Paper Title:
Diagnosis for Vibration Fault of Steam Turbine Based on Modified Particle Swarm Optimization Support Vector Machine
  Abstract

Due to the influence of artificial factor and slow convergence of particle swarm algorithm (PSO) during parameters selection of support vector machine (SVM), this paper proposes a modified particle swarm optimization support vector machine (MPSO-SVM). A Steam turbine vibration fault diagnosis model was established and the failure data was used in fault diagnosis. The results of application show the model can get automatic optimization about the related parameters of support vector machine and achieve the ideal optimal solution globally. MPSO-SVM strategy is feasible and effective compared with traditional particle swarm optimization support vector machine (PSO-SVM) and genetic algorithm support vector machine (GA-SVM).

  Info
Periodical
Chapter
Chapter 1: Mechanic Manufacturing System and Automation
Edited by
Zhixiang Hou
Pages
113-116
DOI
10.4028/www.scientific.net/AMM.128-129.113
Citation
Z. B. Shi, Q. G. Song, M. Z. Ma, "Diagnosis for Vibration Fault of Steam Turbine Based on Modified Particle Swarm Optimization Support Vector Machine", Applied Mechanics and Materials, Vols. 128-129, pp. 113-116, 2012
Online since
October 2011
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$32.00
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