Title :
Wavelet packets analysis of rolling bearing vibration signal and fault testing
Author_Institution :
Inf. Eng. Coll., Central South Univ., Changsha, China
Abstract :
Proposes a method for fault testing on a rolling bearing based on wavelet transformation and pattern recognition. Wavelet packets decomposition is used to extract features of dynamic vibration information; K-NN is introduced to test the fault on a rolling bearing. Experiments show that the proposed method attains a satisfactory effect.
Keywords :
condition monitoring; fault diagnosis; feature extraction; signal processing; testing; wavelet transforms; K-NN method; K-nearest neighbour method; dynamic vibration information; fault testing; features extraction; pattern recognition; rolling bearing vibration signal; wavelet packets analysis; wavelet packets decomposition; wavelet transformation; Automatic testing; Automation; Data mining; Educational institutions; Feature extraction; Intelligent control; Rolling bearings; Signal analysis; Wavelet packets;
Conference_Titel :
Intelligent Control and Automation, 2002. Proceedings of the 4th World Congress on
Print_ISBN :
0-7803-7268-9
DOI :
10.1109/WCICA.2002.1020079
