DocumentCode
724231
Title
A monitoring method based on combination of EPCA and RPCA
Author
Wang Xiao-gang ; Sun Jie ; Hu Hao ; Sha Yi ; Zhu Chun-li
Author_Institution
Coll. of Inf. Sci. & Eng., Northeastern Univ., Shenyang, China
fYear
2015
fDate
23-25 May 2015
Firstpage
2752
Lastpage
2757
Abstract
Process monitoring is a very important measure which ensures process safety and stable operation. Considering the insufficient process information at the very beginning of new process and the necessity that process model needs to be updated constantly in order to adapt to process changes, a method based on a combination of extended principal component analysis (EPCA) and recursive principal component analysis (RPCA) is proposed in this article. Afterwards, the method proposed is applied in grinding processes and simulated, which shows that the method can not only effectively solve the problem of critical shortage of process information when a new process is run, but also improve the utilization rate of the normal followed-up samples, making process model more adaptable to process variability. Finally, the simulations results illustrate effectiveness and practicality of the investigated method.
Keywords
grinding; principal component analysis; process monitoring; EPCA; RPCA; extended principal component analysis; grinding processes; process monitoring; process safety; recursive principal component analysis; Adaptation models; Data models; Matrix decomposition; Monitoring; Principal component analysis; Process control; Simulation; EPCA; Grinding Process; Process Monitoring; RPCA;
fLanguage
English
Publisher
ieee
Conference_Titel
Control and Decision Conference (CCDC), 2015 27th Chinese
Conference_Location
Qingdao
Print_ISBN
978-1-4799-7016-2
Type
conf
DOI
10.1109/CCDC.2015.7162397
Filename
7162397
Link To Document