SADEP—a fuzzy diagnostic system shell-an application to fossil power plant operation

Abstract Artificial Intelligence applications in large-scale industry, such as fossil fuel power plants, require the ability to manage uncertainty and time. In these domains, the knowledge about the process comes from experts' experience and it is generally expressed in a vague-fuzzy way using ill-defined linguistic terms. In this paper, we present a fuzzy expert system shell to assist an operator of fossil power plants. The fuzzy expert system shell, called SADEP, is based.on a new methodology for dealing with uncertainty and time called Fuzzy Temporal Network (FTN). The FTN generates a formal and systematic structure used to model the temporal evolution of a process under uncertainty. The inference mechanism for a FIN consists in the calculation of the possibility degree of the real time occurrence of the events using the fuzzy compositional rule Sup-min. A FTN can be used to recognize the significance of events and state variables with respect to current plant conditions and predict the future propagation of disturbances. SADEP was validated with the diagnosis of two detailed disturbances of a fossil power plant: a power load increment in the drum level and a water condenser pump failure. The evaluations performed in this work indicate that SADEP can potentially improve plant availability through early diagnosis of disturbances that could lead to plant shutdown.