Induction machine diagnostic using adaptive neuro fuzzy inferencing system

8Citations
Citations of this article
3Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Electrical machines are subjected to wear and tear after being used for sometime and proper maintenance is required to prevent breakdown. One of the main maintenance efforts is to detect fault occurring in the electrical machines. Some of these faults are slowly developing faults and early detection of these faults is crucial to prevent machine breakdown. In this paper, we investigate the effectiveness of a fault detection and diagnosis system using adaptive neuro fuzzy inferencing system (ANFIS) on a simulated three-phase induction motor. Several parameters of the induction motor are adjusted to represent faulty conditions. The experimental results obtained show that the algorithm has good fault detection and diagnosis ability.

Cite

CITATION STYLE

APA

Shukri, M., Khalid, M., Yusuf, R., & Shafawi, M. (2004). Induction machine diagnostic using adaptive neuro fuzzy inferencing system. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3215, pp. 380–387). Springer Verlag. https://doi.org/10.1007/978-3-540-30134-9_51

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free