The Application of HIWO-SVM in Analog Circuit Fault Diagnosis

被引:7
|
作者
Hu, Hongzhi [1 ,2 ]
Tian, Shulin [1 ]
Guo, Qing [2 ]
Ouyang, Aijia [2 ]
机构
[1] Univ Elect Sci & Technol China, Sch Automat Engn, Chengdu 611731, Peoples R China
[2] Guilin Univ Elect Technol, Guangxi Key Lab Automat Detecting Technol & Instr, Guilin 541004, Peoples R China
基金
中国国家自然科学基金;
关键词
Differential evolution; invasive weed optimization; support vector machine; analog circuit; fault diagnosis; INVASIVE WEED OPTIMIZATION; SUPPORT VECTOR MACHINES; ALGORITHM; CLASSIFICATION; SELECTION;
D O I
10.1142/S0218001415500196
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The paper proposes a fault diagnosis model based on the HIWO-SVM algorithm given the fact that the basic support vector machines (SVM) cannot solve er effectively the problem of fault diagnosis in analog circuit. First of all, the wavelet package technique is adopted for extracting the information of the faults from the test points in the analog circuit. The differential evolution (DE) algorithm is then integrated with the purpose of improving the performance of the basic IWO algorithm, i.e. a hybrid IWO(HIWO) algorithm. The HIWO algorithm is further used to optimize the parameters of SVM in order to avoid the randomness of the parameter selection, thereby improving the diagnosis precision and robustness. The experimental results on a filter circuit show that the method is more effective and reliable than the other methods for fault diagnosis.
引用
收藏
页数:27
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