Induction motors' faults detection and localization using stator current advanced signal processing techniques

1999 ◽  
Vol 14 (1) ◽  
pp. 14-22 ◽  
Author(s):  
M.E.H. Benbouzid ◽  
M. Vieira ◽  
C. Theys
Keyword(s):  
Signal Processing ◽  
Induction Motors ◽  
Stator Current ◽  
Processing Techniques ◽  
Detection And Localization ◽  
Signal Processing Techniques

scholarly journals Comparative Analysis of Signal Processing Techniques for Fault Detection in Three Phase Induction Motor

2021 ◽  
Vol 3 (1) ◽  
pp. 61-76
Author(s):  
Thomas Amanuel ◽  
Amanuel Ghirmay ◽  
Huruy Ghebremeskel ◽  
Robel Ghebrehiwet ◽  
Weldekidan Bahlibi
Keyword(s):  
Signal Processing ◽  
Fault Detection ◽  
Induction Motor ◽  
Induction Motors ◽  
Research Work ◽  
Detection Accuracy ◽  
Frequency Information ◽  
Three Phase ◽  
Processing Techniques ◽  
Signal Processing Techniques

Signal processing is considered as an efficient technique to detect the faults in three-phase induction motors. Detection of different varieties of faults in the rotor of the motor are widely studied at the industrial level. To extend further, this research article presents the analysis on various signal processing techniques for fault detection in three-phase induction motor due to the damages in rotor bar. Usually, Fast Fourier Transform (FFT) and STFT are used to analyze the healthy and faulty motor conditions based on the signal characteristics. The proposed study covers the advantages and limitations of the proposed wavelet transform (WT) and each technique for detecting the broken bar of induction motors. The good frequency information can be collected from FFT techniques for handling multiple faults identification in three-phase induction motor. Despite the hype, the detection accuracy gets reduced during the dynamic condition of the machine because the frequency information on sudden time changes cannot be employed by FFT. The WT method signal analysis is compared with FFT to propose fault detection method for induction motor. The WT method is proving better accuracy when compared to all existing methods for signal information analysis. The proposed research work has simulated the proposed method with MATLAB / SIMULINK and it helps to effectively detect the healthy and faulty conditions of the motor.

scholarly journals TÉCNICAS DE PROCESAMIENTO DE SEÑALES UTILIZADAS PARA EL ANÁLISIS DE LA DISTORSIÓN ARMÓNICA GENERADA POR VARIADORES DE FRECUENCIA EN MOTORES DE INDUCCIÓN

2015 ◽  
Vol 6 (1) ◽  
pp. 72
Author(s):  
Manuel Ivan Balleteros Csmcho ◽  
Francy Julieth Cadena Villalba ◽  
Adolfo Andres Jaramillo Matta
Keyword(s):  
Signal Processing ◽  
Induction Motors ◽  
State Of The Art ◽  
Harmonic Distortion ◽  
Variable Frequency ◽  
Variable Frequency Drive ◽  
Driven System ◽  
Cage Rotor ◽  
Processing Techniques ◽  
Signal Processing Techniques

Se presenta una detallada revisión del estado del arte de las técnicas de procesamiento de señales utilizadas para el análisis de la distorsión armónica generada por variadores de frecuencia en motores de inducción con rotor jaula de ardilla, referenciando algunas de las investigaciones más relevantes relacionadas con este tema. Finalmente, son identificadas oportunidades de investigación que a la fecha no han sido tratadas por la comunidad científica en este campo del conocimiento.Signal Processing Techniques Used for Analyzing Harmonic Distortion Generated by Variable Frequency Drive in Induction Motors Abstract This article presents a detailed review of the state of the art of signal processing techniques used for the analysis of harmonic distortion generated by variable frequency induction motors with squirrel cage rotor is presented, referencing some of the most relevant research related with this issue. Finally, are identified research opportunities that to date have not been addressed by the scientific community in this field of knowledge.Keywords: electric motor-driven system, state of the art, harmonic distortion, signal processing techniques.

Experimental investigation and comparative study of signal processing techniques dedicated for the diagnosis of rotor failures in the induction motors

2022 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Wissam Dehina ◽  
Mohamed Boumehraz ◽  
Wissam Dehina ◽  
Frédéric Kratz
Keyword(s):  
Signal Processing ◽  
Spectral Density ◽  
Power Spectral Density ◽  
Theoretical Development ◽  
Content Type ◽  
Spectral Density Estimation ◽  
Stator Current ◽  
Power Spectral ◽  
Processing Techniques ◽  
Signal Processing Techniques

Purpose The purpose of this paper is to propose applications of advanced signal-processing techniques for the diagnosis and detection of rotor fault in an induction machine. Two techniques are used: spectral analysis techniques and time frequency techniques for the diagnosis of an electrical machine. One is based on the power spectral density estimation techniques, such as periodogram and Welch periodogram. The second method is based on Hilbert transform (HT) to extract the envelope for the stator current. Then, this signal is processed via discrete wavelet transform (DWT) for determining the faulty components in the spectrum of the stator current envelope and identifying the eigenvalues of energies (HDWT). Design/methodology/approach First, this paper focused on theoretical development and a comparative study of these signal-processing techniques, which are based on the periodogram, Welch periodogram, HT and the DWT to extract the envelope for the stator current; it is used to compute the energy stored in each decomposition level obtained by the stator current envelope (HDWT). Moreover, the Welch periodogram is applied to obtain the envelope spectrum. Findings The simulation obtained and the experimental validation results of the proposed methods through MATLAB environment show the effectiveness of the proposed approaches with a good accuracy by power spectral density estimation techniques (periodogram and Welch periodogram). Moreover, the faults are manifested through the appearance of new frequencies components, as well as the envelope for the stator current (HT and DWT). This approach is effective for non-stationary and stationary signal to extract useful information for the detection of broken bar fault. Originality/value The current paper proposes a new diagnosis method for the detection and characterization of broken rotor bars defects early; it is founded primarily on theoretical development, and the comparison is based on the power spectral density technique (periodogram and Welch periodogram) and the computation of the energy stored in each decomposition level (precisely the HT and DWT). Moreover, the Welch periodogram is applied to obtain the envelope spectrum. The main advantages of the proposed techniques increase their reliability and availability.

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