Abstract
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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
