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Corrosion pitting damage detection of rolling bearings using data mining techniques
Zhang YL(章永来); Zhou XF(周晓锋); Shi HB(史海波); Zheng ZY(郑泽宇); Li S(李帅)
Department数字工厂研究室
Source PublicationInternational Journal of Modelling, Identification and Control
ISSN1746-6172
2015
Volume24Issue:3Pages:235-243
Indexed ByEI
EI Accession number20154701562466
Contribution Rank1
Funding OrganizationNational Scientific and Technological Support Projects of China under Grant No.2012BAF12B08
KeywordCorrosion Pitting Machine Learning Support Vector Data Description Rolling Bearings Pca Svdd Principal Component Analysis
AbstractDetection of rolling bearings is very crucial for the reliable operation in the process of condition monitoring of rotating machinery. In this paper, a novel monitoring method using support vector data description (SVDD) with principal component analysis (PCA) for fault diagnosis of corrosion pitting on the raceways and balls in rolling bearings is proposed to improve diagnostic accuracy based on feature extraction dataset of vibration signals. The feasibility and validity of the proposed monitoring scheme are investigated through case study. Experiment results show that the proposed method can achieve 92.85% accuracy, 93.11% sensitivity, and 90.47% specificity based on an unbalanced dataset.
Language英语
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/17292
Collection数字工厂研究室
Corresponding AuthorZhang YL(章永来)
Affiliation1.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
2.University of Chinese Academy of Sciences, Beijing, China
3.Key Laboratory of Networked Control System, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
Recommended Citation
GB/T 7714
Zhang YL,Zhou XF,Shi HB,et al. Corrosion pitting damage detection of rolling bearings using data mining techniques[J]. International Journal of Modelling, Identification and Control,2015,24(3):235-243.
APA Zhang YL,Zhou XF,Shi HB,Zheng ZY,&Li S.(2015).Corrosion pitting damage detection of rolling bearings using data mining techniques.International Journal of Modelling, Identification and Control,24(3),235-243.
MLA Zhang YL,et al."Corrosion pitting damage detection of rolling bearings using data mining techniques".International Journal of Modelling, Identification and Control 24.3(2015):235-243.
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