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建立了定子水内冷方式发电机定子绕组的动态温度水力模型,通过推导与计算,得到描述定子绕组动态温度水力模型的解析表达式。用径向基函数(RBF)神经网络对模型参数进行辨识,求取了单调连续2个负荷之间定子线棒温度的过渡时间,以此作为监测发电机运行状况的判据。通过对某电厂一台600MW汽轮发电机进行计算,证明了该方法的正确性。用这种方法进行热故障在线监测最大的优点是不受定子线棒温度延迟时间的影响,具有较大的实用价值。
The dynamic temperature-hydraulic model of the stator windings of stator-water intercooled generator was established. The analytical expression describing the dynamic temperature-hydraulic model of the stator windings was obtained by derivation and calculation. The radial basis function (RBF) neural network is used to identify the parameters of the model, and the transition time of the stator bar temperature between two consecutive monotonic loads is obtained, which can be used as a criterion to monitor the operating status of the generator. Through the calculation of a 600MW turbine generator in a power plant, the correctness of the method is proved. The biggest advantage of on-line thermal fault detection using this method is that it is not affected by the delay time of the stator bar temperature and has great practical value.