修复扭曲的全息图数据用于声音场重建
Yang Shen1, Chuan-Xing Bi1, Xiao-Zheng Zhang1
1Institute of Sound and Vibration Research, Hefei University of Technology, 193 Tunxi Road, Hefei 230009, People's Republic of China.
The Journal of the Acoustical Society of America
|June 21, 2024
概括
这项研究引入了一种新的方法来修复扭曲的全息图数据,以准确地重建声音场. 该方法有效地识别和纠正损坏的测量,确保高准确度的声学重建.
科学领域:
- 声学和信号处理
- 计算物理 计算物理
- 数据科学数据科学数据科学
背景情况:
- 声场重建依赖于精确的声学测量.
- 扭曲或损坏的全息图数据显著降低了重建的准确性.
- 现有的方法可能会在自动错误检测和纠正方面遇到困难.
研究的目的:
- 提出和验证一个强大的方法来修复扭曲的全息图数据.
- 为了使准确的声音场重建,即使有损坏的测量.
- 开发一种用于区分和纠正测量错误的自动化方法.
主要方法:
- 一个相当的源模型代表全息图压力.
- 在使用单一价值分解的模式框架内制定.
- 贝叶斯推论用于推导测量指标和模式系数的后置分布.
主要成果:
- 对所有损坏的测量进行自动歧视.
- 精确修复扭曲的全息图压力.
- 声音场重建的准确性与使用无错误数据相比较.
结论:
- 拟议的方法有效地修复扭曲的全息图数据,用于声场重建.
- 该方法在模拟和实验验证两方面都表现出了稳健性.
- 这种技术提高了声学测量和重建的可靠性.
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