Diagnostics Relevant Modeling of Squirrel-Cage Induction Motor: Electrical Faults

Sarathbabu Duvvuri, SSSR (2020) Diagnostics Relevant Modeling of Squirrel-Cage Induction Motor: Electrical Faults. In: International Conference on Numerical Optimization in Engineering and Sciences, NOIEAS 2019, 19 June 2019through 21 June 2019, Warangal.

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Abstract

In this paper, simplified SCIM models are formulated based on stationary, rotor, and synchronous reference frames. All these models are compared and analyzed in terms of their diagnostic relevance to major electrical faults (stator inter-turn short-circuit and broken rotor bars). Ability to develop distinct residual signatures is a key for any model-based fault diagnosis method. The performance of various models in terms of their ability to generate a distinct residual and best-suited model is recommended based on discriminatory ability index proposed in this manuscript. Extended Kalman filter is the most commonly used estimator for nonlinear systems. The SCIM, being a nonlinear system, extended Kalman filter is considered for state estimation. As an extension, parameter sensitivity analysis is carried out for the best-suited model. Efforts are made to convey which parameters have a significant effect in case there is plant-model mismatch. Analytical computations are carried out for a 3 kW SCIM motor using MATLAB software. The results show that the most effective squirrel-cage induction motor model for model-based fault diagnostics. © Springer Nature Singapore Pte Ltd. 2020.

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IITH Creators:
IITH CreatorsORCiD
Item Type: Conference or Workshop Item (Paper)
Uncontrolled Keywords: Extended Kalman filter (EKF); Reference frame theory; Squirrel-cage induction motor (SCIM)
Subjects: Electrical Engineering
Divisions: Department of Electrical Engineering
Depositing User: . LibTrainee 2021
Date Deposited: 31 Oct 2022 05:21
Last Modified: 31 Oct 2022 05:21
URI: http://raiith.iith.ac.in/id/eprint/11106
Publisher URL: http://doi.org/10.1007/978-981-15-3215-3_17
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