中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Monitoring and fault diagnosis for industrial process

文献类型:会议论文

作者Li S(李帅); Zhou XF(周晓锋); Shi HB(史海波); Zheng ZY(郑泽宇)
出版日期2015
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
关键词manifold learning contribution analysis monitoring fault diagnosis
页码1356-1361
中文摘要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.
收录类别EI ; CPCI(ISTP)
产权排序1
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
语种英语
ISSN号2379-7711
ISBN号978-1-4799-8730-6
WOS记录号WOS:000380502300248
源URL[http://ir.sia.cn/handle/173321/17353]  
专题沈阳自动化研究所_数字工厂研究室
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]. 见:2015 IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems (CYBER). Shenyang, China. June 8-12, 2015.

入库方式: OAI收割

来源:沈阳自动化研究所

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