计算机测量与控制
計算機測量與控製
계산궤측량여공제
COMPUTER MEASUREMENT & CONTROL
2009年
7期
1250-1252
,共3页
主元分析法%支持向量机%故障诊断%模拟电路
主元分析法%支持嚮量機%故障診斷%模擬電路
주원분석법%지지향량궤%고장진단%모의전로
Principal Components Analysis (PCA)～ Support Vector Machine (SVM)%fault diagnosis%three-phase bridge rectifier
主元分析法(PCA)通过提取故障样本集的主元得到降维的特征空间,利于故障特征提取;支持向量机(SVM)应用于故障诊断时具有良好分类性能;结合两者优点.提出了基于PCA特征提取和SVM相结合的模拟电路故障诊断识别新方法:对电路输出响应信号进行PCA处理,提取故障特征的主成分,然后利用多类SVM对故障模式进行分类决策,实现故障诊断;仿真实验结果表明,该方法能够实现模拟电路故障的快速检测与故障定位,具有速度快、精度高、鲁棒性好的特点.
主元分析法(PCA)通過提取故障樣本集的主元得到降維的特徵空間,利于故障特徵提取;支持嚮量機(SVM)應用于故障診斷時具有良好分類性能;結閤兩者優點.提齣瞭基于PCA特徵提取和SVM相結閤的模擬電路故障診斷識彆新方法:對電路輸齣響應信號進行PCA處理,提取故障特徵的主成分,然後利用多類SVM對故障模式進行分類決策,實現故障診斷;倣真實驗結果錶明,該方法能夠實現模擬電路故障的快速檢測與故障定位,具有速度快、精度高、魯棒性好的特點.
주원분석법(PCA)통과제취고장양본집적주원득도강유적특정공간,리우고장특정제취;지지향량궤(SVM)응용우고장진단시구유량호분류성능;결합량자우점.제출료기우PCA특정제취화SVM상결합적모의전로고장진단식별신방법:대전로수출향응신호진행PCA처리,제취고장특정적주성분,연후이용다류SVM대고장모식진행분류결책,실현고장진단;방진실험결과표명,해방법능구실현모의전로고장적쾌속검측여고장정위,구유속도쾌、정도고、로봉성호적특점.
Principal Components Analysis (PCA) extract the main element from the fault sample set to obtain compacted feature space so it is propitious for fault diagnosis. Support Vector Machine (SVM) has shown its good classification performance in fault diagnosis. A new method of fault diagnosis for analog circuit based on PCA-SVM is raised and it includes both advantages. The circuit output is sampled in frequency domain and it is preprocessed by PCA to extract main components of the fault features. Fault patterns under various states are classified using multi-class SVM, and fault diagnosis is realized. The simulation results show that PCA-SVM is feasible to detect and locate faults quickly and exactly and has high robustness.
