Full-Text Search:
Home|About CNKI|User Service|中文
Add to Favorite Get Latest Update

Intelligent Fault Diagnosis for Air-condition System Based on Support Vector Machine

LIU Shun-bo,DUAN Qi-chang,ZHOU Guang-wei(The Second Artillery Engineering University,Xi'an 710025,China)  
As a part of weapon material management system,air-condition system is becoming more and more important to national defense engineering,resulting in the increasingly complex structure and function and putting forward higher requirements for automatic detection.For the purpose of effectively improving the efficiency and accuracy of fault diagnosis for air-condition system,this paper proposes a fault diagnosis model based on the support vector machine(SVM) of principal component analysis(PCA).Firstly,the model normalizes data to eliminate abnormal data and applies principal component analysis to simple data attributes;then it eliminates redundant information for feature extraction and makes fault diagnosis by support vector machine;and at the end,it uses grid-search method and cross validation method to optimize the parameters of the penalty function and kernel function of SVM.The results show that the diagnosis accuracy is greatly improved from 58.0181% to 99.9536%,and the faults can be effectively located and distinguished.
Download(CAJ format) Download(PDF format)
CAJViewer7.0 supports all the CNKI file formats; AdobeReader only supports the PDF format.
©CNKI All Rights Reserved