随着社会的发展，变电站噪声越来越受到人们的关注，因此有必要对变电站噪声进行研究。首先利用声级计对重庆和尚山110 kV变电站的噪声进行测量，并利用灰色GM(1,1)方法对变电站噪声进行预测，可以得到每月噪声的变化情况；然后利用径向基函数(radical basis function, RBF)神经网络对不同温度、距离的噪声进行预测。最后利用RBF神经网络对不同温度和变压器运行负荷时的噪声进行计算，为新建变电站的设计提供参考。

With the development of society, the audible noise in substation has been paid more and more attention, so it is necessary to study the substation’s audible noise. Firstly, the noise of 110 kV Heshangshan Substation in Chongqing was measured with sound level meter, and the audible noise in substation was predicted by using GM(1,1) model, with which the monthly variation of the noise can be obtained. Then, the noise in different temperatures and distances was predicted by using radical basis function (RBF) neural network. Finally, the audible noise in different temperatures and operation loads of transformer was calculated with using RBF neural network, which could provide references for the design of new substations.