Multirate Factor Analysis Models for Fault Detection in Multirate Processes

Abstract

Generally, the measurements of modern industries are collected from different sources, which indicates that the traditional multivariate statistical process monitoring methods cannot be directly used in the multirate systems if one aims to utilize the complete multirate measurements. Hence, a set of multirate factor analysis models is developed for process modeling and fault detection purpose in the multirate processes. In the proposed model, the cross correlations are described and bounded by the common factors and the model parameters are calibrated using the expectation–maximum algorithms. Also, the proposed models are further discussed both from theoretical and geometric perspective. Finally, the proposed fault detection methods are tested by a simulated Tennessee–Eastman process and a real R2S anaerobic reactor unit in the wastewater treatment process.