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介绍了基于人工神经网络 (ANN)方法的变电站故障诊断的系统 ,并对其容错性进行了研究 ,该系统充分利用人工神经网络所具有的强大的学习能力及高度的容错性等特点 ,实现对变电站故障元件的诊断。仿真结果表明 ,本系统不仅能在输入信息正确的条件下准确地诊断出故障元件 ,而且在输入信息不完整或少部分信息错误的情况下 ,仍能给出满意的诊断结果。
The fault diagnosis system of substation based on artificial neural network (ANN) is introduced and its fault tolerance is studied. The system makes full use of the powerful learning ability and high fault tolerance of artificial neural network, Substation fault component diagnosis. The simulation results show that this system can not only diagnose the faulty components accurately when the input information is correct, but also provide satisfactory diagnosis results when the input information is incomplete or a small amount of information is wrong.