Fault diagnosis using concurrent projection to latent structures

Yu C. PAN, Yining DONG, S. Joe QIN

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

2 Citations (Scopus)


Recently, a concurrent projection to latent structures (CPLS) for multivariate statistical process was proposed. It has been proved to be a better monitoring method than the traditional PLS. However, its fault diagnosis methods have not been developed yet. In this paper, we discuss a new fault diagnosis approach based on CPLS. Five monitoring indices used in CPLS are unified into two general forms. Based on these general forms, we define their complete decomposition contributions (CDC) and reconstruction-based contributions (RBC). The diagnosability of these two contribution methods is further analyzed. Finally, simulation case studies are presented to demonstrate the results.
Original languageEnglish
Pages (from-to)1276-1281
Number of pages6
Issue number8
Early online date25 Sept 2015
Publication statusPublished - 2015
Externally publishedYes
Event9th IFAC Symposium on Advanced Control of Chemical Processes, ADCHEM 2015 - , Canada
Duration: 7 Jun 201510 Jun 2015


  • Concurrent projection to latent structures (CPLS)
  • Contribution plots
  • Data-driven
  • Fault diagnosis
  • Process monitoring
  • Quality monitoring


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