Neural Network Based Fault Diagnosis of Three Phase Inverter Fed Vector Control Induction Motor

  • Bilal Djamal Eddine Cherif Diagnosis Group, Laboratory LDEE, Electrical Engineering Faculty, University of Sciences and Technology of Oran, Bir El Djir, P. O. B. 1505, El-Mnaouer, Oran 31000, Algeria http://orcid.org/0000-0001-7703-2295
  • Azeddine Bendiabdellah Diagnosis Group, Laboratory LDEE, Electrical Engineering Faculty, University of Sciences and Technology of Oran, Bir El Djir, P. O. B. 1505, El-Mnaouer, Oran 31000, Algeria
  • Mokhtar Bendjebbar Diagnosis Group, Laboratory LDEE, Electrical Engineering Faculty, University of Sciences and Technology of Oran, Bir El Djir, P. O. B. 1505, El-Mnaouer, Oran 31000, Algeria
  • Amina Tamer Diagnosis Group, Laboratory LDEE, Electrical Engineering Faculty, University of Sciences and Technology of Oran, Bir El Djir, P. O. B. 1505, El-Mnaouer, Oran 31000, Algeria

Abstract

The paper investigates the detection and location of IGBT open-circuit faults in two-level inverter fed induction motor controlled by indirect vector control strategy. The investigation proposes two new approaches entirely based on the Artificial Neural Network (ANN) for the extraction of the exact fault angle corresponding to the IGBT switch open-circuit fault. The first approach (Approach1) based on the Clark currents transform calculates the average value of the Clark currents to find the exact fault angle θ. The second approach (Approach2) based directly on the three-phase stator currents (without any transformation) calculates the average value of the three-phase currents to determine the exact fault angle between the phases (θab, θbc, θca). The paper conducts also a comparative study between the two approaches to assess the merits of each one of them. Experimental work is conducted to illustrate the effectiveness of the techniques and validate the results obtained.

Keywords: vector control, open-circuit fault, detection, location, ANN
Published online
2019-10-31
How to Cite
Cherif, B. D. E., Bendiabdellah, A., Bendjebbar, M. and Tamer, A. “Neural Network Based Fault Diagnosis of Three Phase Inverter Fed Vector Control Induction Motor”, Periodica Polytechnica Electrical Engineering and Computer Science. doi: https://doi.org/10.3311/PPee.14315.
Section
Articles