Fault detection in industrial plants plays an important role for ensuring the product quality, safety, and reliability of plant equipment. The purpose of this work is to propose a fault detection technique with a black-box modeling and a statistical module based on Neyman–Pearson test (NPT). In fact, Nonlinear Auto-Regressive Moving Average with eXogenous input (NARMAX) model is used to obtain a model for the normal condition operation. To detect a fault, The NPT has been applied to the residual of NARMAX model. The efficiency of the technique is illustrated through its application to monitor product quality in a distillation unit.
