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Monitoring and fault diagnosis for industrial process
Li S(李帅); Zhou XF(周晓锋); Shi HB(史海波); 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1356-1361
收录类别EI ; CPCI(ISTP)
EI收录号20161402187679
WOS记录号WOS:000380502300248
产权排序1
ISSN号2379-7711
ISBN号978-1-4799-8730-6
关键词Manifold Learning Contribution Analysis Monitoring Fault Diagnosis
摘要Monitoring and fault diagnosis are crucial for industrial process. In this paper, a simple and efficient manifold learning method is used for process monitoring and fault diagnosis. Firstly, local neighbor relationship of process data is used for process modelling, which divides process data into the embedding space and residual space. Then, different statistics and confidence limits are computed, which can be used for monitoring. Finally, the contribution analysis based on manifold learning is used for fault diagnosis. When the fault variables are found, quality control can be introduced to improve production safety and quality stabilization in industrial process. The manifold learning method is applied for one practical foods industrial production process. The experiment results show the feasibility and efficiency of the manifold learning method for monitoring and fault diagnosis.
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/173321/17353
专题数字工厂研究室
作者单位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
Li S,Zhou XF,Shi HB,et al. Monitoring and fault diagnosis for industrial process[C]. Piscataway, NJ, USA:IEEE,2015:1356-1361.
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