Title :
Fault Diagnosis for Induction Motors Using the Wavelet Ridge
Author :
Yang, Cunxiang ; Cui, Guangzhao ; Wei, Yunbing ; Wang, Yongji
Abstract :
Early detection and diagnosis of incipient faults is desirable for online condition assessment, product quality assurance, and improved operational efficiency of induction motors. The characteristic frequency component(CFC) of broken rotor bars is very close to the power frequency component in frequency domain but far less in amplitude, which brings about great difficulty in detecting the broken bars in induction motors. A new method based on wavelet ridge is presented in this paper. As a motor accelerates progressively and the CFC of its broken rotor bars approaches the power frequency component gradually during the motor´s starting period, the wavelet ridge-based method is adopted to analyze this transient procedure and the CFC is extracted effectively. The influence of power frequency can be eliminated, and the detection accuracy can be greatly improved. Furthermore, experimental results show this is truly a novel but excellent approach for the detection of the broken rotor bars in squirrel-cage induction motors.
Keywords :
fault diagnosis; rotors; squirrel cage motors; broken rotor bars; characteristic frequency component; fault diagnosis; power frequency component; squirrel-cage induction motors; wavelet ridge; Acceleration; Bars; Fault detection; Fault diagnosis; Frequency domain analysis; Induction motors; Quality assurance; Rotors; Transient analysis; Wavelet analysis;
Conference_Titel :
Bio-Inspired Computing: Theories and Applications, 2007. BIC-TA 2007. Second International Conference on
Conference_Location :
Zhengzhou
Print_ISBN :
978-1-4244-4105-1
Electronic_ISBN :
978-1-4244-4106-8
DOI :
10.1109/BICTA.2007.4806457