Paper Title:
Research on Rotating Machinery Vibration Fault Based on Support Vector Machine
  Abstract

The research on support vector machine in fault diagnose has already obtained a lot of breakthroughs, such as the mode identify problems in small sample, nonlinearity, high dimension and so on. However, there are some limitations in the traditional support vector machine. In this paper, in allusion to the current rotating machinery fault diagnosis problem, the basic principles of support vector machine are studied. According to the complex characteristics of rotating machinery vibration fault, a fault extraction method is proposed based on the K-L transform. Multi-classification algorithm of support vector machine is improved, and the algorithm is used to analyze the rotating machinery vibration. By using its capabilities of model identification and system modeling, the initial symptom, occurrence, development of the typical faults are dynamically analyzed. These provide new ideas and methods for fault diagnosis of rotating machinery.

  Info
Periodical
Advanced Materials Research (Volumes 139-141)
Edited by
Liangchi Zhang, Chunliang Zhang and Tielin Shi
Pages
2603-2607
DOI
10.4028/www.scientific.net/AMR.139-141.2603
Citation
C. Zhang, D. Q. Liu, "Research on Rotating Machinery Vibration Fault Based on Support Vector Machine", Advanced Materials Research, Vols. 139-141, pp. 2603-2607, 2010
Online since
October 2010
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Price
$32.00
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