Title :
Analog Circuit Fault Diagnosis Using Multi-wavelet Transform and SVM
Author :
Yunyan, Hu ; Minfang, Peng ; Chenglai, Tian ; Hu, Tan
Author_Institution :
Coll. of Electr. & Inf. Eng., Hunan Univ., Changsha, China
fDate :
July 31 2012-Aug. 2 2012
Abstract :
A new method for diagnosing analog circuit faults using multi-wavelet transform and support vector machine (SVM) is presented. The response signals of the analog circuit are preprocessed using multi-wavelet transform and the optimal fault feature with better classification capacity are obtained using energy normalization. Then, the features are inputted into the ensemble SVM to identify different fault cases. Simulation results indicate that this method can effectively enhance the analog fault diagnostic accuracy.
Keywords :
analogue circuits; circuit reliability; electronic engineering computing; fault diagnosis; support vector machines; wavelet transforms; SVM; analog circuit fault diagnosis; classification capacity; energy normalization; multiwavelet transform; response signals; support vector machine; Analog circuits; Circuit faults; Fault diagnosis; Support vector machine classification; Wavelet transforms; SVM; analog circuit; fault diagnosis; multi-wavelet transform;
Conference_Titel :
Digital Manufacturing and Automation (ICDMA), 2012 Third International Conference on
Conference_Location :
GuiLin
Print_ISBN :
978-1-4673-2217-1
DOI :
10.1109/ICDMA.2012.52
