Fault Diagnosis Method Based on Embedded Acquisition Equipment and SVM

Ming Hong She; Hong Bing Yang; Ming Ying She

doi:10.4028/www.scientific.net/AMR.468-471.1681

Paper Titles

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False Color Composite System of Multi-Spectral RS Images Based on IDL
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Finite Element Analysis for the Stiffness and the Buckling of Corrugated Tubes in Heat Exchanger
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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 468-471Fault Diagnosis Method Based on Embedded...

Fault Diagnosis Method Based on Embedded Acquisition Equipment and SVM

Abstract:

Fault diagnosis method based on embedded acquisition equipment and SVM is proposed in the paper.The function of the module mainly includes data acquisition, data processing and data storage.SVM is trained by the features and the five states of rolling bearing. The structure of diagnostic model by SVM is defined as 5 input nodes and 5 output nodes,among which 5 input nodes are the features including peak factor,waveform factor,impulse factor,margin factor and kurtosis factor and 5 output nodes are the five states of rolling bearing include normal state, housing washer failure, retainer failure, rolling element failure and inner ring failure.The experimental results show that the diagnostic performance of SVM is effective.

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Periodical:

Advanced Materials Research (Volumes 468-471)

Pages:

1681-1684

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.468-471.1681

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Online since:

February 2012

Authors:

Ming Hong She, Hong Bing Yang, Ming Ying She

Keywords:

Data Acquisition Module, Embedded Acquisition, Fault Diagnosis, Support Vector Machine (SVM)

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References

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