Identification of damaged rotor bar in induction motor based on transient analysis of start-up current using MODWT

The impact of a broken rotor bar on the induction motor’s stator current has been investigated in this paper. Its central concept depends on the discovery of distinctive features related to rotor faults in the time-frequency maps produced by the use of wavelet transform. The fundamental and the higher frequency components have been removed from the raw signal before the application of continuous wavelet transform (CWT) so that the expected fault signature can be easily identified. This is accomplished through the use of the maximal overlap discrete wavelet transform (MODWT), that dissolves the raw signal into several levels of detail and approximate levels containing specific frequency bands, and then reconstructs a signal using coefficients from some of those levels that capture only the frequencies of interest. This method based on start-up transient analysis allows for the avoidance of certain important drawbacks of the conventional MCSA, such as the difficulty in differentiating the closely placed fault frequencies and the likelihood of a wrong diagnostic. In 2D ANSYS Maxwell software, a machine model is created and faults are implemented and investigated. The effectiveness of the detection technique has been proven using real-time public data after first being tested on simulated data.

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Publication Details

Journal
Franklin Open
Published
2026-10-03
DOI
https://doi.org/10.1016/j.fraope.2026.100780
Primary Topic
Machine Fault Diagnosis Techniques
Type
article
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article

Identification of damaged rotor bar in induction motor based on transient analysis of start-up current using MODWT

Sudip Halder, Rajanikant A. Metri, Ishan Srivastava, Bimal Kumar Dora et al.
Franklin Open
Machine Fault Diagnosis Techniques
article

Identification of damaged rotor bar in induction motor based on transient analysis of start-up current using MODWT

Sudip Halder, Rajanikant A. Metri, Ishan Srivastava, Bimal Kumar Dora, Sunil Bhat, Chandrakant Bhattar
article en

Abstract

The impact of a broken rotor bar on the induction motor’s stator current has been investigated in this paper. Its central concept depends on the discovery of distinctive features related to rotor faults in the time-frequency maps produced by the use of wavelet transform. The fundamental and the higher frequency components have been removed from the raw signal before the application of continuous wavelet transform (CWT) so that the expected fault signature can be easily identified. This is accomplished through the use of the maximal overlap discrete wavelet transform (MODWT), that dissolves the raw signal into several levels of detail and approximate levels containing specific frequency bands, and then reconstructs a signal using coefficients from some of those levels that capture only the frequencies of interest. This method based on start-up transient analysis allows for the avoidance of certain important drawbacks of the conventional MCSA, such as the difficulty in differentiating the closely placed fault frequencies and the likelihood of a wrong diagnostic. In 2D ANSYS Maxwell software, a machine model is created and faults are implemented and investigated. The effectiveness of the detection technique has been proven using real-time public data after first being tested on simulated data.

Franklin OpenVol. 17
Babasaheb Bhimrao Ambedkar University (IN), Visvesvaraya National Institute of Technology (IN)
Openalex Percentile: Top 16%
Machine Fault Diagnosis Techniques
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