DocumentCode
473587
Title
Application of EMD and SVD in fault identification
Author
Zhu, Zhihui ; Sun, Yunlian
Author_Institution
Sch. of Electr. Eng., Wuhan Univ., Wuhan
fYear
2007
fDate
3-6 Dec. 2007
Firstpage
1247
Lastpage
1250
Abstract
The method based on empirical mode decomposition (EMD) and singular value decomposition (SVD) for power fault identification is presented in this paper. First, fault signal was adaptively decomposed into a series of smooth intrinsic mode functions (IMFs) with different time scales via EMD; second, the matrix is formed by different level IMFs and SVD method decompose the matrix to obtain singular value as eigenvector; finally, support vector machines (SVMs) is used as classifier to identify the fault type. The simulation results show that EMD and SVD can well extract the fault feature and SVMs network can attain high accuracy of fault identification.
Keywords
fault location; power system faults; singular value decomposition; support vector machines; EMD; SVD; SVM; empirical mode decomposition; fault feature extraction; matrix decomposition; power fault identification; singular value decomposition; smooth intrinsic mode functions; support vector machines; Fault diagnosis; Power engineering; empirical mode decomposition; fault identification; singular value decomposition; support vector machines;
fLanguage
English
Publisher
ieee
Conference_Titel
Power Engineering Conference, 2007. IPEC 2007. International
Conference_Location
Singapore
Print_ISBN
978-981-05-9423-7
Type
conf
Filename
4510216
Link To Document