During the fault diagnosis of generator units

the similarity modeling method(SBM) can be used to obtain the equipment operation characteristics through calculating the historical data

which can monitor the equipment in real-time.The fuzzy probability signed directed graph(FPSDG) can be used for fault diagnosis of equipment by establishing a complete cell library and probability tables

which can accurately locate the equipment faults.Combing the advantages of SBM and FPSDG

the equipment monitoring and fault diagnosis method based on SBMFPSDG is obtained in this study.Take the high pressure(HP) heater as the research object

the SBM model is established based on its historical operating data

and the fault cell library and probability tables are obtained according to the operating characteristics of the equipment.Then the HP heater monitoring and fault diagnosis can be realized.This method is used to calculate and simulate the No.1 HP heater of a 600 MW domestic unit.The results show that this method can accurately estimate the HP heater parameters

which has great real-time monitoring ability.Moreover

by this method

the fault can be alarmed and accurately located in the early stage of equipment failure.In short

this fault diagnosis method is simple and suitable for engineering applications.