文献类型：期刊文献

英文题名：Temporal-Spatial Global Locality Projections for Multimode Process Monitoring

作者：Song, Bing[1];Shi, Hongbo[1]

机构：[1]East China Univ Sci & Technol, Minist Educ, Key Lab Adv Control & Optimizat Chem Proc, Shanghai 200237, Peoples R China

年份：2018

卷号：6

起止页码：9740

外文期刊名：IEEE ACCESS

收录：;EI(收录号：20180604751545);WOS:【SCI-EXPANDED(收录号:WOS:000427913700001)】；

基金：This work was supported in part by the National Natural Science Foundation of China under Grant 61703161, Grant 61374140, and Grant 61673173, in part by the Fundamental Research Funds for the Central Universities under Grant 222201714031 and Grant 222201717006, and in part by the China Postdoctoral Science Foundation under Grant 2017M611472.

语种：英文

外文关键词：Multimode process monitoring; temporal and spatial scale; local and global structure; temporal-spatial global locality projections

摘要：Multimode is an important feature of modern processes, since various manufacturing strategies are needed to satisfy different demands of markets. Direct application of traditional multivariate statistical process monitoring methods cannot obtain satisfactory results, as the data set collected from multimode processes always follows multimodal distribution. To construct a single model which can monitor multimode processes directly, this paper proposes an original algorithm named temporal-spatial global locality projections. First, given that both temporal and spatial neighbors can express the similarity, the determination of the neighborhood is conducted in both the temporal and spatial scale. Second, an optimization objective function which preserves not only the local structure but also the global structure is defined. Third, the monitoring statistic is established via the local outlier factor. To certify the effectiveness, a numerical example, the multimode Tennessee Eastman process, and the CE117 process which is proposed by TecQuipment for process control are studied.