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题名: Vibration analysis approach for corrosion pitting detection based on SVDD and PCA
作者: 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: 2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER)
会议录出版者: IEEE
会议录出版地: Piscataway, NJ, USA
出版日期: 2015
页码: 1534-1538
收录类别: EI ; CPCI(ISTP)
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
产权排序: 1
WOS记录号: WOS:000380502300280
Citation statistics:
内容类型: 会议论文
URI标识: http://ir.sia.cn/handle/173321/17355
Appears in Collections:数字工厂研究室_会议论文

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Recommended Citation:
Zhang YL,Shi HB,Zhou XF,et al. Vibration analysis approach for corrosion pitting detection based on SVDD and PCA[C]. 见:2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER). Shenyang, China. June 8-12, 2015.
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