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.