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Engineering Review : Međunarodni časopis namijenjen publiciranju originalnih istraživanja s aspekta analize konstrukcija, materijala i novih tehnologija u području strojarstva, brodogradnje, temeljnih tehničkih znanosti, elektrotehnike, računarstva i građevinarstva, Vol. 42 No. 3, 2022.

Izvorni znanstveni članak

https://doi.org/10.30765/er.1949

Pattern recognition and diagnosis of short and open circuit faults inverter in induction motor drive using neural networks

Younes Tamissa orcid id orcid.org/0000-0002-4657-4400 ; Laboratoire du Génie Electrique, LAGE, Department of Electronics and Telecommunications, University of Kasdi Merbah-Ouargla, Algeria
Fella Charif orcid id orcid.org/0000-0002-3601-6077 ; Laboratoire du Génie Electrique, LAGE, Department of Electronics and Telecommunications, University of Kasdi Merbah-Ouargla, Algeria
Farid Kadri orcid id orcid.org/0000-0002-5440-5965 ; Laboratoire du Génie Electrique, LAGE, Department of Electronics and Telecommunications, University of Kasdi Merbah-Ouargla, Algeria
Abderrazak Benchabane orcid id orcid.org/0000-0001-8436-5805 ; Laboratoire du Génie Electrique, LAGE, Department of Electronics and Telecommunications, University of Kasdi Merbah-Ouargla, Algeria

Puni tekst: engleski pdf 1.188 Kb

str. 138-148

preuzimanja: 326

citiraj

Sažetak

Nowadays, feeding induction motors with voltage source inverters under faulty conditions is a major challenge. For this reason, electrical systems must be well thought out to provide good diagnostics for these elements. Consequently, the early detection of faults is very important to establish strategies that allow us to control the operation and take preventive measures to avoid frequent failures. Our aim in this paper is to train multilayer neural networks using features extracted from currents and voltages measurements to detect and classify open and short-circuit switch faults in source voltage inverters. Simulation results show that instead of using several types of features extracted from measurements of several signal cycles as in previous works, a two-component feature obtained from one cycle is sufficient to obtain an excellent accuracy. The normalized mean Clark currents and the power spectrum using the fast Fourier transform have been used as features for open switches and short-circuit faults respectively.

Ključne riječi

direct torque control; induction motor; neural networks; open switches fault; short-circuit fault

Hrčak ID:

293352

URI

https://hrcak.srce.hr/293352

Datum izdavanja:

18.12.2022.

Posjeta: 1.043 *