The nonlinear autoregressive network with exogenous inputs (NARX) is a recurrent dynamic neural architecture, which is commonly used for input–output modeling of nonlinear dynamical systems. Due to the lack of accurate mathematical model for the performance analysis on surge protective devices (SPDs), with the input of fast rising time electromagnetic pulse (FREMP), the NARX neural network is employed to predict the response characteristics of SPD in this paper. In order to verify the feasibility of this method, SPD test system is set up according to IEC 61000-4-24. The results show that the response curve estimated by the proposed model is in good agreement with experimental results, especially the waveform parameters such as response time, pulse peak, and residual voltage. The good forecasting performance of the network suggests that the NARX model used in this paper has good generalization ability. Moreover, with less measured data it can predict the response of the SPD under different voltage levels that were not yet measured.

中文翻译：

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基于NARX神经网络的电涌保护器响应特性预测

具有外生输入的非线性自回归网络 (NARX) 是一种循环动态神经架构，通常用于非线性动力系统的输入-输出建模。由于缺乏对浪涌保护器（SPD）性能分析的准确数学模型，本文在快速上升时间电磁脉冲（FREMP）输入下，采用NARX神经网络对SPD的响应特性进行预测。为了验证该方法的可行性，根据IEC 61000-4-24建立了SPD测试系统。结果表明，所提模型估计的响应曲线与实验结果吻合较好，尤其是响应时间、脉冲峰值、残余电压等波形参数。网络良好的预测性能表明本文采用的NARX模型具有良好的泛化能力。此外，通过较少的测量数据，它可以预测 SPD 在尚未测量的不同电压水平下的响应。