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Bearing Binary Classification Intelligent Diagnosis by Combined Improved EEMD with SVM
- Source :
- Applied Mechanics and Materials. :1066-1070
- Publication Year :
- 2013
- Publisher :
- Trans Tech Publications, Ltd., 2013.
-
Abstract
- In order to perform the bearing intelligent fault diagnosis,combined improved EEMD with SVM respectively applied to the binary classification identification of bearing normal and ball fault, normal and inner circle fault,normal and outer ring fault in this paper.Improve EEMD decomposed 9d normalized energy for characteristic vector,the SVM binary classification and recognition of bearings normal and ball fault, normal and inner circle fault, normal and outer ring fault is researched.Compared to the SVM classification accuracy using different kernel functions that is linear kernel function, polynomial kernel function, RBF kernel function and Sigmoid kernel function.In the same parameters,SVM classification accuracy based on linear kernel function and polynomial kernel function is a hundred percent.Bearing normal and ball fault,normal and inner circle fault,normal and outer ring fault is completely correct apart.And there are the classification errors based on RBF kernel function and Sigmoid kernel functions.
- Subjects :
- Bearing (mechanical)
business.industry
Pattern recognition
General Medicine
Sigmoid function
law.invention
Support vector machine
ComputingMethodologies_PATTERNRECOGNITION
Kernel method
Binary classification
Polynomial kernel
law
Kernel (statistics)
Radial basis function kernel
Artificial intelligence
business
Computer Science::Distributed, Parallel, and Cluster Computing
Mathematics
Subjects
Details
- ISSN :
- 16627482
- Database :
- OpenAIRE
- Journal :
- Applied Mechanics and Materials
- Accession number :
- edsair.doi...........3050010c604eaab5409e14b18f2bf142