Title :
Fault Diagnosis of Hydraulic Pump Based on Rough Set and PCA Algorithm
Author :
Liu, Siyuan ; Jiang, Wanlu ; Niu, Huifeng
Author_Institution :
Coll. of Mech. Eng., Yanshan Univ., Qinhuangdao
Abstract :
In order to analyze the fuzzy and low signal-noise ratio on fault characteristics of hydraulic pump, a new rough set (RS) fault diagnosis algorithm based on principal component analysis (PCA) as guide is proposed. Firstly, the algorithm uses wavelet analysis to process noise abatement so as to extract the effective fault characteristic. Secondly, it utilizes PCA method to make dimension reduction and decoupling relativity between these characteristics. Thirdly, it establishes diagnosis rules knowledge base through the rough set theory. Lastly, the validity of this method is verified through the simulated experiment on doffing-shoe fault diagnosis of hydraulic pump.
Keywords :
fault diagnosis; fuzzy set theory; hydraulic systems; principal component analysis; pumps; rough set theory; doffing-shoe fault diagnosis; hydraulic pump; principal component analysis; rough set theory; wavelet analysis; Educational institutions; Fault diagnosis; Knowledge engineering; Noise reduction; Principal component analysis; Signal analysis; Signal detection; Signal processing; Vibrations; Wavelet analysis; fault diagnosis; hydraulic pump; principal component analysis (PCA); rough set(RS); wavelet analysis;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2008. FSKD '08. Fifth International Conference on
Conference_Location :
Jinan Shandong
Print_ISBN :
978-0-7695-3305-6
DOI :
10.1109/FSKD.2008.538
