Research on Mechanical Mechanics with Fault Diagnosis Method for Gearbox Based on Relevance Vector Machine

Hu Cheng Zhao

doi:10.4028/www.scientific.net/AMR.703.208

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Research on Mechanical Mechanics with Fault Diagnosis Method for Gearbox Based on Relevance Vector Machine
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HomeAdvanced Materials ResearchAdvanced Materials Research Vol. 703Research on Mechanical Mechanics with Fault...

Research on Mechanical Mechanics with Fault Diagnosis Method for Gearbox Based on Relevance Vector Machine

Abstract:

In order to more effectively solve some difficult problems in gearbox failure diagnosis, a gearbox fault diagnosis method based on Relevance Vector Machine (RVM) is proposed. RVM is developed in Bayesian framework. It does not need to estimate the regularization parameter with less relevance vectors, and its kernel function does not need to satisfy Mercer condition. Simulation results show that: compared with the traditional BP neural network, RVM has the faster modeling speed, more accurate diagnosis, and is worthy of promotion and application in fault diagnosis of the gearbox.

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Periodical:

Advanced Materials Research (Volume 703)

Pages:

208-211

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.703.208

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Online since:

June 2013

Authors:

Hu Cheng Zhao

Keywords:

Bayesian Framework, Fault Diagnosis, Gearbox, Relevance Vector Machine

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