Monitoring and Fault Diagnosis of Chemical Processes Based on CMPCA

This paper presents a monitoring and fault diagnosis method for chemical processes based on consistent multi-way principal component analysis (CMPCA). Firstly, data from different batches will be synchronized based on dynamic time warping (DTW) technique, then the consistent data will be used for modeling and fault diagnosis, which makes the monitoring and fault diagnosis for batch processes more reliable.