A Modified Outlier Detection Method in Dynamic Data Reconciliation

作     者：周凌柯 苏宏业 褚健 

作者机构：Department of Automation Nanjing University of Science & Technology Institute of Advanced Process Control Zhejiang University Hangzhou 310027 China Institute of Advanced Process Control Zhejiang University 

出 版 物：《Chinese Journal of Chemical Engineering》 (中国化学工程学报（英文版）)

年 卷 期：2005年第13卷第4期

页      面：542-547页

核心收录：

学科分类：07[理学] 070104[理学-应用数学] 0701[理学-数学] 

基　　金：Supported by the National Outstanding Youth Science Foundation of China (No. 60025308) and Key Technologies R&DProgram in the 10th Five-year Plan (No. 2001BA204B07) 

主　　题：data reconciliation outlier detection gross error 

摘      要：Data reconciliation technology can decrease the level of corruption of process data due to measurement noise, but the presence of outliers caused by process peaks or unmeasured disturbances will smear the reconciled results. Based on the analysis of limitation of conventional outlier detection algorithms, a modified outlier detection method in dynamic data reconciliation (DDR) is proposed in this paper. In the modified method, the outliers of each variable are distinguished individually and the weight is modified accordingly. Therefore, the modified method can use more information of normal data, and can efficiently decrease the effect of outliers. Simulation of a continuous stirred tank reactor (CSTR) process verifies the effectiveness of the proposed algorithm.