Closed‐loop Fault Detection Using the Local Approach

Fault detection and isolation (FDI) has become a crucial issue for industrial process monitoring in order to increase availability, reliability and production safety. Model‐based FDI methods rely on a mathematical model and input‐output data of a process to perform detection. The local approach is a new model‐based FDI method that aims to detect slight changes of a system's parametric properties. Closed‐loop detection is an important issue for the local approach since all control systems work under closed‐loop conditions. A new algorithm was proposed to revise the original detection algorithm in order to make it work for closed‐loop data. Simulation results show that the proposed method can detect the changes of parameters of a system that can affect closed‐loop performance.