TYPE MODEL
Fig. 7. IM test bench for fault detection.
the Rogowski transducer proposed in this paper (Fig. 6). The
traditional Rogowski sensor measures the currents up to 20 A,
from 10 to 500 Hz, and with a sensibility of 148 mV/A.
The fully analyzed band ranges from 0 to 400 Hz with a
resolution of 0.2 Hz for FFT analysis, which is enough to cover
the significant band of an induction machine and to distinguish
the harmonics due to a fault.
The test rig and the data are shown in Fig. 7. Load control has
been implemented by using an IM and a commercial inverter,
where variable load order was introduced.
B. Fourier Analysis of Motor Stator Currents for Different
Operating Conditions
Fig. 8 illustrates the stator current spectrum of a healthy
motor measured with a traditional Rogowski coil and with the
proposed Rogowski sensor.
We can observe how the fundamental harmonic takes similar
amplitude to the third and fifth harmonics if the current is mea-
sured with the proposed Rogowski sensor. If we compare the
two graphs, we can see that the harmonics of high frequencies
are higher with the proposed Rogowski sensor than with the
traditional Rogowski sensor.
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PONCELAS et al.: MOTOR FAULT DETECTION USING ROGOWSKI SENSOR 4067
Fig. 8. Stator current spectrum of a healthy IM supplied with 50 Hz.
(a) Traditional Rogowski sensor. (b) Rogowski sensor without an integrator.
Fig. 9. Stator current spectrum of a healthy IM supplied with 33 Hz.
Fig. 9 depicts the current spectrum of the same motor sup-
plied with a different current frequency. The adaptive filter
changes the cutoff frequency to a new one adapted to the new
conditions. Again, it is easy to see that the harmonics with high
frequencies take more amplitude if they are measured with the
proposed Rogowski sensor. Fig. 10 shows the detail near the
fifth harmonic of the current spectrum of an IM with eight
broken bars (right side) as opposed to the current spectrum of a
healthy motor (left side). Both motors have been supplied with
50 Hz. All the graphs are normalized to 0 dB at the peak of the
fundamental frequency.
Harmonics that appear due to the fault are inside the ovals. In
the graphs, we can appreciate how these harmonics concerning
the main harmonic increase their amplitude if they are measured
with the proposed Rogowski sensor.
The amplitude of these harmonics measured with the pro-
posed transducer is more than 25 dB higher than the harmonics
obtained with the traditional Rogowski sensor. This means that
the fault can easily be detected and that it is possible to use an
ADC with less resolution in the acquisition hardware.
Fig. 11 shows the same motor supplied with 33 Hz. The fault
harmonics are inside an oval again. In this situation, the fault
harmonics measured with the proposed Rogowski sensor are
Fig. 10. Stator current spectrum of an IM supplied with 50 Hz. Fifth har-
monic sideband. (a) Healthy motor measured with a traditional Rogowski
sensor. (b) Healthy motor measured with a Rogowski sensor without an
integrator. (c) Motor with broken bars measured with a traditional Rogowski
sensor. (d) Motor with broken bars measured with a Rogowski sensor without
an integrator.
Fig. 11. Stator current spectrum of an IM supplied with 33 Hz. Fifth har-
monic sideband. (a) Healthy motor measured with a traditional Rogowski
sensor. (b) Healthy motor measured with a Rogowski sensor without an
integrator. (c) Motor with broken bars measured with a traditional Rogowski
sensor. (d) Motor with broken bars measured with a Rogowski sensor without
an integrator.
detected, whereas, with the traditional one, they are so small
that they are difficult to differentiate from noise.
Similar results have been obtained with a motor with lower
damage level, i.e., with one broken bar, not shown here for the
sake of readability.
The proposed Rogowski sensor is also useful for the detec-
tion of other faults, such as eccentricity. Fig. 12 illustrates the
current spectrum of an IM with an eccentricity fault, supplied
with 50 Hz. The harmonics inside an oval are the harmonics
that appear due to the fault. The figure depicts how these fault
harmonics take more amplitude with the proposed Rogowski
sensor.
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4068 IEEE TRA NSACTI ONS ON INDUSTRIAL ELECTRONICS, VOL. 56, NO. 10, OCTOBER 2009
Fig. 12. Stator current spectrum of an IM with eccentricity supplied with
50 Hz. (a) Traditional Rogowski sensor. (b) Rogowski sensor without an
integrator.
Fig. 13. Stator current spectrum of an IM with eccentricity supplied with
50 Hz. Third harmonic sideband. (a) Healthy motor measured with a traditional
Rogowski sensor. (b) Healthy motor measured with a Rogowski sensor without
an integrator. (c) Motor with broken bars measured with a traditional Rogowski
sensor. (d) Motor with broken bars measured with a Rogowski sensor without
an integrator.
Fig. 13 shows the detail near the third harmonic for the motor
with an eccentricity fault (right side) as opposed to the healthy
motor (left side) supplied with 50 Hz.
The fault harmonics are inside an oval. Fig. 14 depicts the
third-harmonic detail for the motor with an eccentricity fault as
opposed to the healthy motor for a current supply of 33 Hz. As
we can see, the fault harmonics are better detected with nominal
speed.
These experimental results allow us to confirm that the
Rogowski transducer without the integrator is suitable for
MCSA.
The results obtained from the proposed Rogowski sensor
have been compared with those obtained with the traditional
Rogowski sensor.
With the proposed Rogowski transducer, the harmonics of
high frequency take more amplitude than the same harmonics
obtained with the other transducers. This effect is not important
Fig. 14. Stator current spectrum of an IM with eccentricity supplied with
33 Hz. Third harmonic sideband. (a) Healthy motor measured with a traditional
Rogowski sensor. (b) Healthy motor measured with a Rogowski sensor without
an integrator. (c) Motor with broken bars measured with a traditional Rogowski
sensor. (d) Motor with broken bars measured with a Rogowski sensor without
an integrator.
at frequencies around 50 Hz, but, at higher frequencies, the am-
plitude of the harmonics obtained with the Rogowski transducer
without an integrator is clearly higher, and it can be used for
fault detection at medium-to-high frequencies.
IV. CONCLUSION
This paper has presented an implementation of a Rogowski
coil for fault detection in an IM. To increase the reliability of
the acquisition system, it is suggested to remove the integrator
that is characteristic in this kind of current probes. In this way,
the proposed Rogowski transducer simplifies the electronics;
it prevents adjustment problems with integrator circuits, and
it performs better at high frequencies. Moreover, the proposed
acquisition system has used an adaptive filter to attenuate the
fundamental harmonic in order to achieve better use of the
dynamic range of the digital acquisition system.
Theoretical analyses and experiments support this paper, and
results have shown that this Rogowski transducer without an
integrator can be used as an improved sensor for fault detection
through stator current readings in electrical motors.
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Oscar Poncelas was born in Barcelona, Spain, in
1978. He received the B.S. and M.S. degrees in elec-
tronic engineering from the Universitat Politècnica
de Catalunya (UPC), Barcelona, Spain, in 2001 and
2008, respectively.
Since 2002, he has been with the Department of
Electronic Engineering, UPC, as a Technical Staff,
where he is currently with the Motion Control and
Industrial Applications Group, where the group’s
major research activities concern induction and per-
manent magnet motor drives, enhanced efficiency
drives, and fault detection and diagnosis of electrical motor drives.
Javier A. Rosero was born in Potosi, Colombia,
in 1978. He received the B.S. degree in electrical
engineering from the Universidad of Valle, Cali,
Colombia, in 2002, and the Ph.D. degree from
the Universitat Politècnica de Catalunya (UPC),
Barcelona, Spain, in 2007.
Between 2002 and 2004, he worked in the mainte-
nance of power systems and substations in Bogotá,
Colombia. He is currently a Senior Engineer with
the ABB Company, Spain, where he is working
in the field of motor control and applications. He
actively collaborates with the Motion Control and Industrial Applications
Group (MCIA) as researcher. His research interests are focused on the areas of
simulation, modeling, supervision, diagnosis, and control of electrical machines
and drives.
Jordi Cusidó (M’09) was born in Sabadell, Spain,
in 1979. He received the B.S. degree in electri-
cal engineering from the Universitat Politècnica de
Catalunya (UPC), Barcelona, Spain, in 2005.
In 2005, he joined the Department of Electronic
Engineering, UPC, where he is currently with the
Motion Control and Industrial Applications Group
as an Assistant Professor teaching courses on analog
electronics for aeronautical applications. The group’s
major research activities concern induction and per-
manent magnet motor drives, enhanced efficiency
drives, direct torque controllers, and sensorless vector drives. The group is also
active in motor fault detection algorithms, automotive drive applications, data
acquisition systems, and signal processing and adaptive control. His research
interests include electrical machines, variable speed drive systems, electrical
systems for automotive and aeronautical applications, and fault detection algo-
rithms. He has authored more than ten peer-reviewed scientific papers published
in technical journals and conference proceedings. He participates in European-
Union- and Spanish-government-funded projects. He has also participated as
an Engineer or responsible for research and development projects funded by
local private companies, in the areas of electrical machine design and industrial
control. He collaborates with automotive companies for the distribution of their
components and subsystems.
Mr. Cusidó is a member of the IEEE Industrial Electronics Society and
IEEE Aerospace and Electronic Systems Society. He is also a member of
the Technological Centre of Manresa (CTM), where he is responsible for
technological assistance to several industries and university departments in the
fields of automotive and aeronautical applications.
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4070 IEEE TRA NSACTI ONS ON INDUSTRIAL ELECTRONICS, VOL. 56, NO. 10, OCTOBER 2009
Juan Antonio Ortega (M’94) received the M.S. de-
gree in telecommunication engineering and the Ph.D.
degree in electronics from the Universitat Politècnica
de Catalunya (UPC), Barcelona, Spain, in 1994 and
1997, respectively.
In 1994, he joined the Department of Electronic
Engineering, UPC, as a full-time Associate Lecturer,
where, since 2001, he has been with the Motion Con-
trol and Industrial Applications Group, where the
group worked in the area of motor current signature
analysis. From 1994 to 2001, he was with the Sensor
Systems Group, where he worked in the areas of smart sensors, embedded
systems, and signal conditioning, acquisition, and processing. Since 1994, he
has taught courses on microprocessors and signal processing. In 1998, he
obtained a tenured position as an Associate Professor. His current R&D areas
include motor diagnosis, signal acquisition, smart sensors, embedded systems,
and remote labs. In the last several years, he has participated in several Spanish-
and European-funded research projects about these items. He has more than
30 referred journal and conference papers.
Luis Romeral (M’98) received the B.S. degree in
electrical engineering and the Ph.D. degree from
the Universitat Politècnica de Catalunya (UPC),
Barcelona, Spain, in 1985 and 1995, respectively.
He is currently with the Motion Control and Indus-
trial Applications Group, Department of Electronic
Engineering, UPC. The group’s major research activ-
ities concern induction and permanent magnet motor
drives, fault detection and diagnosis of electrical
motor drives, and energy efficiency. His research
interests include electric machines, power electron-
ics converters and modulation strategies, variable speed drive systems, fault
detection and motor diagnosis, and microprocessor-based real-time control al-
gorithms. He has developed and taught postgraduate courses on programmable
logic controllers, electrical drives and motion control, and sensors and actua-
tors. He has authored more than 50 peer-reviewed scientific papers, and seven
Ph.D. dissertations have been completed under his supervision over the last
years. He participates as a Partner or Subcontractor in European-Union-funded
projects, and, additionally, he is responsible for several research projects funded
by Spanish agencies. He has also participated as an Engineer or responsible for
research and development projects funded by local private companies.
Dr. Romeral is a member of the IEEE Industrial Electronics Society and the
European Power Electronics and Drives Association as well as the International
Federation of Automatic Control.
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... Literature has shown that waveform analysis can offer deeper insights into the degradation of power equipment [48], [62], [63], [95], [152] or even identification of loads [60], [61]. Although these methods are 'online' in nature, they rely on real-time data reporting and cloud computing to analyze and identify pre-cursors to catastrophic failures. ...
... For instance in machine fault diagnostics [95], current spectrum of an induction machine can contain abnormal harmonics due to eccentricity faults. Similarly, current harmonics have been reported to cause loss-of-life in distribution and large power transformers [163]. ...
Thesis
Full-text available
The electric grid is undergoing major transformations and developments resulting in unprecedented levels of volatility, uncertainty, and stress on grid infrastructure. Smart sensors and methods aiding in advanced visibility and situational awareness are key for tackling these issues. In this work, a decentralized architecture is proposed, where sensing, local computation and control capability are embedded in the edge devices, communicating with a set of trusted 'data mules' in a 'delay-tolerant' manner, while functioning autonomously. This system has been designed and implemented as an overall platform – called Global Asset Monitoring, Management and Analytics (GAMMA) Platform intended to provide the backbone for a global array of sensors and actuators. Further, as a building block for advanced current sensing solutions, a smart, low-cost ‘clip-on’ current sensor based on PCB-embedded Rogowski coil has been developed. The sensor hosts a novel signal conditioning stage allowing an 'auto-tuning' feature, resulting in a universal current sensor design for measuring a wide range of currents, including faults for smart grid applications. Finally, the research proposes a method to instrument and monitor key parameters for the most common electric utility asset – the pole-top distribution transformer. The work done in this research enables scalable, edge-intelligent sensing solutions for monitoring grid infrastructure, allowing utility operators to gain advanced visibility in an economical way.
... Between the two, the Rogowski coil essentially being air-cored provides lots of flexibility in terms of designing compact integrated switch current sensors for high-frequency detection applications [15,16]. Specifically, PCB-embedded Rogowski coils are among the favorites, due to inherently being compact, flexible, and cost-efficient [19][20][21][22][23]. Having several impactful advantages, the Rogowski coil detector cannot directly measure the desired current. ...
Preprint
Full-text available
Amongst several existing non-invasive switch current measurement solutions, the PCB-embedded Rogowski coil has a few more advantages to be used for high-frequency, compact, and high-power designs, especially due to being air-cored. This is while, negligible low-frequency gain, as well as integrator circuit configuration, resulting in a droop for the Rogowski coil detector output. Increasing the nominal switching frequency to hundreds of kilohertz and above causes the droop issue to become much more complicated to tackle, such that, provisional solutions such as the addition of electronic reset would also be near impossible to implement, due to very small on-time. In this paper, a novel complementary PCB-embedded Rogowski-pair detector is proposed to remove the droop burden, while maintaining high-frequency performance. The main idea is to pair up identical coils and allocate one to detect the DC component of the measured switch-current, while the other coil measures a fully AC-coupled signal. Given the characteristics of the switch-current waveforms, an analog electronic circuit combines the two sensor outputs and compensates for the absence of the DC component measured by a normal Rogowski coil. A well-tuned Rogowski-pair was prototyped and tested to measure the switch current of a high-speed Silicon-Carbide (SiC) module.
... Electronic transformers are widely used in electrical power systems, especially the electronic current transformer based on Rogowski coil and the electronic voltage transformer based on capacitive voltage divider [1][2][3][4][5][6][7][8][9]. Since the output signals of Rogowski coil and capacitive voltage divider are proportional to the rate of change of the primary signals, they are required to recover the measured primary signals, which is usually realized by electronic integrator circuits [10][11][12]. ...
Article
Full-text available
This paper analyses the formation mechanism of the transmission distortion of electronic voltage transformer, and points out that the integrator will magnify the transient transfer error and superimpose the dynamic additional component on the output signal, which may cause the transfer distortion of voltage signal in serious cases. To restrict the electronic transformer transient variable error effect on distance relay, a distance relay method using instantaneous value after equal transfer processes is proposed. It directly uses output differential signals of the capacitor voltage divider and Rogowski coil. The capacitor voltage divider and Rogowski coil are decomposed into several typical variable link in series. The virtual digital transfer link, which is constructed by the digital filter, is used to compensate for the difference parts of the transfer link, so that the voltage and current signals pass through the same transfer link. It can mitigate the influence of voltage and current signal transfer difference on the calculation accuracy of distance relay. The simulation results show that the proposed distance relay method has fast operation speed and is less affected by abnormal voltage and current signal transfer, and its performance is better than existing distance relay methods.
... While the constraints are that the difficulty determination of fault indicator and that the sensor position influences the results [85]. Apart from flux sensor, a Rogowski-coil current sensor without integrator circuit is used to detect eccentricity for the IM [86]. In [87], search coils, serving as stray flux sensors, are equally placed outside a generator to locate the SE position. ...
Article
Full-text available
Research on the modeling and fault diagnosis of rotor eccentricities has been conducted during the past two decades. A variety of diagnostic theories and methods have been proposed based on different mechanisms, and there are reviews following either one type of electric machines or one type of eccentricity. Nonetheless, the research routes of modeling and diagnosis are common, regardless of machine or eccentricity types. This article tends to review all the possible modeling and diagnostic approaches for all common types of electric machines with eccentricities and provide suggestions on future research roadmap. The paper indicates that a reliable low-cost non-intrusive real-time online visualized diagnostic method is the trend. Observer-based diagnostic strategies are thought promising for the continued research.
Article
Motor current signature analysis (MCSA) used in the diagnosis of centrifugal pumps has become a hot topic due to its non-intrusive and cost-effective nature. Yet, traditional current-based diagnosis methods show limitations as massive computation and power frequency interference. Moreover, most of them focus on the fault detection, fewer discuss the applications in operation evaluation. Therefore in this article, the hydro-mechanical-electric coupling effect that exists in the induction motor-centrifugal pump system is analyzed systematically. On this foundation, novel indicators that can reflect the harmonic distortion and noise proportion of stator current signals, and further indicate the hydraulic stability and operation status are proposed. Theoretical and experimental analysis support this paper, and results have demonstrated that our proposed indicators can indicate the operation change, identify the optimal operation region, and reflect the development of cavitation for centrifugal pumps. These indicators have the advantages of easy calculation and identification, therefore can be conveniently compared with accepted standards and enable immediate remedial actions to be implemented to ensure the stable operation.
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The thesis presents solutions to improve the performance of a partially levitating bearingless permanent magnet synchronous machine with a multi-three-phase winding. A combined winding topology, which consists of three independent three-phase sub-windings, is installed in the stator where each phase contributes to both the suspension force and the motoring torque. This work focuses on control algorithms, including fault-tolerant controls, a current limitation technique, and a current-sharing technique. Firstly, the thesis presents an analytical formulation of the force and torque generation in healthy operative conditions. Following, the three-phase and single-phase open-circuit fault conditions are also analysed. The analytical model of the machine is presented in a generic matrix form so that it can be applied to any machine with a multi-three-phase winding structure if the coupling among sectors is negligible. The fault-tolerant control algorithms address the issues of open-circuit faults of an entire three-phase sub-winding, of a single-phase in a three-phase sub-winding, or of two phases belonging to two different three-phase sub-windings. The theoretical analysis is verified with both Finite Elements Analysis and experimental tests. Then, the thesis proposes a current limitation technique. The main challenges with the combined winding configuration consist of decoupling the suspension force and torque generation and designing a proper current limitation technique. The latter is required in order to maintain the machine in safe operative conditions according to its current-voltage rating and its operative thermal limits. This thesis addresses the limitation technique based on the analytical models, considering both healthy and faulty conditions. In particular, the proposed current limitation technique allows prioritising the suspension force, which is considered a safety-critical output with respect to the torque in order to avoid the rotor touchdown. Numerical simulation results and experimental validation are provided to validate the algorithm. Finally, the thesis proposes a modular approach for a current-sharing control of the machine. A thorough explanation of the methodology used is presented, as well as control algorithms to consider the torque and force control combined with the current-sharing management of the machine. Particular emphasis is also placed on validating the modelling hypotheses based on a finite element characterisation of the machine electro-mechanical behaviour. The proposed control strategy is also extended to cater to the possibility of one or more inverters failure, thus validating the intrinsic advantage of the redundancy obtained by the system's modularity. An extensive experimental test is finally carried out on a prototyped machine. The obtained results validate the current-sharing operation in either healthy or faulty scenarios, both at steady-state and under transient conditions. These outcomes show the potential of the proposed strategy to increase the versatility of fault-tolerant drives applied to this machine topology.
Article
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Article
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A Rogowski current transducer is an invaluable tool for semiconductor and power electronic circuit development since it is nonintrusive and does not saturate at high currents. This paper reviews the operating principles, performance limitations and development of this measurement technology and outlines improvements to the integrator design that enables bandwidths of 10 MHz to be achieved