Hierarchical Monitoring for Multi-unit Chemical Processes Based on Local-global Correlation Features

Abstract

A hierarchical process monitoring method based on local-global correlation features is proposed for a class of multi-unit chemical processes. The process operation status is identified by characterizing the correlation within a local unit, between units, and between the local unit and the whole process, through which the monitoring reliability is enhanced. First, based on canonical correlation analysis, individual characteristics and external correlation characteristics of each unit are extracted by introducing correlated variables from neighboring units; Second, multivariate statistical monitoring models are established for individual characteristics of each unit and external correlation characteristics of all units; Then, the unit-variable hierarchical contribution plot is established to locate the fault units and fault variables hierarchically. The effectiveness of the proposed hierarchical monitoring is demonstrated through applications to the Tennessee Eastman process and a laboratory distillation process.