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Hybrid intelligent diagnostic method for large steam turbine generator sets

JIANG Dongxiang, NI Weidou Department of Thermal Engineering, Tsinghua University, Beijing 100084, China  
In order to improve the ability of condition monitoring and fault diagnostic system, a hybrid intelligent diagnostic method for condition monitoring and fault diagnosis of large steam turbine generator sets is proposed. This method integrates different intelligent diagnostic techniques, includes signal analysis, fuzzy logic, fuzzy pattern recognition, fuzzy neural network and knowledge based systems. It has been used to monitor, analyze and diagnose the condition of thermal system and vibration faults of machinery in power plants.
【Fund】: 国家攀登计划
【CateGory Index】: TM311.07
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