Multiple-fault diagnosis of the Tennessee eastman process based on system decomposition and dynamic PLS

The hybrid fault diagnosis method based on a combination of the signed digraph and partial least-squares (PLS) has the advantage of improving the diagnosis resolution, accuracy, and reliability, compared to those of previous qualitative methods, and of enhancing the ability to diagnose multiple fault [Ind. Eng. Chem. Res. 2003, 42, 6145-6154]. In this study, the method is applied for the multiple fault diagnosis of the Tennessee Eastman challenge process. The target process is decomposed using the local qualitative relationships of each measured variable. Linear and quadratic models based on dynamic PLS are built to estimate each measured variable, which is then compared with the estimated value in order to diagnose the fault. Through case studies, the proposed method demonstrated a good diagnosis capability compared with previous statistical methods.