Title :
Application of signal processing technology based on symbolic time series analysis to rotor broken fault detection
Author :
Hu, Wei ; Wen, Liang ; Gao, Lei ; Ye, Jinhiao
Author_Institution :
Dept. of Autom., Shenyang Aerosp. Univ., Shenyang, China
Abstract :
An improved method of motor fault detection based on symbolic time series analysis is proposed, and the method adaptively partition off the region which has the most symbols in the symbolic series into two new regions. The method makes that the regions with more information are assigned more symbols relatively but those with sparse information are assigned fewer symbols, which enhances the sensitive degree of symbols to the signal. Laboratory experiments of fault diagnosis of broken rotor for inductive motor show that comparing with the uniform partition, the new method is more sensitive to the system and also owns a stronger robustness and a better reliability.
Keywords :
fault diagnosis; reliability; rotors; signal processing; time series; fault diagnosis; motor fault detection; reliability; rotor broken fault detection; signal processing technology; symbolic time series analysis; Reliability;
Conference_Titel :
Intelligent Signal Processing and Communication Systems (ISPACS), 2010 International Symposium on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4244-7369-4
DOI :
10.1109/ISPACS.2010.5704732