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A novel approach for data mining of steam turbine based on neural network and genetic algorithm is brought forward, aimed at overcoming shortages of some current knowledge attaining methods. The historical fault data of steam turbine is processed with fuzzy and discrete method firstly, a multiplayer backpropagation neural network is structured secondly, the neural network is trained via teacherpsilas...
Based on nonlinear mapping relationship between fault symptom and fault type in subsystems of FOG SINS (fiber-optic gyroscope strapdown inertial system), BP (back propagation) and Elman neural network approaches were presented for fault diagnosis. Fault mechanism and failure behavior of FOG SINS was analyzed, then featured fault types were extracted from FOG SINS faults and the extracted features...
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