Research on Fault Prediction Technology of Complicated Equipment

Sai Sai Jin; Kao Li  Huang; Guang Yao Lian; Bao Chen Li

doi:10.4028/www.scientific.net/AMM.347-350.448

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HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 347-350Research on Fault Prediction Technology of...

Research on Fault Prediction Technology of Complicated Equipment

Abstract:

For the problems of not enough fault information for the complicated equipment and difficult to predict the fault, we apply Support Vector Machine (SVM) to build the fault prediction model. On the basis of analyzing regression algorithm of SVM, we use Least Square Support Vector Machine (LS-SVM) to build the fault prediction model.LS-SVM can effectively debase the complication of the model. Finally, we take the fault data of a hydraulic pump to validate this model. By selecting appropriate parameters, this model can make better prediction for the fault data, and it has higher prediction precision. It is proved that the fault prediction model which based on LS-SVM can make better prediction for fault trend of complicated equipment.

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Periodical:

Applied Mechanics and Materials (Volumes 347-350)

Pages:

448-452

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.347-350.448

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Online since:

August 2013

Authors:

Sai Sai Jin, Kao Li Huang, Guang Yao Lian, Bao Chen Li

Keywords:

Fault Diagnosis, Fault Prediction Model, Hydraulic Pump, Least Squares Support Vector Machines (Ls-SVM), Regression Algorithm

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