Detection of Deterioration of Three-phase Induction Motor using Vibration Signals

Measurement Science Review

Glowacz Adam¹  Glowacz Witold¹  Kozik Jarosław²  Piech Krzysztof²  Liu Hui³  Caesarendra Wahyu⁴  Irfan Muhammad⁵  Faizal Khan Z.⁶  Gutten Miroslav⁷  Brumercik Frantisek⁸ 

[1] AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, Department of Automatic Control and Robotics, Al. A. Mickiewicza 30, 30-059Kraków, Poland;AGH University of Science and Technology, Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering, Department of Power Electronics and Energy Control Systems, Al. A. Mickiewicza 30, 30-059Kraków, Poland;College of Quality and Safety Engineering, China Jiliang University, Hangzhou310018, China;Faculty of Integrated Technologies, Universiti Brunei Darussalam, Jalan Tungku Link, GadongBE1410, Brunei Darussalam;Najran University, Electrical Engineering Department, Kingdom of Saudi Arabia;Shaqra University, College of Computing and Information Technology, Department of Computer Science, Kingdom of Saudi Arabia;University of Zilina, Faculty of Electrical Engineering, 1, Univerzitna Str., 01026Zilina, Slovakia;University of Zilina, Mechanical Engineering Faculty, Department of Desing and Machine Elements, 1 Univerzitna Str., 01026Zilina, Slovakia;

关键词: signal processing;    vibration signal;    induction motor;    deterioration;    diagnosis;   

DOI  :  10.2478/msr-2019-0031

来源: DOAJ

【 摘 要 】

Nowadays detection of deterioration of electrical motors is an important topic of research. Vibration signals often carry diagnostic information of a motor. The authors proposed a setup for the analysis of vibration signals of three-phase induction motors. In this paper rotor fault diagnostic techniques of a three-phase induction motor (TPIM) were presented. The presented techniques used vibration signals and signal processing methods. The authors analyzed the recognition rate of vibration signal readings for 3 states of the TPIM: healthy TPIM, TPIM with 1 broken bar, and TPIM with 2 broken bars. In this paper the authors described a method of the feature extraction of vibration signals Method of Selection of Amplitudes of Frequencies – MSAF-12. Feature vectors were obtained using FFT, MSAF-12, and mean of vector sum. Three methods of classification were used: Nearest Neighbor (NN), Linear Discriminant Analysis (LDA), and Linear Support Vector Machine (LSVM). The obtained results of analyzed classifiers were in the range of 97.61 % – 100 %.

【 授权许可】

Unknown