Paper Title:
Research on Mechanical Fault Identification Based on Improved SVM
  Abstract

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, J. W. Xiang, Y. T. Zhong, "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
$32.00
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