| Summary: | The objective of the study is to build an automated system to monitor and control the turbine generator (TG) processes, based on acoustic analysis of the stator failures, for the purpose of improving the operating efficiency of the nuclear power plant (NPP) as a whole. This requires the development of an information and measurement system (IMS) which receives information on the status of the TG stator windings from the noise detectors installed on the TG surface. Acoustic analysis of the TG “hot” spots is used to identify the TG status.
Petri nets were used to build a stochastic model of the automated TG monitoring and control system. The model in question allows local changes in the status of the TG stator windings to be detected and makes it possible to reduce the problem dimensionality through the selection of a subset of conditions leading to a risk of the stator failure. The model is simple and features a high speed of response. The use of the IMS structure under consideration enables the TG condition to be detected at the initial failure stage and the measurement process rate to be increased tenfold.
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