Batch process monitoring and fault diagnosis based on improved MPLS

Aiming at the defect of three-dimensional data pre-processing of traditional partial least squares (MPLS) in batch process online monitoring, a improved method of MPLS is researched to do online monitoring and fault diagnosis. In the data pre-processing, the method combines the advantages of traditional expanding methods. It contains information of different batches that remove the nonlinear and dynamic characteristics of the process at a certain extent, as well as resolving the problem of data filled in online applications; In calculating the monitoring statistic of T², the method researched in this paper uses time-varying covariance to replace the fixed one of principal components, which fully considers the dynamic characteristics of the score vector. Meanwhile, aiming at the problem of characteristic of lagging in process that the ordinary contribution plot method is difficult to correctly display the source of the fault of the current moment, a fault diagnosis method based on time-varying contribution plot is proposed in this paper. The improved method was proved to be effective by comparing with traditional MPLS through experiments.