DocumentCode :
3462486
Title :
Early Fault Feature Extraction of Rotor Imbalance and Self-Healing Monitoring
Author :
Wang Zhongsheng ; Wang Xiang ; Luo Baopeng
Author_Institution :
Coll. of Aeronaut., Northwestern Polytech. Univ., Xi´an, China
fYear :
2009
fDate :
7-9 Dec. 2009
Firstpage :
492
Lastpage :
495
Abstract :
Based on the analysis of rotor imbalance mechanism, the presumption of extracting early fault features of rotor imbalance through the utilization of wavelet packet noise elimination and feature zoom as well as conducting self healing monitoring over the rotor imbalance through the utilization of electromagnetic induction principle is proposed. In addition, simulation experiment is applied to prove the feasibility of the proposed method. In this paper, analysis and research have been carried out with respect to the selection of optimum wavelet packet basis, wavelet packet noise elimination and feature zoom, structure of fault feature vector, principle of electromagnetic induction rotor balance, which provides a new thinking and method for self-equilibrating of rotor.
Keywords :
aerospace engines; electromagnetic induction; fault tolerant computing; feature extraction; interference suppression; mechanical engineering; rotors; wavelet transforms; early fault feature extraction; electromagnetic induction; rotor imbalance; self-healing monitoring; wavelet packet noise elimination; Aircraft propulsion; Electromagnetic analysis; Electromagnetic induction; Electromagnetic interference; Engines; Feature extraction; Magnetic levitation; Monitoring; Wavelet analysis; Wavelet packets;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Innovative Computing, Information and Control (ICICIC), 2009 Fourth International Conference on
Conference_Location :
Kaohsiung
Print_ISBN :
978-1-4244-5543-0
Type :
conf
DOI :
10.1109/ICICIC.2009.185
Filename :
5412678
Link To Document :
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