ANN based real time incipient fault detection and protection system for induction motor
by Makarand S. Ballal, Hiralal M. Suryawanshi, Mahesh K. Mishra
International Journal of Power and Energy Conversion (IJPEC), Vol. 1, No. 2/3, 2009

Abstract: Artificial neural network (ANN) has its unique advantage in the area of incipient faults detection. This article presents an ANN based real time fault detection and protection system for two types of incipient faults viz. inter-turn insulation failure and bearing wear in single-phase induction motor. The ANN fault detection (ANNFD) program is developed in C++ and implemented using a PC based DSP controller board. The ANN is trained and tested by collecting the online experimental data for five input parameters viz. motor intake current, rotor speed, winding temperature, bearing temperature and noise. The results are compared with the signature of measurable parameters. The results of evaluation indicate that the system produces satisfactory performance for the fault detection as well as for the protection of motor.

Online publication date: Thu, 20-Aug-2009

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Power and Energy Conversion (IJPEC):
Login with your Inderscience username and password:

    Username:        Password:         

Forgotten your password?


Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com