中国化学工程学报（英文版）
中國化學工程學報（英文版）
중국화학공정학보（영문판）
CHINESE JOURNAL OF CHEMICAL ENGINEERING
2015年
1期
146-153
,共8页
High order statistics%Nonlinear characteristics diagnosis%Interpretative structural model%TE process
Nonlinear characteristic fault detection and diagnosis method based on higher-order statistical (HOS) is an effec-tive data-driven method, but the calculation costs much for a large-scale process control system. An HOS-ISM fault diagnosis framework combining interpretative structural model (ISM) and HOS is proposed:(1) the adja-cency matrix is determined by partial correlation coefficient;(2) the modified adjacency matrix is defined by directed graph with prior knowledge of process piping and instrument diagram;(3) interpretative structural for large-scale process control system is built by this ISM method;and (4) non-Gaussianity index, nonlinearity index, and total nonlinearity index are calculated dynamical y based on interpretative structural to effectively eliminate uncertainty of the nonlinear characteristic diagnostic method with reasonable sampling period and data window. The proposed HOS-ISM fault diagnosis framework is verified by the Tennessee Eastman process and presents improvement for highly non-linear characteristic for selected fault cases.
