TR2023-039
Broken-bar Fault Detection by Injecting a Frequency Modulated Continuous Wave Signal
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- "Broken-bar Fault Detection by Injecting a Frequency Modulated Continuous Wave Signal", IEEE International Electric Machines and Drives Conference (IEMDC), DOI: 10.1109/IEMDC55163.2023.10239083, May 2023.BibTeX TR2023-039 PDF
- @inproceedings{Liu2023may,
- author = {Liu, Dehong and Varatharajan, Anantaram and Goldsmith, Abraham and Kong, Chuizheng and Sigatapu, Laxman and Wang, Yebin},
- title = {Broken-bar Fault Detection by Injecting a Frequency Modulated Continuous Wave Signal},
- booktitle = {IEEE International Electric Machines and Drives Conference (IEMDC)},
- year = 2023,
- month = may,
- doi = {10.1109/IEMDC55163.2023.10239083},
- isbn = {979-8-3503-9900-4},
- url = {https://www.merl.com/publications/TR2023-039}
- }
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- "Broken-bar Fault Detection by Injecting a Frequency Modulated Continuous Wave Signal", IEEE International Electric Machines and Drives Conference (IEMDC), DOI: 10.1109/IEMDC55163.2023.10239083, May 2023.
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MERL Contacts:
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Research Areas:
Electric Systems, Multi-Physical Modeling, Signal Processing
Abstract:
It is challenging to detect broken-bar faults in squirrel-cage induction motors using motor current signature analysis (MCSA) due to the small magnitude and proximity of the fault signature relative to the operating frequency component, especially when the motor slip is very small. In this paper we propose a signal injection method to detect the broken-bar fault by injecting a frequency modulated continuous wave (FMCW) signal to the stator voltage. Model analysis and simulation show that under broken-bar fault conditions, the injected FMCW signal induces another FMCW signal of a lower frequency band, which as a newly-defined fault signature can be extracted by analyzing cross correlation between the injected signal and the induced signal in the frequency domain. Compared to other signal injection methods, our method is more robust and insusceptible to harmonic interference. Experimental results on a three-phase squirrel-cage induction motor validate our method in detecting broken-bar faults from noisy measurements even when the motor slip is very small.
Related News & Events
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NEWS MERL researchers presented four papers and organized a special session at The 14th IEEE International Electric Machines and Drives Conference Date: May 15, 2023 - May 18, 2023
Where: San Francisco, CA
MERL Contacts: Dehong Liu; Bingnan Wang
Research Areas: Applied Physics, Control, Electric Systems, Machine Learning, Optimization, Signal ProcessingBrief- MERL researchers Yusuke Sakamoto, Anantaram Varatharajan, and
Bingnan Wang presented four papers at IEMDC 2023 held May 15-18 in San Francisco, CA. The topics of the four oral presentations range from electric machine design optimization, to fault detection and sensorless control. Bingnan Wang organized a special session at the conference entitled: Learning-based Electric Machine Design and Optimization. Bingnan Wang and Yusuke Sakamoto together chaired the special session, as well as a session on: Condition Monitoring, Fault Diagnosis and Prognosis.
The 14th IEEE International Electric Machines and Drives Conference: IEMDC 2023, is one of the major conferences in the area of electric machines and drives. The conference was established in 1997 and has taken place every two years thereafter.
- MERL researchers Yusuke Sakamoto, Anantaram Varatharajan, and