Antonio Garcia Espinosa

Bearing Fault Detection by a Novel Condition-Monitoring Scheme Based on Statistical-Time Features and Neural Networks

Bearing degradation is the most common source of faults in electrical machines. In this context, this work presents a novel monitoring scheme applied to diagnose bearing faults. Apart from detecting local defects, i.e., single-point ball and raceway faults, it takes also into account the detection of distributed defects, such as roughness. The development of diagnosis methodologies considering both kinds of bearing faults is, nowadays, subject of concern in fault diagnosis of electrical machines. First, the method analyzes the most significant statistical-time features calculated from vibration signal. Then, it uses a variant of the curvilinear component analysis, a nonlinear manifold learning technique, for compression and visualization of the feature behavior. It allows interpreting the underlying physical phenomenon. This technique has demonstrated to be a very powerful and promising tool in the diagnosis area. Finally, a hierarchical neural network structure is used to perform the classification stage. The effectiveness of this condition-monitoring scheme has been verified by experimental results obtained from different operating conditions.

Modeling of Surface-Mounted Permanent Magnet Synchronous Motors With Stator Winding Interturn Faults

This paper develops and analyzes a parametric model for simulating healthy and faulty surface-mounted permanent magnet synchronous motors. It allows studying the effects of stator winding interturn short-circuit faults. A relevant feature of the developed model is that it deals with spatial harmonics due to a nonsinusoidal rotor permanent magnet configuration. Additionally, the proposed model is valid for studying the behavior of these machines running under nonstationary conditions, including load or speed variations. Stator current spectra obtained from simulations performed by applying the proposed model show a close similitude with experimental results, highlighting the potential of such a model to understand the effects of stator winding failures on the current spectrum and allowing it to carry out an automatic diagnosis of such faults.

Fault Detection by Means of Hilbert–Huang Transform of the Stator Current in a PMSM With Demagnetization

This paper presents a study of the permanent magnet synchronous motor (PMSM) running under demagnetization. The simulation has been carried out by means of two dimensional (2-D) finite element analysis (FEA), and simulations results were compared with experimental results. The demagnetization fault is analyzed by means of decomposition of stator currents obtained at different speeds. The Hilbert Huang transform (HHT) is used as processing tool. This transformation represents time-dependent series in a two-dimensional (2-D) time-frequency domain by extracting instantaneous frequency components within the signal through an Empirical Mode Decomposition (EMD) process.

Detection of Demagnetization Faults in Permanent-Magnet Synchronous Motors Under Nonstationary Conditions

This paper presents the results of our study of the permanent-magnet synchronous motor (PMSM) running under demagnetization. We examined the effect of demagnetization on the current spectrum of PMSMs with the aim of developing an effective condition-monitoring scheme. Harmonics of the stator currents induced by the fault conditions are examined. Simulation by means of a two-dimensional finite-element analysis (FEA) software package and experimental results are presented to substantiate the successful application of the proposed method over a wide range of motor operation conditions. Methods based on continuous wavelet transform (CWT) and discrete wavelet transform (DWT) have been successfully applied to detect and to discriminate demagnetization faults in PMSM motors under nonstationary conditions. Additionally, a reduced set of easy-to-compute discriminating features for both CWT and DWT methods has been defined. We have shown the effectiveness of the proposed method by means of experimental results.

Feature Extraction of Demagnetization Faults in Permanent-Magnet Synchronous Motors Based on Box-Counting Fractal Dimension

This paper presents a methodology for feature extraction of a new fault indicator focused on detecting demagnetization faults in a surface-mounted permanent-magnet synchronous motors operating under nonstationary conditions. Preprocessing of transient-current signals is performed by applying Choi-Williams distribution to highlight the salient features of this demagnetization fault. In this paper, fractal dimension calculation based on the computation of the box-counting method is performed to extract the optimal features for diagnosis purposes. It must be noted that the applied feature-extraction process is autotuned, so it does not depend on the severity of the fault and is applicable to a wide range of operating conditions of the motor. The performance of the proposed system is validated experimentally. According to the obtained results, the proposed methodology is reliable and feasible for diagnosing demagnetization faults in industrial applications.

A Sensorless Method for Controlling the Closure of a Contactor

We propose a new closed-loop sensorless method for reducing contact bounce on closure of a contactor. Several approaches to the problem have already been described; most of them use some kind of sensor to establish the position and speed of the contacts in real time, whereas in our approach, the position and speed of the moving armature and contacts are calculated by using only the current and voltage values of the contactor coil as control inputs. A fuzzy controller takes as input the position and velocity of the armature and provides as output an intensity set point that controls the velocity of the closure of the contacts. Furthermore, we have developed a low-cost electronic module that implements the control system and integrates it in the contactor. The module eliminates the bounces completely and thus prevents the contacts from repeatedly making and breaking the circuit.

A Novel Parametric Model for AC Contactors

This paper develops a robust and fast parametric model to describe the dynamic behavior of an ac contactor. The model solves simultaneously the mechanical and electromagnetic coupled differential equations that govern its dynamic response. It deals with the shading rings and takes into account the fringing flux. Data from simulations carried out by applying the presented parametric model are compared with experimental data, demonstrating the models validity and effectiveness.

A Computer Model for Teaching the Dynamic Behavior of AC Contactors

Ac-powered contactors are extensively used in industry in applications such as automatic electrical devices, motor starters, and heaters. In this work, a practical session that allows students to model and simulate the dynamic behavior of ac-powered electromechanical contactors is presented. Simulation is carried out using a rigorous parametric model of the ac contactor that avoids simplification assumptions and is thoroughly explained. The goal of this practical is to introduce students to the topic of dynamic simulation of real devices. It covers both the transient and the steady-state response of the electromechanical system under study. The proposed methodology is flexible and not particularly time-consuming, and it allows the students easily to change the electromechanical constants of the contactor they are studying. The results of the simulations were compared with experimental data acquired by the students; a close similarity between real and simulated data was observed. The Technical University of Catalonia (UPC), Spain, has incorporated the simulation methodology proposed in this paper in a practical session of an electrical engineering course.

Simulation and Fault Detection of Short Circuit Winding in a Permanent Magnet Synchronous Machine (PMSM) by means of Fourier and Wavelet Transform

This paper presents permanent magnet synchronous machines with short circuit of turns. Two-dimensional (2-D) finite element analysis (FEA) is used to simulation of PMSM under fault. PMSM is working at nominal condition and speed change of 5000 rpm. Relationships between stator-current-induced harmonics were investigated by means of Fourier (FFT) and discrete wavelet transforms (DWT). The simulation is also compared with experimental results.

Sensorless Control and Fault Diagnosis of Electromechanical Contactors

This paper describes a novel algorithm for a closed-loop sensorless control of electromagnetic devices. It integrates a novel fault diagnosis algorithm of the whole electromagnetic circuit. Applied to a contactor with a dc core, it eliminates the armature and contact bounce, whether it is ac or dc powered and at either 50 or 60 Hz. The position and velocity of the moving armature and contacts are calculated by means of the online determination of the inductance using only the measured current and voltage values of the contactor coil as control inputs. A fuzzy controller takes the position and velocity of the armature as input and provides the current set point as output, which controls the velocity of closure of the contacts. The algorithm has been implemented in a low-cost electronic module.