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首页> 外文期刊>IEEE Transactions on Electromagnetic Compatibility >Modeling and Optimization of EMI Filter by Using Artificial Neural Network
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Modeling and Optimization of EMI Filter by Using Artificial Neural Network

机译:用人工神经网络建模与优化EMI滤波器

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摘要

In power electronic devices, high-speed switching often causes serious electromagnetic interference (EMI) problems. For compliance with electromagnetic compatibility standards, EMI filters are widely used. This article develops an efficient modeling and optimization method of EMI filter by employing artificial neural network (ANN). A partly connected ANN, which is accurate and time saving in training procedure, is proposed to model an EMI filter. Moreover, genetic algorithm and the EMI filter model based on the partly connected ANN are applied to optimizing the EMI filter. Through comparing simulated and measured results of insertion loss of EMI filter, the proposed modeling and optimization method is validated. Compared to equivalent circuit model and electromagnetic model, the proposed method can establish a more accurate EMI filter model and can optimize the design of the EMI filter more efficiently.
机译:在电力电子设备中,高速切换通常会导致严重的电磁干扰(EMI)问题。为了符合电磁兼容性标准,EMI过滤器被广泛使用。本文通过采用人工神经网络(ANN)开发EMI滤波器的有效建模和优化方法。建议将部分连接的ANN,其在​​训练过程中准确,节省时间,以模拟EMI滤波器。此外,基于部分连接的ANN的遗传算法和EMI滤波器模型应用于优化EMI滤波器。通过比较EMI滤波器插入损耗的模拟和测量结果,验证了所提出的建模和优化方法。与等效电路模型和电磁模型相比,所提出的方法可以建立更精确的EMI滤波器模型,可以更有效地优化EMI滤波器的设计。

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