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Artificial neural network modeling of electromagnetic interference caused by nonlinear devices inside a metal enclosure

机译:金属外壳内部非线性设备引起的电磁干扰的人工神经网络建模

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The artificial neural network (ANN) modeling of electromagnetic interference from a nonlinear device connected with transmission lines exposed to electromagnetic field to the linear device inside a metal enclosure is investigated in this paper. A rectangular loop antenna operating at 2.5GHz is used to excite electromagnetic field inside an enclosure with dimension 99x49x44cm(3). Another wideband loop antenna welded with a HSMS-282C Schottky diode pair is used as the nonlinear device connected with the transmission line in order to enhance the coupling and radiating effects inside the enclosure. The linear devices are three monopole probes connected with spectrum analyzer to measure the output power. Experimental results show that the output power from probes near the wideband loop welding with a pair of diodes contains not only fundamental but harmonic components, which are caused by the nonlinear response of diodes excited by induced current. A three-layer ANN model is proposed to predict this nonlinear electromagnetic interference inside the metal enclosure. Results show that the trained BL-MLP model using 576 measured data can predict the response of probes (linear device) interfered by the loop antenna welding with diodes (nonlinear device) inside the cavity well.
机译:本文研究了一种人工神经网络(ANN)对来自与暴露于电磁场的传输线相连的非线性设备到金属外壳内部线性设备的电磁干扰进行建模的方法。使用工作在2.5GHz的矩形环形天线来激发尺寸为99x49x44cm(3)的机柜内部的电磁场。另一个焊接有HSMS-282C肖特基二极管对的宽带环形天线用作与传输线连接的非线性设备,以增强外壳内部的耦合和辐射效果。线性设备是与频谱分析仪连接的三个单极探头,用于测量输出功率。实验结果表明,在宽带环路焊接一对二极管附近的探头的输出功率不仅包含基波分量,而且还包含谐波分量,这是由感应电流激发的二极管的非线性响应引起的。提出了一个三层神经网络模型来预测金属外壳内部的这种非线性电磁干扰。结果表明,使用576个测量数据训练的BL-MLP模型可以预测腔室内部二​​极管(非线性器件)与环形天线焊接干扰的探针(线性器件)的响应。

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