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Fault Detection and Diagnosis Technology Based on SVM and Immune Algorithm

Author: LiuLiJun
Tutor: GuXingSheng
School: East China University of Science and Technology
Course: Control Science and Engineering
Keywords: Support Vector Machine Troubleshooting Immune Genetic Algorithm Clonal selection algorithm TE process
CLC: TP18
Type: Master's thesis
Year: 2011
Downloads: 148
Quote: 0
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Abstract


With modern technology continues to evolve , expanding industrial scale , production equipment have become increasingly complex , industrial safety of the production process more and more people 's attention , so the process monitoring and fault diagnosis in recent years become a research hotspot . In recent years , support vector machine as a novel machine learning method has been widely used , and in the case of small sample showed its advantages. This paper considers the characteristics of complex industrial process systems , support vector machines and immune algorithm in industrial process fault diagnosis conducted in-depth research . In this paper, industrial process fault detection and diagnosis methods are reviewed in detail and compared various detection and diagnostic performance of the method introduced statistical learning theory and support vector machines for classification of the basic principles, research support vector machines kernel function parameters on the fault detection and diagnosis effect . In order to improve support vector machine fault diagnosis performance presented to immune algorithm and support vector machine combines fault detection and diagnosis algorithm , respectively, of immune genetic algorithm and clonal selection algorithm is proposed to improve the immune genetic algorithm based on improved support vector machines and clonal selection algorithm based on improved support vector machine and applied fault detection and diagnosis. In order to verify the effectiveness of the proposed method to the standard TE model simulation model as a platform to which the TE troubleshooting process . Simulation results show that the proposed immune genetic algorithm based on improved support vector machine and clone selection algorithm based on improved support vector machine with high efficiency of fault diagnosis .

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CLC: > Industrial Technology > Automation technology,computer technology > Automated basic theory > Artificial intelligence theory
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