Angel Sapena-Bañó

• Doctor of Engineering
• Professor (Assistant) at Polytechnic University of Valencia

Induction motors are essential components in industry due to their efficiency and cost-effectiveness. This study presents an innovative methodology for automatic fault detection by analyzing images generated from the Fourier spectra of current signals using deep learning techniques. A new preprocessing technique incorporating a distinctive backgrou...

Undergraduate courses in electrical machines often include an introduction to the air gap magnetic field as a basic element in the energy conversion process. The students must learn the main properties of the field produced by basic winding configurations and how they relate to the winding current and frequency. This paper describes a new test equi...

This contribution describes the change in methodology introduced in the subject of electrical technology within the industrial technologies engineering degree at Escuela Técnica Superior de Ingeniería Industrial, Universitat Politècnica de València. The main purpose of the methodology change was to improve the attainment of student outcomes by the...

Induction machines (IMs) play a critical role in various industrial processes but are susceptible to degenerative failures, such as broken rotor bars. Effective diagnostic techniques are essential in addressing these issues. In this study, we propose the utilization of convolutional neural networks (CNNs) for detection of broken rotor bars. To acco...

Este artículo presenta un nuevo programa para ayudar a los estudiantes en su aprendizaje de la asignatura de Tecnología Eléctrica del Grado de Ingeniería Industrial de la Universitat Politècnica de València, más concretamente en el temario concerniente al dimensionado de instalaciones eléctricas y a la protección de estas instalaciones respecto a f...

Diagnosis of induction machines based on deep learning models is becoming a trend in maintenance systems of modern industry. The implementation of such systems allows low-cost industrial monitoring due to the characteristics of hardware and software. However, combining deep learning models with current embedded systems is a difficult issue due to t...

Induction machines (IMs) are a critical component of many industrial processes, and their failure can cause large economic losses. Condition-based maintenance systems (CBMs) that are capable of detecting their failures at an incipient stage can reduce these risks by continuously monitoring the IMs’ condition. The development and reliable operations...

The locally optimized chirplet spectrogram (LOCS) is a novel method proposed in this work for generating a high-resolution and cost-effective spectrogram of the induction machine (IM) current, suitable for the identification of fault-related harmonics in transient conditions. Its distinctive novelty is that it optimizes automatically the parameters...

Skin and proximity effects can cause a non-uniform current distribution in the electrical conductors used in alternating current (ac) busbar systems, which increases resistance, decreases internal inductance, and causes asymmetries in the electromagnetic fields and forces. As no explicit solution for the ac resistance or the ac internal inductance...

Since it is not efficient to physically study many machine failures, models of faulty induction machines (IMs) have attracted a rising interest. These models must be accurate enough to include fault effects and must be computed with relatively low resources to reproduce different fault scenarios. Moreover, they should run in real time to develop on...

Induction machines are essential components of many industrial installations and, therefore, their faults must be detected early. Fault detection using current spectrum analysis is attracting an increasing interest as a condition-based monitoring technique. However, its use to detect rotor asymmetries in high-power induction machines, which operate...

Induction machines (IMs) are one of the main sources of mechanical power in many industrial processes, especially squirrel cage IMs (SCIMs), due to their robustness and reliability. Their sudden stoppage due to undetected faults may cause costly production breakdowns. One of the most frequent types of faults are cage faults (bar and end ring segmen...

Over the years, induction machines (IMs) have become key components in industry applications as mechanical power sources (working as motors) as well as electrical power sources (working as generators). Unexpected breakdowns in these components can lead to unscheduled down time and consequently to large economic losses. As breakdown of IMs for failu...

Motor current signature analysis has become a widespread fault diagnosis technique for induction machines, because it is non-invasive, and requires low resources of hardware (a current sensor) and software (a fast Fourier transform). Nevertheless, its industrial application faces practical problems. One of its most challenging scenarios is the dete...

The development of condition monitoring (CM) systems of induction machines (IMs) is essential for the industry because the early fault detection would help engineers to optimise maintenance plans. However, the use of several IMs to test and validate the fault diagnosis methods developed requires also costly test benches that, anyway, often face lim...

This paper presents an application for the energy monitoring of commercial refrigeration facility, based on the concept and technology of the Internet of Things. The purpose of this application is to offer support to the activities of energy audits ant to the implementation of energy management systems, where the energy consumption of a facility mu...

Motor current signature analysis (MCSA) is a fault diagnosis method for induction machines (IMs) that has attracted wide industrial interest in recent years. It is based on the detection of the characteristic fault signatures that arise in the current spectrum of a faulty induction machine. Unfortunately, the MCSA method in its basic formulation ca...

Induction machines (IMs) are critical components of many industrial processes, what justifies the use of condition-based maintenance (CBM) systems for detecting their faults at an early stage, in order to avoid costly breakdowns of production lines. The development of CBM systems for IMs relies on the use of fast models that can accurately simulate...

Condition based maintenance (CBM) systems of induction machines (IMs) require fast and accurate models that can reproduce the fault related harmonics generated by different kinds of faults. Such models are needed to develop new diagnostic algorithms for detecting the faults at an early stage, to analyse the physical interactions between simultaneou...

Fault diagnosis of induction motors through the analysis of the stator current is increasingly being used in maintenance systems because it is non-invasive and has low requirements of hardware and software. Nevertheless, its industrial application faces some practical limitations. In particular, the detection of fault harmonics that are very close...

Most industrial processes are run by induction machines (IMs). Condition monitoring of IM assures their continuity of service, and it may avoid highly costly breakdowns. Among the methods for condition monitoring, on-line motor current signature analysis is being attracting a rising interest, because it is non-invasive, and it can identify a wide v...

Induction machines drive many industrial processes and their unexpected failure can cause heavy production losses. The analysis of the current spectrum can identify online the characteristic fault signatures at an early stage, avoiding unexpected breakdowns. Nevertheless, frequency domain analysis requires stable working conditions, which is not th...

Fault diagnosis of rotor asymmetries of IM using the stator current relies on the detection of the characteristic signatures of the fault harmonics in the current spectrum. In some scenarios, such as large induction machines running at a very low slip, or unloaded machines tested offline, this technique may fail. In these scenarios, the fault harmo...

Induction machines drive many industrial processes, and their unexpected failure can cause heavy production losses. The analysis of the current spectrum can identify online the characteristic fault signatures at an early stage, avoiding unexpected breakdowns. Nevertheless, frequency domain analysis requires stable working conditions, which is not t...

While wind turbine (WT) power capacities continue to increase and new offshore developments are being deployed, operation and maintenance (O&M) costs continue to rise, becoming the center of attention in the wind energy sector. The electric generator is among the top three contributors to failure rates and downtime of WTs, where the doubly-fed indu...

Induction machines (IMs) power most modern industrial processes (induction motors) and generate an increasing portion of our electricity (doubly fed induction generators). A continuous monitoring of the machine’s condition can identify faults at an early stage, and it can avoid costly, unexpected shutdowns of production processes, with economic los...

Fault diagnosis of induction machines (IMs) requires a fast model of the machine, for adjusting fault thresholds in data-driven diagnostic methods, for computing the residuals in model-driven diagnostic systems, or for training autonomous expert systems. Due to the interaction between time and space harmonics under faulty conditions, this model mus...

The development of advanced fault diagnostic systems for induction machines through the stator current requires accurate and fast models that can simulate the machine under faulty conditions, both in steady-state and in transient regime. These models are far more complex than the models used for healthy machines, because one of the effect of the fa...

The aim of this paper is to introduce a new methodology for the fault diagnosis of induction machines working in the transient regime, when time-frequency analysis tools are used. The proposed method relies on the use of the optimized Slepian window for performing the short time Fourier transform (STFT) of the stator current signal. It is shown tha...

AC lines of industrial busbar systems are usually built using conductors with rectangular cross sections, where each phase can have several parallel conductors to carry high currents. The current density in a rectangular conductor, under sinusoidal conditions, is not uniform. It depends on the frequency, on the conductor shape, and on the distance...

The aim of this paper is to introduce a new methodology for the fault diagnosis of induction machines working in transient regime, when time-frequency analysis tools are used. The proposed method relies on the use of the optimized Slepian window for performing the short time Fourier transform (STFT) of the stator current signal. It is shown that fo...

The aim of this paper is to introduce a new methodology for the fault diagnosis of induction machines working in transient regime, when time-frequency analysis tools are used. The proposed method relies on the use of the optimized Slepian window for performing the short time Fourier transform (STFT) of the stator current signal. It is shown that fo...

Transient-based methods for fault diagnosis of induction machines (IMs) are attracting a rising interest, due to their reliability and ability to adapt to a wide range of IM's working conditions. These methods compute the time-frequency (TF) distribution of the stator current, where the patterns of the related fault components can be detected. A si...

This paper introduces a new approach for improving the fault diagnosis in induction motors under time-varying conditions. A significant amount of published approaches in this field rely on representing the stator current in the time-frequency domain, and identifying the characteristic signatures that each type of fault generates in this domain. How...

Purpose Rectangular conductors play an important role in planar transmission line structures, multiconductor transmission lines, in power transmission and distribution systems, LCL filters, transformers, industrial busbars, MEMs devices, among many others. The precise determination of the inductance of such conductors is necessary for their design...

This paper introduces a speed-sensorless method for detecting rotor asymmetries in wound rotor induction machines working under nonstationary conditions. The method is based on the time-frequency analysis of rotor currents and on a subsequent transformation, which leads to the following goals: unlike conventional spectrograms, it enables to show th...

Diagnosis of induction motors in industrial facilities is crucial to avoid unexpected outages that may lead a huge economic losses. Hence, this field has attracted a rising interest, in order to improve the accuracy of the fault diagnosis and to extend it to a growing number of different types of faults. Over the last decade, and recently, new diag...

Improved fault diagnostic techniques in wind turbines is a field of growing interest, given the negative impact that unexpected breakdowns have on the profitability of wind farms. Traditional and new diagnostic techniques mainly based, respectively, on vibration and generator current monitoring cannot be applied easily to small wind groups due to t...

The discrete wavelet transform (DWT) has attracted a rising interest in recent years to monitor the condition of rotating electrical machines in transient regime, because it can reveal the time–frequency behavior of the current’s components associated to fault conditions. Nevertheless, the implementation of the wavelet transform (WT), especially on...

The diagnosis of induction machines using Fourier transform relies on tracking the frequency signature of each type of fault in the current's spectrum, but this signature depends on the machine's slip and the supply frequency, so it must be recomputed for each working condition by trained personnel or by diagnostic software. Besides, sampling the c...

Fault diagnosis of rotor asymmetries in induction machines working at a very low slip, through Fourier-based methods, usually requires a long acquisition time to achieve a high spectral resolution and a high sampling frequency to reduce aliasing effects. However, this approach generates a huge amount of data, which makes its implementation difficul...

Most of automation systems in industry are based on Programmable Logical Controllers (PLCs) due to its reliability and immunity to industrial environments. Besides, PLCs's flexibility and capabilities have allowed human to automate a huge number of industrial processes. In this paper a new multilevel graphical and modular approach is proposed for p...

This paper introduces a new method of fault diagnosis for induction motors, the Multilayer Park's Vector Approach, derived from the well-known fault diagnostic method based on Park's Vector Approach analysis. This new method allows the detection of failures in steady and transient regimes operation on induction motors. The resulting vector generate...

Diagnosis of faults in induction motors has been accomplished traditionally following a two stage procedure: first, the selected diagnostic quantity is measured and treated with an appropriate signal analysis tool, and, second, the diagnostic signal is evaluated, either by trained personnel or by automatic systems, to determine the presence and the...

Induction motors play a key role in the industrial field. Therefore, continuous monitoring and online diagnostic systems are essential to guarantee the seamless operation of modern industrial facilities. But, in moder automation installations, motor operation is controlled by programmable logic controllers (PLCs), which have become the main field c...

Improved fault diagnostic techniques in wind turbines is a field of growing interest, given the negative impact that unexpected breakdowns have on the profitability of wind farms. New diagnostic techniques based on generator currents monitoring have recently been developed, but their use is still irrelevant despite the advantages that current monit...

Virtual Instruments offer new possibilities for the electrical machines students to visualize and understand facts and correlations that otherwise often require more or less difficult calculations to be performed beforehand. The recent trend on the introduction of Data Acquisition systems (manipulated, accessed and controlled by means of VIs), eith...

Packaging automated industry is based on PLC control systems. Most of them are IEC 61131-3 PLC compliant. The standard was the first step to introduce Object Oriented Programming (OOP) features in the PLC based automation such as encapsulation in Function Blocks. Nevertheless, other major benefits of OOP such inheritance, or polymorphism weren't de...

Programmable Logic Controllers (PLC) are key components in modern packaging automation systems. But their success has led to the presence of a broad range of brands and models, each one with its own and unique features, but also with its own environment for software development. This situation has some major drawbacks: it is very difficult to upgra...

Undergraduate courses in electrical machines often include an introduction to their magnetic circuits and to the various magnetic materials used in their construction and their properties. The students must learn to be able to recognize and compare the permeability, saturation, and losses of these magnetic materials, relate each material to its spe...

The diagnosis of electrical motors through the detection of fault frequency signatures in the current's spectrum has become an established standard in the field of industrial maintenance systems. Nevertheles, its implementation on devices with low computing power remains a practical challenge. Industrial controllers, such as programmable logic cont...

On-line diagnosis of induction motors faults requires special, high speed hardware, such as DSP or FPGAs. Practical implementation of diagnosis algorithms in such a device must take into account the limited amount of memory available for storing sampled data, and for performing spectral analysis using the FFT. Another practical problem is the need...

The use of advanced diagnosis techniques for induction motor (IM) faults relies on the use of automated classifiers, such as those based on support vector machines (SVMs), which are able to assess the condition of the machine using a set of relevant features extracted either from the time domain or from the frequency domain machines signals. But th...

This paper presents an open, multilevel condition monitoring system for induction motors (IMs). The current, voltage, speed and temperature values of the IM are measured with commercial, industrial equipment (power analyzer, temperature relay), and transmitted to a programmable logic controller (PLC) through a MODBUS industrial network. The PLC pro...