Model Acceptability Measure for the Identi cation of Failures in Qualitative Fault Monitoring Systems

This paper deals with two of the main tasks of Fault Monitoring Systems (FMS): fault detection and fault identiication. During fault detection, the FMS should recognize that the plant behavior is abnormal, and therefore, that the plant is not working properly. During fault identiication, the FMS should conclude which type of failure has occurred. The rst goal of this work is to consolidate a new fault detection technique, called enveloping, that was developed in the context of the Fuzzy Inductive Reasoning Fault Monitoring System (FIRFMS). The second and primary goal of this paper is to introduce the model acceptability measure as a tool to enhance and make more robust the fault identiica-tion process in the context of FIRFMS. The enveloping technique and the model acceptability measure are applied to an electric circuit model previously used for such purpose in the literature. It is shown that the new methods outperform the ones previously advocated in FIRFMS for that purpose 1 .