Experimental investigation in induction motors using signal processing techniques for early detection of inter-turn short circuit faults

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.

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Advanced Signal Processing Techniques for Bearing Fault Detection in Induction Motors

2018 15th International Multi-Conference on Systems, Signals & Devices (SSD) ◽

10.1109/ssd.2018.8570403 ◽

2018 ◽

Cited By ~ 2

Author(s):

Firas Ben Abid ◽

Ahmed Braham

Keyword(s):

Signal Processing ◽

Fault Detection ◽

Induction Motors ◽

Bearing Fault ◽

Bearing Fault Detection ◽

Processing Techniques ◽

Signal Processing Techniques

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On-Line Fault Detection of Inverter-Fed Induction Motors Using Advanced Signal Processing Techniques

IFAC Proceedings Volumes ◽

10.1016/s1474-6670(17)37512-2 ◽

2000 ◽

Vol 33 (11) ◽

pp. 1119-1124 ◽

Cited By ~ 3

Author(s):

Armin Wolfram ◽

Rolf Isermann

Keyword(s):

Signal Processing ◽

Fault Detection ◽

Induction Motors ◽

On Line ◽

Processing Techniques ◽

Signal Processing Techniques

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

REDES DE INGENIERÍA ◽

10.14483/udistrital.jour.redes.2015.1.a05 ◽

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.

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