Model-based stator interturn short-circuit fault detection and diagnosis in induction motors

Duvvuri, S S S R S and Detroja, Ketan P (2015) Model-based stator interturn short-circuit fault detection and diagnosis in induction motors. In: 7th International Conference on Information Technology and Electrical Engineering (ICITEE), 29-30, Oct. 2015, Chiang Mai.

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Abstract

In this paper, a novel model-based method for induction motor with stator inter-turn short-circuit fault detection is presented. The proposed technique is based on the whiteness of innovation sequence developed by the standard extended Kalman filter. Nonlinear Generalized Likelihood Ratio method is applied to identify the faulty phase along with its severity. This technique just requires current sensors which are available in most induction motor drive systems to provide good controllability, and induction motor design details are not necessary. Computer simulations are carried out for a 4-hp squirrel cage induction motor using MATLAB environment. The results show the superiority of the proposed method as it provides better estimates for stator interturn fault detection.

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IITH Creators:

IITH Creators	ORCiD
Detroja, Ketan P	UNSPECIFIED

Item Type:

Conference or Workshop Item (Paper)

Uncontrolled Keywords:

MATLAB environment,extended Kalman filter,fault diagnosis, induction motor drive systems, model based stator interturn short-circuit fault detection, nonlinear generalized likelihood ratio method, squirrel cage induction motor.

Subjects:

Others > Electricity
Others > Engineering technology

Divisions:

Department of Electrical Engineering

Depositing User:

Library Staff

Date Deposited:

10 Jun 2016 09:44

Last Modified:

05 Sep 2017 06:50

URI:

http://raiithold.iith.ac.in/id/eprint/2450