new approach to multivariate statistical process control and its application to wastewater treatment process monitoring

This paper presents a new process monitoring and fault diagnosis approach based on a modified Multivariate StatisticalProcess Control (MSPC) and evaluates its applicability to municipal wastewater treatment process monitoring. Firstly,a conventional MSPC, based on Principal Component Analysis (PCA), is adjusted to provide an easy-to-understand userinterface and then a new yet simplified reconfigurable diagnostic model is introduced. The user interface that has beendeveloped is designed to integrate MSPC seamlessly with existing process monitoring systems that use the so-called trendgraphs. The proposed diagnostic model is constructed by aggregating small models with either one or two inputs, whichenhances the tractability of the diagnostic model. The effectiveness of the modified MSPC is demonstrated through a series of offline and online experiments, using a set of real multivariate process data from a municipal wastewater treatment.plant.