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Blast Quantification Using Hopkinson Pressure Bars
Published on: July 5, 2016
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智能手机和超声波麦克风数据的比较来自燃油空气爆炸物和高爆炸物
S K Takazawa1, S K Popenhagen1, L A Ocampo Giraldo2
1Hawai ´ i Institute of Geophysics and Planetology, University of Hawai ´ i, Mānoa, Hawai ´ i 96740, USA.
The Journal of the Acoustical Society of America
|September 4, 2024
概括
智能手机网络为检测较小爆炸提供了灵活,负担得起的替代方案. 虽然智能手机的音频在超声波频率上有局限性,但它们的传感器数据显示出对爆炸识别和定位的承诺.
科学领域:
- 地质物理学 地质物理学
- 声学 声学 在声学方面
- 传感器网络 传感器网络
背景情况:
- 传统的超声波网络对于大型爆炸是有效的,但对于较小的事件是有限的.
- 越来越多的人对在脆弱区域附近检测较小爆炸的兴趣增加,需要更密集的传感器网络.
- 智能手机网络提供了一个负担得起的,灵活的替代传统的超声波阵列.
研究的目的:
- 评估使用智能手机网络用于爆炸检测和描述的可行性.
- 为了比较智能手机和传统的超声波麦克风捕获的爆炸声波形状.
- 探索使用智能手机传感器数据进行爆炸信号分析的新方法.
主要方法:
- 部署了一个智能手机网络,并配备了一个超声波麦克风,以捕获爆炸信号.
- 在时间,频率和时间频率领域分析了爆炸波形.
- 开发并介绍了一种使用智能手机传感器相对声幅的源定位方法.
主要成果:
- 由于设备的局限性,智能手机的声波形式显示在超声波频率 (<20 Hz) 上有过.
- 智能手机数据很难使用传统的爆炸特征方法 (例如,峰值超压).
- 时间频率表示和多传感器输入的相似性显示了爆炸识别的潜力.
结论:
- 智能手机网络不适合对超声波爆炸信号的直接波形分析.
- 智能手机网络的潜力在于互补的传感器数据和用于爆炸检测的先进信号处理.
- 对利用相对声幅和多传感器融合的进一步研究可以提高爆炸局部化能力.
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