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基于神经网络的声学超材料板正反向设计方法

陈为谦 郭辉 傅伟 孙裴 王岩松

陈为谦, 郭辉, 傅伟, 孙裴, 王岩松. 基于神经网络的声学超材料板正反向设计方法[J]. 上海工程技术大学学报, 2025, 39(3): 347-353, 374. doi: 10.12299/jsues.24-0163
引用本文: 陈为谦, 郭辉, 傅伟, 孙裴, 王岩松. 基于神经网络的声学超材料板正反向设计方法[J]. 上海工程技术大学学报, 2025, 39(3): 347-353, 374. doi: 10.12299/jsues.24-0163
CHEN Weiqian, GUO Hui, FU Wei, SUN Pei, WANG Yansong. Forward-reverse design method for acoustic metamaterial plates based on neural networks[J]. Journal of Shanghai University of Engineering Science, 2025, 39(3): 347-353, 374. doi: 10.12299/jsues.24-0163
Citation: CHEN Weiqian, GUO Hui, FU Wei, SUN Pei, WANG Yansong. Forward-reverse design method for acoustic metamaterial plates based on neural networks[J]. Journal of Shanghai University of Engineering Science, 2025, 39(3): 347-353, 374. doi: 10.12299/jsues.24-0163

基于神经网络的声学超材料板正反向设计方法

doi: 10.12299/jsues.24-0163
基金项目: 国家自然科学基金(52172371);上海市优秀学术/技术带头人计划项目(21XD1401100);上海市新能源汽车振动噪声评价与控制技术专业服务平台(18DZ2295900)
详细信息
    作者简介:

    陈为谦(1997 − ),男,硕士生,研究方向为声学超材料板智能设计方法。E-mail:chenwq99@foxmail.com

    通讯作者:

    郭 辉(1981 − ),男,教授,博士,研究方向为振动噪声测控技术。E-mail:hgsues@163.com

  • 中图分类号: TB535

Forward-reverse design method for acoustic metamaterial plates based on neural networks

  • 摘要: 声学超材料板是一种可以在特定频率范围内禁止弹性波传播的人工复合结构,由于存在多种机理的共同作用,其物理性能难以用理论公式进行推导和表述。设计一种基于局域共振机理的声学超材料板结构,利用有限元方法对其带隙特性进行分析,获得不同元胞结构参数及对应带隙特性,建立声学超材料板样本集。设计正向设计神经网络模型,获取结构参数与带隙范围的正向映射关系,实现输入结构参数即可输出相应的带隙范围的正向预测。在此基础上,提出一种反向设计神经网络模型,实现根据目标带隙范围获取声学超材料板结构参数的反向设计。仿真结果表明,提出的声学超材料板正反向设计方法可以避免复杂繁琐的理论推导和计算,有助于推动声学超材料领域的进一步发展。
  • 图  1  声学超材料板基本单元

    Figure  1.  Unit of AMP

    图  2  正方形单元不可约布里渊区

    Figure  2.  Regular unit irreducible Brillouin zone

    图  3  声学超材料板基本单元能带图

    Figure  3.  Band diagram of AMP unit

    图  4  建立声学超材料板样本集流程图

    Figure  4.  Workflow of establishing sample set of acoustic metamaterial plates

    图  5  正反向设计神经网络示意图

    Figure  5.  Schematic diagram of forward-reverse neural network

    图  6  正反向设计神经网络的工作流程图

    Figure  6.  Workflow of forward and inverse design based on neural network

    表  1  声学超材料板材料参数

    Table  1.   Material parameters of AMP

    参数 空气
    声速/(m·s−1) 3300 343.2
    泊松比 0.3
    密度/( kg·m−3) 7700 1.2
    杨氏模量/Pa 4.08×1010
    下载: 导出CSV

    表  2  数据集部分数据

    Table  2.   Part of data set

    a/mm b/mm c/mm d/mm 带隙上界/Hz 带隙下界/Hz
    1.5 4.0 5.0 3.5 2359.763 6466.259
    1.5 4.0 5.0 4.0 2380.481 6460.853
    2.0 1.5 2.5 1.5 1590.832 4539.679
    2.0 1.5 2.5 2.0 1602.459 4532.605
    2.5 4.0 5.0 3.5 2498.582 5767.737
    2.5 4.0 5.0 4.0 2521.416 5768.602
    3.0 1.5 2.5 1.5 1655.130 4018.305
    3.0 1.5 2.5 2.0 1667.593 4014.454
    下载: 导出CSV

    表  3  正向设计神经网络输出的带隙和有限元仿真带隙

    Table  3.   Band gaps from forward neural network model and finite element simulation

    样本 a/mm b/mm c/mm d/mm 正向设计神经网络输出/Hz 有限元仿真结果/Hz
    1 3.12 1.56 2.33 3.37 3849~1657 3842~1665
    2 1.73 3.27 3.32 2.69 5279~1950 5362~1911
    3 2.64 2.43 3.62 1.29 4979~1975 4920~1995
    4 2.25 3.75 3.75 2.15 5307~2079 5270~2084
    5 1.86 1.77 2.61 2.79 4739~1690 4717~1657
    6 3.69 2.21 1.51 3.15 3367~1421 3342~1386
    下载: 导出CSV

    表  4  反向设计神经网络计算结果

    Table  4.   Results of the reverse design neural network

    目标带隙/Hz a/mm b/mm c/mm d/mm 仿真结果/Hz
    1500~4500 2.28 3.21 2.56 3.19 1541.1~4461.3
    1500~5000 1.15 0.72 2.44 4.81 1569.2~5110.6
    2000~4500 3.74 3.16 3.27 3.31 2094.7~4440.9
    2000~6000 1.61 3.08 3.95 2.35 2047.4~5895.0
    2500~5000 3.65 1.97 4.69 3.13 2440.3~5045.2
    2500~6000 1.58 3.84 4.96 4.25 2389.0~6075.1
    下载: 导出CSV
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出版历程
  • 收稿日期:  2024-06-07
  • 网络出版日期:  2025-12-22
  • 刊出日期:  2025-09-30

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