Application of the B-Spline wavelet in railway catenary intelligent fault diagnosis

Author

Gao, Yan-ling ; Zhang, De-ying

Author_Institution

Beijing Inst. of Petro-Chem. Technol., Beijing

Volume

4

fYear

2007

fDate

2-4 Nov. 2007

Firstpage

1853

Lastpage

1856

Abstract

A new method based on cubic B-Spline dyadic mother wavelet of centro -symmetric about zero is presented, the principle of singularity detection by using wavelet transform modulus maximum is applied in railway catenary fault feature extraction by using the mother wavelet, at last, the project is concluded by using BP neural network to recognize pattern. The result shows that it can confirm position accurately and identify the fault types effectively.

Keywords

backpropagation; fault diagnosis; feature extraction; maintenance engineering; railway engineering; railway safety; signal classification; splines (mathematics); wavelet transforms; BP neural network; cubic B-spline dyadic mother wavelet; feature extraction; pattern recognition; railway catenary intelligent fault diagnosis; transient signals; wavelet transform modulus maximum; Fault diagnosis; Feature extraction; Frequency; Pattern recognition; Rail transportation; Spline; Time domain analysis; Wavelet analysis; Wavelet domain; Wavelet transforms; BP neural network; cubic B-Spline; feature extraction; modulus maximum; mother wavelet;

fLanguage

English

Publisher

ieee

Conference_Titel

Wavelet Analysis and Pattern Recognition, 2007. ICWAPR '07. International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4244-1065-1

Electronic_ISBN

978-1-4244-1066-8

Type

conf

DOI

10.1109/ICWAPR.2007.4421756

Filename

4421756