Title :
Induction Motor Bearing Fault Detection Using Wavelet-Based Envelope Analysis
Author_Institution :
Dept. of Mech. & Autom. Eng., Kao-Yuan Univ., Kaohsiung, Taiwan
Abstract :
This paper proposes a new signal processing approach based on the fusion of the wavelet transform and envelope spectrum to extract features of defects in a number of induction motor bearing conditions. The bearing conditions considered are a normal bearing and bearings with outer and inner race faults. This approach provides one solution to overcome the shortcomings of the traditional envelope analysis in finding the most suitable resonant frequency band for demodulation. Experiment results show that the proposed approach is capable of completely extracting the characteristic frequencies related to the defects in rolling element bearings.
Keywords :
fault diagnosis; induction motors; machine bearings; wavelet transforms; envelope spectrum; induction motor bearing fault detection; resonant frequency band; signal processing; wavelet based envelope analysis; wavelet transform; Discrete wavelet transforms; Resonant frequency; Rolling bearings; Vibrations; Wavelet analysis; Fault detection; envelope spectrum; motor bearing; wavelet transform;
Conference_Titel :
Computer, Consumer and Control (IS3C), 2014 International Symposium on
Conference_Location :
Taichung
DOI :
10.1109/IS3C.2014.321