Comprehensive monitoring of industrial processes using multivariable characteristics evaluation and subspace decomposition | |
Li S(李帅)1,2,3,4; Zhou XF(周晓锋)1,2,3; Shi HB(史海波)1,2,3; Pan FC(潘福成)1,2,3; Li X(李歆)1,2,3; Zhang YC(张宜弛)1,2,3 | |
刊名 | CANADIAN JOURNAL OF CHEMICAL ENGINEERING |
2021 | |
页码 | 1-18 |
关键词 | comprehensive monitoring fault detection industrial processes multivariable characteristics subspace decomposition |
ISSN号 | 0008-4034 |
产权排序 | 1 |
英文摘要 | Gaussianity, non-Gaussianity, linearity, and nonlinearity generally coexist within industrial process variables, and should be taken into account simultaneously for process modelling with monitoring. This paper presents a comprehensive monitoring method of industrial processes using multivariable characteristics evaluation and subspace decomposition. First, a multivariable characteristics evaluation method is presented to divide the process variables into the Gaussian linear, Gaussian nonlinear, non-Gaussian linear, and non-Gaussian nonlinear subspaces. Second, the PCA-ICA-KPCA-KICA-based multivariable subspace decomposition is proposed for process modelling. Furthermore, comprehensive monitoring is developed and final results are combined using comprehensive statistics. By multivariable characteristics evaluation and subspace decomposition, the proposed method could evaluate and seek the multivariable characteristics and enhance the performance of process monitoring. The effectiveness and feasibility of the proposed comprehensive monitoring method are demonstrated by a numerical system and the benchmark Tennessee Eastman (TE) process. |
资助项目 | Natural Science Foundation of Liaoning Province, China[2019-MS-344] |
WOS关键词 | INDEPENDENT COMPONENT ANALYSIS ; FAULT-DETECTION ; DIAGNOSIS ; MODEL ; DIVISION ; ICA |
WOS研究方向 | Engineering |
语种 | 英语 |
WOS记录号 | WOS:000691014400001 |
资助机构 | Natural Science Foundation of Liaoning Province, ChinaNatural Science Foundation of Liaoning Province [2019-MS-344] |
内容类型 | 期刊论文 |
源URL | [http://ir.sia.cn/handle/173321/29551] |
专题 | 沈阳自动化研究所_数字工厂研究室 |
通讯作者 | Li S(李帅); Zhou XF(周晓锋) |
作者单位 | 1.Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang, China 2.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China 3.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang, China 4.University of Chinese Academy of Sciences, Beijing, China |
推荐引用方式 GB/T 7714 | Li S,Zhou XF,Shi HB,et al. Comprehensive monitoring of industrial processes using multivariable characteristics evaluation and subspace decomposition[J]. CANADIAN JOURNAL OF CHEMICAL ENGINEERING,2021:1-18. |
APA | Li S,Zhou XF,Shi HB,Pan FC,Li X,&Zhang YC.(2021).Comprehensive monitoring of industrial processes using multivariable characteristics evaluation and subspace decomposition.CANADIAN JOURNAL OF CHEMICAL ENGINEERING,1-18. |
MLA | Li S,et al."Comprehensive monitoring of industrial processes using multivariable characteristics evaluation and subspace decomposition".CANADIAN JOURNAL OF CHEMICAL ENGINEERING (2021):1-18. |
个性服务 |
查看访问统计 |
相关权益政策 |
暂无数据 |
收藏/分享 |
除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。
修改评论