Title :
Modeling and monitoring of multimode process based on between-mode relative analysis
Author :
Yingwei, Zhang ; Yunpeng, Fan ; Rongrong, Sun
Author_Institution :
State Laboratory of Synthesis Automation of Process Industry, Northeastern University, Shenyang 100819, China
Abstract :
The between-mode relative analysis algorithm based on kernel independent component analysis (KICA) for multimode process monitoring is proposed in this paper. The main contributions of the proposed approach are as follows: 1) KICA algorithm is used to extract the independent components, and then find the relationship between different modes;2) according to the relative changes which are obtained by the proposed algorithm, each mode is divided into three parts which contain the increased part, the decreased part and the unchanged part; 3) the monitoring statistics are calculated to detect fault and recognize modes for the three parts above respectively. The performance of the proposed method is illustrated by Tennessee Eastman Process (TEP). Comparing to the traditional multimode method, the experiment results show the advantage of the proposed approach.
Keywords :
Algorithm design and analysis; Covariance matrices; Data models; Loading; Monitoring; Principal component analysis; Signal processing algorithms; Between-mode Relative Analysis; Fault Monitoring; Kernel Independent Component Analysis (KICA); Mode Recognition;
Conference_Titel :
Control Conference (CCC), 2015 34th Chinese
Conference_Location :
Hangzhou, China
DOI :
10.1109/ChiCC.2015.7260637