Fault Detection for Nonlinear Processes Based on Local Linear Fuzzy Models in Parallel and Series-Parallel Mode

Abstract

In this contribution, a new approach for model-based fault detection and isolation (FDI) of sensor faults for non linear processes is presented. A local linear fuzzy model of the process is used for the generation of structured residual equations similar to the parity space approach. The model is run in parallel and series-parallel to the process which leads to residuals with different sensitivities. The practical applicability is illustrated on an industrial scale thermal plant. Here, five different faults can be detected and isolated continuously over all ranges of operation.