Fuzzy-Based Intelligent Algorithm for Diagnosis of Drive Faults in Induction Motor Drive System

• Published in: Arabian journal for science and engineering (2011) Vol. 45; no. 3; pp. 1385 - 1395
• Main Authors: Mayadevi, N., Mini, V. P., Hari Kumar, R., Prins, Shruti
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.03.2020; Springer Nature B.V
• Subjects: Algorithms; Computer simulation; Conversion; Engineering; Fault detection; Fault diagnosis; Fuzzy logic; Fuzzy systems; Harmonic distortion; Humanities and Social Sciences; Induction motors; multidisciplinary; Research Article - Electrical Engineering; Science; Fuzzy logic; Induction motor; Motor drives; Total harmonic distortion; Fault detection
• ISSN: 2193-567X; 1319-8025; 2191-4281
• DOI: 10.1007/s13369-019-03935-2

This paper presents the design and development of a novel, fuzzy-based algorithm for the detection and diagnosis of drive faults in an induction motor drive system (IMDS). A detailed investigation on the performance of IMDS under various faults and load conditions revealed that the combination of root-mean-square value and total harmonic distortion (THD) of the stator currents can accurately transpire various fault conditions. In this work, the efficacy of fuzzy logic is employed to characterize and diagnose the fault since it is difficult to find crisp boundaries for the correlation between the extracted parameters and fault conditions. The performance of the developed algorithm is tested and verified using simulation in MATLAB Simulink.