Shukri , Mohamad and Khalid, Marzuki and Yusuf, Rubiyah and Shafawi, Mohd (2004) Induction machine diagnostic using adaptive neuro fuzzy inferencing system. In: Knowledge-Based Intelligent Information and Engineering Systems. Lecture Notes in Computer Science , 3215/2004 . Springer Berlin / Heidelberg, Germany, pp. 380-387. ISBN 978-3-540-23205-6
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Official URL: http://www.springerlink.com/content/3gajgyqtma6dvf...
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.
|Item Type:||Book Section|
|Additional Information:||ISBN: 3-540-23205-2 8th International Conference on Knowledge-Based Intelligent Information and Engineering Systems Wellington Inst Technol, Wellington, Sep. 2004, NEW ZEALAND|
|Uncontrolled Keywords:||adaptive neuro fuzzy inferencing system (ANFIS), induction motor, faulty conditions|
|Subjects:||Q Science > QA Mathematics > QA75 Electronic computers. Computer science|
|Divisions:||Computer Science and Information System (Formerly known)|
|Deposited By:||Surayahani Abu Bakar|
|Deposited On:||20 Jan 2009 07:40|
|Last Modified:||09 Mar 2011 06:32|
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