摘要：AbstractRecently, 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.
关键词：KeywordsConcurrent projection to latent structures (CPLS)process monitoringquality monitoringcontribution plotsfault diagnosisdata-driven
