使用SE-ResNet在海冰中的剪切和纵向声波传播参数的反转
Jin Bai1, Yi Liu2, Xuegang Zhang1
1Science and Technology on Underwater Test Control Laboratory, Dalian 116000, China.
Sensors (Basel, Switzerland)
|September 27, 2025
概括
由于海冰的复杂结构,准确测量海冰的剪波速度至关重要. 本研究引入了一种使用先进建模和测量技术的综合方法,以提高海冰中声波传播的预测准确性.
科学领域:
- 地质物理学 地质物理学
- 声学 声学 在声学方面
- 材料科学 材料科学 材料科学
背景情况:
- 了解海冰中的声波传播对于科学研究至关重要.
- 在海冰中切割波速度的测量显示,由于复杂的内部结构,与现有模型存在重大差异.
- 海冰的微观结构,包括气泡和晶体的方向,影响剪切波的速度.
研究的目的:
- 开发一种综合方法,用于准确地预测海冰中的剪波速度.
- 解决海冰物理性质的测量和建模方面的挑战.
- 为了提高在海冰中声波速度预测的准确性.
主要方法:
- 开发了一种用于控制海冰层生成的实验室方法.
- 增强的剪波速度测量设备,提高了准确性和便携性.
- 使用深度残余神经网络与SE-ResNet用于预测纵向和横向波速.
主要成果:
- 实验室生成的海冰层与测量的物理特性密切匹配.
- 改进的测量设备在恶劣的极地环境中达到1%以上的精度.
- 与ANN相比,SE-ResNet模型提高了分别24.87%和39.59%的剪切和纵向波速预测准确度.
结论:
- 综合方法显著提高了海冰声波速度预测的准确性.
- 新的SE-ResNet模型在预测有限数据的波速方面表现出卓越的性能.
- 这项研究提供了一种更可靠的方法来描述海冰的物理性质.
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