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A Data-Driven Process Monitoring Approach for Dynamic Processes with Deterministic Disturbance

  • School of Astronautics, Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper presents the study on the data-driven process monitoring system design for the dynamic processes with deterministic disturbance. The basic idea of the proposed method is to identify the stable kernel representation (SKR) of the dynamic process by decomposing the process data into different subspaces. By extracting the maximum influence of the disturbance from fault-free data, a process monitoring system is developed based on the identified data-driven SKR. The performance and effectiveness of the proposed scheme are verified and demonstrated through the numerical study on randomly generated systems.

Original languageEnglish
Title of host publicationProceedings - 2018 IEEE 27th International Symposium on Industrial Electronics, ISIE 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages939-944
Number of pages6
ISBN (Print)9781538637050
DOIs
StatePublished - 10 Aug 2018
Externally publishedYes
Event27th IEEE International Symposium on Industrial Electronics, ISIE 2018 - Cairns, Australia
Duration: 13 Jun 201815 Jun 2018

Publication series

NameIEEE International Symposium on Industrial Electronics
Volume2018-June

Conference

Conference27th IEEE International Symposium on Industrial Electronics, ISIE 2018
Country/TerritoryAustralia
CityCairns
Period13/06/1815/06/18

Keywords

  • Data-driven SKR
  • deterministic disturbance
  • process monitoring
  • residual generation

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