Luis Romeral

Fault Detection in Induction Machines Using Power Spectral Density in Wavelet Decomposition

Motor-current-signature analysis has been successfully used in induction machines for fault diagnosis. The method, however, does not always achieve good results when the speed or the load torque is not constant, because this causes variations on the motor-slip and fast Fourier transform problems appear due to a nonstationary signal. This paper proposes a new method for motor fault detection, which analyzes the spectrogram based on a short-time Fourier transform and a further combination of wavelet and power-spectral-density (PSD) techniques, which consume a smaller amount of processing power. The proposed algorithms have been applied to detect broken rotor bars as well as shorted turns. Besides, a merit factor based on PSD is introduced as a novel approach for condition monitoring, and a further implementation of the algorithm is proposed. Theoretical development and experimental results are provided to support the research.

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.

Short-Circuit Detection by Means of Empirical Mode Decomposition and Wigner–Ville Distribution for PMSM Running Under Dynamic Condition

This paper presents and analyzes a method for short-circuit fault detection in a permanent-magnet synchronous motor (PMSM). The study includes steady-state condition and speed transients in motor operation. The stator current is decomposed by empirical mode decomposition (EMD), which generates a set of intrinsic mode functions (IMFs). Quadratic time-frequency (TF) distributions such as smoothed pseudo-Wigner-Ville and Zhao-Atlas-Marks are applied on the more significant IMFs for fault detection. Simulations and experimental laboratory tests validate the algorithms and demonstrate that this kind of TF analysis can be applied to detect and identify short-circuit failures in PMSM.

Novel direct torque control (DTC) scheme with fuzzy adaptive torque-ripple reduction

Investigations were carried out on a novel direct torque control system, which not only reduces the undesirable torque ripple by up to 98% by means of introducing a modulation between the selected active state and a zero state, but also maintains constant switching frequency. Additionally, this two-state modulator is fuzzy adaptive and may be applied to any induction motor. Simulation and the results of experiment illustrate the operation and performance of the proposed fuzzy-logic-based controller.

Detection of Demagnetization Faults in Surface-Mounted Permanent Magnet Synchronous Motors by Means of the Zero-Sequence Voltage Component

This paper develops and analyzes an online methodology to detect demagnetization faults in surface-mounted permanent magnet synchronous motors. The proposed methodology, which takes into account the effect of the inverter that feeds the machine, is based on monitoring the zero-sequence voltage component of the stator phase voltages. The theoretical basis of the proposed method has been established. Attributes of the method presented here include simplicity, very low computational burden, and high sensibility. Since the proposed method requires access to the neutral point of the stator windings, it is especially useful when dealing with fault tolerant systems. A simple expression of the zero-sequence voltage component is deduced, which is proposed as a fault indicator parameter. Both simulation and experimental results presented in this paper show the potential of the proposed method to provide helpful and reliable data to carry out an online diagnosis of demagnetization failures in the rotor permanent magnets.

Diagnosis of Interturn Faults in PMSMs Operating Under Nonstationary Conditions by Applying Order Tracking Filtering

Interturn faults in permanent magnet synchronous machines may have very harmful effects if not early identified. This study deals with the detection of such faults when the machine operates under varying speed conditions. The performance of two methods is analyzed and compared, i.e., the analysis of the third harmonic of the stator currents and the first one of the zero-sequence voltage components. The Vold-Kalman filtering order tracking algorithm is introduced and applied to track the harmonics of interest when the machine operates under a wide speed range and different load levels. This study also presents two reliable fault indicators especially focused to detect stator winding interturn faults under nonstationary speed conditions. Experimental results endorse the methodology proposed, showing its potential to carry out a reliable fault diagnosis scheme.

A Back-emf Based Method to Detect Magnet Failures in PMSMs

Demagnetization faults are troublesome because they have a profound impact on the overall performance of permanent magnet synchronous motors (PMSMs). This work presents and verifies experimentally a system to detect such faults which is based on the measure of the zero sequence voltage component (ZSVC). The proposed method is also appropriate for inverter fed machines and is particularly useful when dealing with fault tolerant systems. A fault severity index which allows quantifying the harshness of such faults is also proposed and its behavior is analyzed from experimental data. Features of the proposed method include low computational burden, simplicity and high sensitivity. Experimental results conducted at different speed and load conditions show the potential of the proposed fault severity index for online diagnosis of demagnetization failures.

Motor Fault Detection Using a Rogowski Sensor Without an Integrator

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.