DocumentCode
554359
Title
Research on fault recognition method based on variable-risk SVM
Author
Fuzhou Feng ; Aiwei Si ; Chaosheng Zhang
Author_Institution
Dept. of Mech. Eng., Acad. of Armored Force Eng., Beijing, China
Volume
2
fYear
2011
fDate
12-14 Aug. 2011
Firstpage
539
Lastpage
543
Abstract
Because the tradition methods of fault pattern recognition can not distinguish the different loss by different misjudgments, the variable-risk support vector machines (SVM) is proposed in this paper. Then, the optimal classification face is redesigned and expert´s experience is integrated when using an actual data to recognize the fault, which makes the result more reliable. Finally, this method has already applied in the diesel engine fault diagnosis successfully.
Keywords
diesel engines; fault diagnosis; pattern recognition; support vector machines; diesel engine fault diagnosis; fault pattern recognition; fault recognition method; optimal classification face; variable-risk SVM; variable-risk support vector machines; Diesel engines; Equations; Face; Fault diagnosis; Mathematical model; Pattern recognition; Support vector machines; fault recognition; support vector machines; vario-risk;
fLanguage
English
Publisher
ieee
Conference_Titel
Electronic and Mechanical Engineering and Information Technology (EMEIT), 2011 International Conference on
Conference_Location
Harbin, Heilongjiang, China
Print_ISBN
978-1-61284-087-1
Type
conf
DOI
10.1109/EMEIT.2011.6023159
Filename
6023159
Link To Document