Application of DTF method in disturbance propagation analysis of complex chemical process

Ke Li, Lei Xie, Xiaocheng Ge, Xu Wang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Oscillations usually propagate to other loops with the delivery of mass and energy, then cause plant-wide oscillation and affect the performance of whole control system in complex chemical process. DTF (Directed Transfer Function) method, which has been widely used to analyze information flow in the brain structures in biomedical area, is applied to the disturbance propagation analysis of complex chemical process in this paper. Based on MVAR (Multivariate Autoregressive) model, DTF can analyze the multivariate causality simultaneously and calculate the causality quantitatively. Based on the DTF value, one can draw the causality graph, get the disturbance propagation path and finally locate fault sources. The results of simulation on TEP (Tennessee Eastman Process) are presented to illustrate the effectiveness of the proposed approach.

Original languageEnglish
Title of host publicationProceedings of the 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014
PublisherIEEE Computer Society
Pages685-689
Number of pages5
ISBN (Print)9781479931064
DOIs
Publication statusPublished - 2014
Externally publishedYes
Event11th International Conference on Networking, Sensing and Control - Miami, United States
Duration: 7 Apr 20149 Apr 2014

Conference

Conference11th International Conference on Networking, Sensing and Control
Abbreviated titleICNSC 2014
CountryUnited States
CityMiami
Period7/04/149/04/14

Fingerprint Dive into the research topics of 'Application of DTF method in disturbance propagation analysis of complex chemical process'. Together they form a unique fingerprint.

  • Cite this

    Li, K., Xie, L., Ge, X., & Wang, X. (2014). Application of DTF method in disturbance propagation analysis of complex chemical process. In Proceedings of the 11th IEEE International Conference on Networking, Sensing and Control, ICNSC 2014 (pp. 685-689). [6819708] IEEE Computer Society. https://doi.org/10.1109/ICNSC.2014.6819708