【作者】 韩凤玲； 陈希有； 董慧峰；

【Author】 HAN Feng-ling, CHEN Xi-you, DONG Hui-feng (Department of Electrical Engineering, Harbin Institute of Technology, Harbin 150001, China)

【机构】 哈尔滨工业大学电气工程系；

【摘要】 为了克服测试误差对相间参数的影响,建立了传输线的神经网络模型,通过给网络提供完善的、能够克服测试误差的样本,选择适当的训练方法,使网络能以较快的速度收敛。仿真研究证明,该传输线的神经网络模型可以有效地克服幅值与相位测试误差,提高了相间参数的测试精度。更多还原

【Abstract】 To overcome the influence of parameter measurement error on phase-to-phase parameters, this paper presents a neural network model for transmission line. By providing a sample that is satisfactory and can resist measurement-error, choosing a proper training method, the network is less time-consuming. Simulation research proves that this NN model can resist amplitude-error and phase-error successfully, and can raise the measuring precise of phase-to-phase parameter.更多还原