高功率腔体滤波器的电磁-热-力多物理场智能代理模型及快速预测

Intelligent surrogate model for the fast prediction of electromagnetic-thermalmechanical multiphysics in high-power cavity filters

电磁多物理场计算在模拟高功率微波器件方面至关重要。为了快速且精确地获取高功率腔体滤波器中由电磁引发的多物理场响应,本文构建了一种基于数据驱动的电磁多物理场代理模型。首先利用有限元方法建立腔体滤波器的多物理场响应数据库,随后基于该数据库构建数据驱动的人工神经网络代理模型。结果对比表明:该代理模型能够精确且快速地预测高功率腔体滤波器在不同输入功率下的S参数曲线,预测精度超过98%,预测时间少于0.2 s;相较于传统的电磁多物理场数值计算方法,计算速度提升了3个数量级以上。因此,本文代理模型的快速精确预测能力对新型高功率微波器件的稳定性分析、可靠性评估和优化设计具有重要的理论指导意义和实际工程应用价值。

The computation of electromagnetically induced multiphysics plays a crucial role in the design of highpower microwave devices.To rapidly and accurately obtain the multiphysics responses induced by electromagnetic fields in high-power cavity filters,this paper proposes a data-driven surrogate model.Specifically,we first build a multiphysics response database for cavity filters by using the finite element method.Subsequently,we develop a datadriven artificial neural network surrogate model based on this database.The result comparison demonstrates that the surrogate model can accurately and fast predict the S-parameter curves of high-power cavity filters under different input powers,with a prediction accuracy exceeding 98%and a prediction time of less than 0.2 s.Compared to traditional numerical computations of electromagnetically induced multiphysics,the computational speed is improved by more than three orders of magnitude.Therefore,the fast and accurate prediction capability of this innovative surrogate model holds significant implications for the stability analysis,reliability assessment,and optimization design of novel highpower microwave devices.