Research on Mechanical Fault Identification Based on Improved SVM

Abstract:

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Fault diagnosis of machinery is in essence a kind of classification problem. Utilizing the desirable classification ability of support vector machine (SVM) for fewer samples, a novel fault diagnosis method based on improved SVM was proposed. Some statistical features were extracted to reflect the equipment operational conditions and were input into fault classifier to attain the final diagnostic result. Experimental signals of gearbox were analyzed using the present method. The results of improved SVM were compared with those of artificial neural network (ANN). It indicates that the proposed method have better classification ability than that of ANN.

Info:

Periodical:

Advanced Materials Research (Volumes 97-101)

Edited by:

Zhengyi Jiang and Chunliang Zhang

Pages:

4257-4260

DOI:

10.4028/www.scientific.net/AMR.97-101.4257

Citation:

D. D. Chen et al., "Research on Mechanical Fault Identification Based on Improved SVM", Advanced Materials Research, Vols. 97-101, pp. 4257-4260, 2010

Online since:

March 2010

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Price:

$35.00

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