Paper Title:
Fault Diagnosis Model Based on Support Vector Machine and Genetic Algorithm
  Abstract

Recently, the dominating difficulty that fault intelligent diagnosis system faces is terrible lack of typical fault samples, which badly prohibits the development of machinery fault intelligent diagnosis. Mainly according to the key problems of support vector machine need to resolve in fault intelligent diagnosis system, this paper makes more systemic and thorough researches in building fault classifiers, parameters optimization of kernel function. A decision directed acyclic graph fault diagnosis classification model based on parameters selected by genetic algorithm is proposed, abbreviated as GDDAG. Finally, GDDAG model is applied to rotor fault system, the testing results demonstrate that this model has very good classification precision and realizes the multi-faults diagnosis.

  Info
Periodical
Edited by
Han Zhao
Pages
2535-2539
DOI
10.4028/www.scientific.net/AMM.130-134.2535
Citation
W. Niu, G. Q. Wang, Z. J. Zhai, J. Cheng, "Fault Diagnosis Model Based on Support Vector Machine and Genetic Algorithm", Applied Mechanics and Materials, Vols. 130-134, pp. 2535-2539, 2012
Online since
October 2011
Export
Price
$32.00
Share

In order to see related information, you need to Login.

In order to see related information, you need to Login.

Authors: Hui Qin Sun, Zhi Hong Xue, Ke Jun Sun, Su Zhi Wang, Yun Du
Chapter 2: Manufacturing Technology
Abstract:BP neural network is currently the most widely used of neural network models in practical application in transformer fault diagnosis. BP...
789
Authors: Na Rui Bu, Run Shan Bai, Zhang Zhen Li, De Zhong Lin
Chapter 6: Vibration, Noise Analysis and Control
Abstract:Analysis of slope stability based on BP neural network, the analytical model of slope stability is built. Aiming at the defects that BP...
1263
Authors: Si Lian Xie, Tie Bin Wu, Shui Ping Wu, Yun Lian Liu
Chapter 18: Computer Applications in Industry and Engineering
Abstract:Evolutionary algorithms are amongst the best known methods of solving difficult constrained optimization problems, for which traditional...
2846
Authors: Rui Ni Li, Xiao Yi Wang, Zai Wen Liu, Ji Ping Xu, Ling Bin Wang
Chapter 4: Waste Disposal and Recycling
Abstract:Various unusual conditions are likely to occur during sewage treatment process, which would lead to some consequences such as the decrease of...
622
Authors: Jian Xue Chen, Shui Yu
Chapter 4: Mechatronics and Automation Manufacturing Systems, Control Technologies
Abstract:Combining ant colony optimization (ACO) algorithm with back-propagation (BP) algorithm, the ACO-BP algorithm is proposed to optimize shift...
553