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Comparison of Fault Detection Techniques for Induction Motors

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2021
Amir Ahmed Qazi, Jawaid Daudpoto, Salman Ahmed Shaikh

Amir Ahmed Qazi, Jawaid Daudpoto and Salman Ahmed Shaikh. Comparison of Fault Detection Techniques for Induction Motors. International Journal of Computer Applications 183(38):13-19, November 2021. BibTeX

	author = {Amir Ahmed Qazi and Jawaid Daudpoto and Salman Ahmed Shaikh},
	title = {Comparison of Fault Detection Techniques for Induction Motors},
	journal = {International Journal of Computer Applications},
	issue_date = {November 2021},
	volume = {183},
	number = {38},
	month = {Nov},
	year = {2021},
	issn = {0975-8887},
	pages = {13-19},
	numpages = {7},
	url = {},
	doi = {10.5120/ijca2021921778},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


In the era of twenty-first century, induction motor plays a dominant role in industrial processes and essentially run out 40 to 50 % of total energy demand. Accordingly, their safety, durability, and efficiency are of major concern. Faults developing in induction motor necessitates significant consideration as they eradicate its operation and reduce the mean life. In this research, the most widely used MCSA that captures stator current signatures and acceleration-based vibration diagnosis techniques are practically investigated employing low-cost sensors. Moreover,the comparative analysis is performed to find an effective method for detection of faults, efficiently and persuade motor safety and reliable operation.


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Motor Current Signature Analysis (MSCA), Fast Fourier Transform (FFT), Condition Monitoring (CM).