Title :
Research on process monitoring method based on SPC and PCA technology
Author :
Zhou, Kunlin ; Guo, Rongsheng
Author_Institution :
Sch. of Mech., Electr. & Inf. Eng., Shandong Univ. at Weihai, Weihai, China
Abstract :
In order to overcome the interaction between variables for the multivariate process monitoring, a new method to use statistical process control and principal component analysis was proposed, which reduced the multivariate process data by the matrix operation. It can extract the main features of the process variable, and set up the upper and lower monitoring limits for the production process, and change the real-time data of the multi-variable into the monitoring information of an integrated process, and present effectively the information to the operators. With this method, it can eliminate the interaction between variables and provide the information quickly and efficiently for the fault diagnosis of production process. An on-line monitoring system was designed for the distillation process as an example, and the effectiveness of this method was illustrated.
Keywords :
condition monitoring; distillation; fault diagnosis; feature extraction; matrix algebra; principal component analysis; statistical process control; distillation process; fault diagnosis; feature extraction; matrix operation; multivariate process monitoring; online monitoring system; principal component analysis; process monitoring method; production process; statistical process control; Fluctuations; Mathematical model; Monitoring; Principal component analysis; Process control; Production; Real time systems; PCA; SPC; fault diagnosis; interaction; monitoring limits; process monitoring;
Conference_Titel :
Control and Decision Conference (CCDC), 2011 Chinese
Conference_Location :
Mianyang
Print_ISBN :
978-1-4244-8737-0
DOI :
10.1109/CCDC.2011.5968271