Fault Root Diagnosis based on Partial Symbol Transfer Entropy

Transfer entropy is a data-driven model-free method, which can obtain the causal relationship between variables, and has been applied in the fields of complex industrial process modeling, monitoring and fault diagnosis. Transfer entropy can detect the causal relationship between variables without assuming any basic model. Because the signal will appear non-stationary time series in which both mean and variance change, so the method of partial symbol transfer entropy is proposed to detect the causality of non-stationary time series, and then the causal network diagram is obtained. The effectiveness of the method is verified by simulation and actual industrial case (Tennessee-Eastman process).