Fault diagnosis of electrical faults of three-phasei nduction motors using acoustic analysis
Year: 2023
Type: article
Abstract: Fault diagnosis techniques of electrical motors can prevent unplanned downtime and loss of money, production, and health. Various parts of the induction motor can be diagnosed: rotor, stator, rolling bearings, fan, insulation damage, and shaft. Acoustic analysis is non-invasive. Acoustic sensors are low-cost. Changes in the acoustic signal are often observed for faults in induction motors. In this paper, the authors present a fault diagnosis technique for three-phase induction motors (TPIM) using acoustic analysis. The authors analyzed acoustic signals for three conditions of the TPIM: healthy TPIM, TPIM with two broken bars, and TPIM with a faulty ring of the squirrel cage. Acoustic analysis was performed using fast Fourier transform (FFT), a new feature extraction method called MoD-7 (maxima of differences between the conditions), and deep neural networks: GoogLeNet, and ResNet-50. The results of the analysis of acoustic signals were equal to 100% for the three analyzed conditions. The proposed technique is excellent for acoustic signals. The described technique can be used for electric motor fault diagnosis applications.
Authors: Witold Glowacz, Daniel Korenciak, Muhammad Irfan, Adam Glowacz, Maciej Sulowicz, Jarosław Kozik, Krzysztof Piech, Miroslav Gutten, Frantisek Brumercik, Wahyu Caesarendra, Guilherme Beraldi Lucas, Hui Lui, Zhixiong Li, Anil Kumar
Institutions: AGH University of Krakow, University of Žilina, Najran University, Cracow University of Technology, Opole University of Technology, Universiti Brunei Darussalam, Universidade Estadual Paulista (Unesp), China Jiliang University, University of Religions and Denominations, Wenzhou University
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $283
OpenAlex ID: W4388691983