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

Autor:	Mokhtar Bendjebbar, Amina Tamer, Azeddine Bendiabdellah, Bilal Djamal Eddine Cherif
Rok vydání:	2019
Předmět:	Vector control Artificial neural network Computer Networks and Communications Computer science Control theory Signal Processing Electrical and Electronic Engineering Fault (power engineering) Software Induction motor Computer Science Applications Information Systems Three phase inverter
Zdroj:	Periodica Polytechnica Electrical Engineering and Computer Science. 63:295-305
ISSN:	2064-5279 2064-5260
DOI:	10.3311/ppee.14315
Popis:	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.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::1eeef78fe7b2f0807af8bb2db1e22a07 https://doi.org/10.3311/ppee.14315 Zobrazit plný text záznamu