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Journal of Control Science and Engineering
Volume 2018, Article ID 1976836, 11 pages
Research Article

Detection of Two-Level Inverter Open-Circuit Fault Using a Combined DWT-NN Approach

Diagnostic Group, Laboratory LDEE, Electrical Engineering Faculty, University of Sciences and Technology of Oran, Bir El Djir, Algeria

Correspondence should be addressed to Bilal Djamal Eddine Cherif; moc.liamg@48cod.firehc

Received 18 November 2017; Revised 19 January 2018; Accepted 29 January 2018; Published 11 March 2018

Academic Editor: Qiang Liu

Copyright © 2018 Bilal Djamal Eddine Cherif and Azeddine Bendiabdellah. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Three-phase static converters with voltage structure are widely used in many industrial systems. In order to prevent the propagation of the fault to other components of the system and ensure continuity of service in the event of a failure of the converter, efficient and rapid methods of detection and localization must be implemented. This paper work addresses a diagnostic technique based on the discrete wavelet transform (DWT) algorithm and the approach of neural network (NN), for the detection of an inverter IGBT open-circuit switch fault. To illustrate the merits of the technique and validate the results, experimental tests are conducted using a built voltage inverter fed induction motor. The inverter is controlled by the SVM control strategy.