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Vibration analysis approach for corrosion pitting detection based on SVDD and PCA
Zhang YL(章永来); Shi HB(史海波); Zhou XF(周晓锋); Zheng ZY(郑泽宇)
作者部门数字工厂研究室
会议名称2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER)
会议日期June 8-12, 2015
会议地点Shenyang, China
会议录名称2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER)
出版者IEEE
出版地Piscataway, NJ, USA
2015
页码1534-1538
收录类别EI ; CPCI(ISTP)
EI收录号20161402187638
WOS记录号WOS:000380502300280
产权排序1
ISSN号2379-7711
ISBN号978-1-4799-8730-6
关键词Machine Learning Rolling Bearing Corrosion Pitting Svdd Pca
摘要This study is focused on corrosion pitting on the raceways and ball in rolling bearings. We analyze 224 records in the time domain, and combine support vector data description (SVDD) with principal component analysis (PCA) algorithm to improve diagnostic accuracy. Experiment results show that the proposed method can achieve good accuracy based on an imbalanced dataset. The new method is thus well-suited for corrosion pitting detection in rolling bearings.
语种英语
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文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/17355
专题数字工厂研究室
作者单位1.Shenyang Institute of Automation, Chinese Academy of Sciences, University of Chinese Academy of Sciences, Beijing, China
2.Shenyang Institute of Automation, Chinese Academy of Sciences, Key Laboratory of Network Control System, Chinese Academy of Sciences, Shenyang, China
推荐引用方式
GB/T 7714
Zhang YL,Shi HB,Zhou XF,et al. Vibration analysis approach for corrosion pitting detection based on SVDD and PCA[C]. Piscataway, NJ, USA:IEEE,2015:1534-1538.
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