An Adaptive Data-Driven Fault Detection Method for Monitoring Dynamic Process

This paper presents an adaptive data-driven fault detection method for dynamic processes. In this method, the vector ARX model is used to model the dynamic process in a data-driven fashion. Then, the adaptive method is developed by means of the incremental and decremental algorithms. The performance and effectiveness of the proposed approach are demonstrated with a numerical case study and an experimental continuous stirred tank heater. The detection results show that the effectiveness of the proposed method.