使用神经网络设计小型化90度混合合器,具有广泛的排斥带
Golshan Mohamadpour1, Salman Karimi1, Saeed Roshani2
1Department of Electrical Engineering, Lorestan University, Khorramabad 68151, Iran.
Micromachines
|May 25, 2024
概括
本研究介绍了一种使用人工神经网络 (ANN) 来优化低通波器 (LPF) 的紧型3dB90度混合合器. 该设计实现了显著的尺寸缩小和有效的和声抑制,以提高性能.
科学领域:
- 电气工程 电气工程
- 电磁学 电磁学 电磁学 电磁学
- 微波工程 微波工程
背景情况:
- 传统的3dB90度混合合器经常面临庞大的尺寸和有限的波排斥能力的挑战.
- 优化微波电路的组件参数通常涉及复杂的模拟和代设计过程.
研究的目的:
- 设计一个紧的3dB90度混合合器,增强波排斥.
- 利用人工神经网络 (ANN) 来自动化和简化集成低通波器 (LPF) 的设计.
主要方法:
- 将四个低通波器 (LPF) 集成到3dB90度混合合器结构中.
- 使用在电磁 (EM) 模拟数据上训练的人工神经网络 (ANN) 来确定LPF尺寸和参数 (切断频率,带宽,插入损失).
主要成果:
- 为1800 MHz合器实现了73%的尺寸缩小,其尺寸为16.6 mm × 15.15 mm.
- 证明了从4.8GHz到11.2GHz的广泛波排斥波段,抑制了第二到第六波.
- 在工作频率上获得低插入损失,小于0.1dB.
结论:
- 拟议的基于ANN的设计方法为开发紧型和高性能混合合器提供了一种简化和自动化的方法.
- 设计的合器表现出优异的尺寸缩小和有效的和声抑制,使其适合各种微波应用.
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