Analog circuit fault diagnosis approach using optimized SVMs based on MST algorithm

摘要：

The classification accuracy and efficiency of multiclass SVMs are largely dependent on the SVM combination strategy in analog circuits fault diagnosis. An optimized SVM extension strategy is presented in this paper, which uses minimum spanning tree (MST) algorithm to simplify the SVM structure and decrease the classification errors. By taking the separability measure of fault classes as edge weight of undirected graph extracted from feature space, the tree nodes are generated by bottom-top method, which represents sub-class partition with clustering characteristic. Finally, hierarchical multiclass SVMs are constructed according to the structure of MST obtained. The MST-SVM classifier is expected to improve the diagnosis accuracy because the fault classes with larger margin are preferentially separated. The experimental results on a high-pass filter circuit prove that the MST-SVM method outperforms other conventional SVM approaches in veracity and efficiency of fault diagnosis.

关键词： fault diagnosis analog circuits SVM classifier MST algorithm separability measure.

作者: Song Guoming Jiang Shuyan Wang Houjun Liu Hong

作者单位: Department of Computer Engineering,Chengdu Electromechanical College,Chengdu 610031,China;School of School of Automation Engineering,University of Electronic Science and Technology of China,Chengdu 61 School of Opto-electronic Engineering,Changchun University of Science and Technology,Changchun 13002

会议类型: 国际会议

会议名称: 2011 10th International Conference on Electronic Measurement & Instruments(第十届电子测量与仪器国际会议 ICEMI2011)

会议地点: 成都

会议语种:英文

页码: 1336-1340

在线出版日期: 2011-08-16（万方平台首次上网日期，不代表论文的发表时间）