Study of Engine Fault Diagnosis Based on Wavelet Packet Decomposition and Neural Network

Fei Fei Yu; Can Yi Du; Xiang Kun Zeng

doi:10.4028/www.scientific.net/AMR.945-949.1077

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 945-949Study of Engine Fault Diagnosis Based on Wavelet...

Study of Engine Fault Diagnosis Based on Wavelet Packet Decomposition and Neural Network

Abstract:

Engine mechanical fault usually causes abnormal change of the body surface vibration signal. Cylinder surface vibration signals under normal condition, piston knocking fault condition and main bearing wear fault condition are analyzed with wavelet packet decomposition method, relative energy value of each frequency band can be calculated and then be regarded as the input vector to form the training sample, BP neural network model is used to identify the fault state, test data shows that this method can effectively recognize the fault types.

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Periodical:

Advanced Materials Research (Volumes 945-949)

Pages:

1077-1081

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.945-949.1077

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Cite this paper

Online since:

June 2014

Authors:

Fei Fei Yu, Can Yi Du*, Xiang Kun Zeng

Keywords:

Fault Diagnosis, Main Bearing Wear, Neural Network (NN), Piston Knocking, Wavelet Packet Decomposition

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* - Corresponding Author

References

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