Abstract
In this paper, we introduce a novel fault detection and diagnosis method using a dynamic independent component analysis-based approach. We also present an innovative mechanism for detecting and diagnosing the faults. The proposed approach is able to accurately detect and isolate the root causes for each individual fault. The Tennessee Eastman challenge process is used to demonstrate the much improved performance of our proposed technique in comparison with other currently existing statistical monitoring and fault detection methods.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have