Induction machine diagnostic using adaptive neuro fuzzy inferencing system - Shukri, Mohamad; Khalid, Marzuki; Yusuf, Rubiyah; Shafawi, Mohd. (Springer Berlin / Heidelberg, 2004)
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.