The Fault Diagnosis Method of Diesel Based on Wavelet Pocket and BP Neural Network

Because of the well time-frequency spectrum disposal capability of wavelet packet, the wavelet packet algorithm is used to analyze the time - frequency characteristics of diesel vibration signals. The signal energy distributing characteristics based on wavelet packet transform. are extracted and tak...

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Bibliographic Details
Published inApplied Mechanics and Materials Vol. 635-637; pp. 910 - 913
Main Authors Wang, Hong Xia, Xu, Jun, Zhang, Qing Hua, Sun, Hong Hui
Format Journal Article
LanguageEnglish
Published Zurich Trans Tech Publications Ltd 01.09.2014
Subjects
Vibration Signal
BP Neural Network (BPNN)
Fault Diagnosis
Wavelet Packe
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Summary:Because of the well time-frequency spectrum disposal capability of wavelet packet, the wavelet packet algorithm is used to analyze the time - frequency characteristics of diesel vibration signals. The signal energy distributing characteristics based on wavelet packet transform. are extracted and taken as diagnostic characteristic vector, then improved BP neural network algorithm that connects additional momentum with self-adaptive learning rate was used to classify and recognize faults of diesel valves. The experimental results show the fault diagnosis method of diesel based on wavelet pocket and BP neural network is effective and feasible.
Bibliography:Selected, peer reviewed papers from the 4th International Conference on Advanced Design and Manufacturing Engineering (ADME 2014), July 26-27, 2014, Hangzhou, China
ISBN:3038352578
9783038352570
ISSN:1660-9336
1662-7482
1662-7482
DOI:10.4028/www.scientific.net/AMM.635-637.910