Research on SVM classification performance in rolling bearing diagnosis

2010 International Conference on Intelligent Computation Technology and Automation, ICICTA 2010

Volumn 3, Issue , 2010, Pages 132-135

  Li, Meng ^a   Wang, Miao ^b   Wang, Chunguang ^b  

^a CHANGCHUN UNIVERSITY   (China)

^b AVIATION UNIVERSITY OF AIR FORCE   (China)

Author keywords

Classification performance; Fault diagnosis; Rolling bearing; SVM

Indexed keywords

CALCULATING COMPLEXITY; CLASSIFICATION PERFORMANCE; DE-NOISING; ENGINEERING APPLICATIONS; EXPERIMENT AND ANALYSIS; FAULT CLASSIFIER; FAULT DIAGNOSIS; FAULT DIAGNOSIS METHOD; FAULT PATTERNS; FAULT SAMPLE; FEATURE EXTRACTING; INTELLIGENT FAULT DIAGNOSIS; KERNEL FUNCTION; MULTI-CLASS CLASSIFICATION; NOVEL METHODS; PCA METHOD; PERFORMANCE COMPARISON; RBF NETWORK; RBF NEURAL NETWORK; RECOGNITION RATES; ROLLING BEARING; ROLLING BEARING DIAGNOSIS; ROLLING BEARINGS; SVM; SVM CLASSIFICATION; TRAINING SAMPLE; TRAINING SPEED; TWO-CLASS CLASSIFIER; WAVELET PACKET;

BEARINGS (MACHINE PARTS); CLASSIFIERS; FEATURE EXTRACTION; NEURAL NETWORKS; PRECISION ENGINEERING; RADIAL BASIS FUNCTION NETWORKS; WAVELET DECOMPOSITION;

BEARINGS (STRUCTURAL);

EID: 77955733345     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICICTA.2010.747     Document Type: Conference Paper

References (7)

1. Rubini R, Meneghetti U, Application of the Envelope and Wavelet Transform Analyses for the Diagnosis of Incipient Faults in Ball Bearings. Mechanical Systems and Signal Processing. 2001.vol.15, no. 2, 287-302.
2. Xu M, Spike Energy and Its Applications. The Shock and Vibration Digest, 1995. (5/6), 11-17.
3. He Zhengjia, Yan Ziyang, Meng Qingfeng, Fault diagnosis theory and application of mechanical device unstable signal. Beijing: Higher Education Press. 2001.
4. Burges C J C. A tutorial on support vector machines for pattern recognition.Data Mining and Knowledge Discovery, 1998(2): 121-167.
5. Gunn S R. Support vector machines for classification and regression. Southampton: Department of Electronics and Computer Science of University of Southampton, 1998.1-28.
6. Weston J, Watkins C. Multi-class Support Vector Machines[M]. In Verleysen M, editor.Proceedings of ESANN99, Brussel D.Facto Press, 1999.
7. Li Meng, Research on the Method of Feature Extraction and Pattern Recognition for Bearings Fault of Rotating Machinery[Doctor's Degree Dissertation]. Chang Chun: Jilin University, 2008.