针对目前浪涌保护器件性能分析方法不完善、缺乏准确数学模型的问题, 提出了一种基于NARX神经网络的电磁脉冲响应时域建模方法, 并给出NARX神经网络建模的理论基础及设计步骤。通过组建传输线脉冲测试平台及静电放电实验平台, 对NUP2105L型瞬态抑制二极管进行注入实验, 采集输入输出实验数据并建立NARX神经网络模型。对建模效果进行分析, 所建模型可以较为准确地预测输入脉冲为方波脉冲、人体金属模型及机器模型静电放电电磁脉冲时, 响应电压曲线趋势、响应时间、脉冲峰值、箝位时间及箝位电压等性能指标, 验证了模型的正确性。

In order to build the electromagnetic pulse response models for surge protectors, a time-domain model based on the NARX neural network is given. The theoretical basis and design steps of modeling with the NARX neural network are presented. The transmission-line pulse system and electrostatic discharge system are built for proving the method. The measurement results obtained in transient voltage suppressor experiment is taken to set up the NARX neural network model. When the input signal is given as a square pulse, machine-model or body-metal-model electrostatic discharge electromagnetic pulse, the established model can forecast performance parameters such as response time, pulse peak and clamping voltage, which verifies the validity of the model.