Improving Monitoring Performance of On-Line Process Based on PCA Method
Principal component analysis (PCA) is very suitable for complex process monitoring and diagnosis, but it suffers many limitations such as great calculation load, poor real-time performance and lacking of on-line monitoring. Here, this paper presents a new method for multi-variable statistical process monitoring. Based on this new method, the principal component monitoring model can be generated in the principal component subspace, and the error monitoring model can be set up in the residual subspace. The method provides a human-machine monitoring interface and related fault-diagnosis interface for integrating Principal/Error/Multi-variable. This will change the real-time data of the multi-variable into the monitoring information of an integrated process, and present them effectively to the operators. With this method, on-line monitoring system was designed for the distillation process as an example, and the effectiveness of this method was illustrated.
process monitoring PCA on-line monitoring human-machine monitoring interface
Kunlin Zhou Gang Rong
School of Mechanical and Electrical Engineering, Shandong University at Weihai, Weihai, 264209 State Key Laboratory of Industrial Control Technology, Institute of Advanced Process Control, Zhejia
国际会议
The 22nd China Control and Decision Conference(2010年中国控制与决策会议)
徐州
英文
4144-4148
2010-05-26（万方平台首次上网日期，不代表论文的发表时间）