Multiblock Concurrent PLS for Decentralized Monitoring of Continuous Annealing Processes

Qiang LIU, S. Joe QIN, Tianyou CHAI

Research output: Journal PublicationsJournal Article (refereed)peer-review

119 Citations (Scopus)

Abstract

In this paper, a data-driven multiblock concurrent projection to latent structures (CPLS) method is proposed for monitoring large-scale manufacturing lines, particularly for cold rolling continuous annealing processes (CAPs) fault diagnosis. The proposed method provides decentralized process monitoring and helps localize faults in both input variables and output variables concurrently. First, the CPLS-based process monitoring method is briefly reviewed. Second, a multiblock CPLS algorithm, which incorporates process block partition, is proposed to diagnose faults relevant to process inputs or outputs with a decentralized structure. For the CAP line application, tension-specific variations, roll-specific variations, and tension-roll covariations are analyzed in each partitioned block. Furthermore, within the roll-specific subspace of an abnormal block, a delay-alignment scheme based on strip transportation delay is proposed to diagnose defective processing materials. © 1982-2012 IEEE.
Original languageEnglish
Article number6729046
Pages (from-to)6429-6437
Number of pages9
JournalIEEE Transactions on Industrial Electronics
Volume61
Issue number11
Early online date30 Jan 2014
DOIs
Publication statusPublished - Nov 2014
Externally publishedYes

Fingerprint

Dive into the research topics of 'Multiblock Concurrent PLS for Decentralized Monitoring of Continuous Annealing Processes'. Together they form a unique fingerprint.

Cite this