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Single and multiple sensor identification of avalanche-generated infrasound

机译:雪崩产生的次声的单传感器和多传感器识别

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The ability to identify snow avalanches as they occur is essential for aggressive avalanche management in transportation corridors and is a fundamental ingredient of avalanche forecasting. Past studies have shown that moving avalanches emit a detectable sub-audible sound signature in the low frequency infrasonic spectrum. Experimental infrasound avalanche monitoring activities conducted in the United States Rocky Mountain West clarify avalanche event identification capabilities of single sensor and multiple sensor systems. Avalanche identification performance of single sensor monitoring systems vary according to ambient noise and signal levels. While single sensor auto correlation signal processing algorithms identify avalanche activity, uncertainties (i.e. false negative identifications and false positive identifications) increase as wind noise increases, and as signal levels decrease due to increasing distance or smaller sources. Monitoring with multiple sensor systems substantially improves avalanche event identification robustness under windy and noisy conditions, while also allowing location estimates of avalanche events to be made. Avalanche event identification and localization capabilities of cross correlation and semblance multiple sensor signal processing algorithms are demonstrated via a sensor array monitoring system. Also demonstrated are avalanche identification and localization capabilities of distributed networks of infrasound monitoring systems. Garnered knowledge is being ported into near real-time prototype systems that will be operated in the Jackson Hole, Wyoming region. Prototype operation will provide performance evaluations in practical highway and recreational area settings. Reliable implementation of infrasound monitoring technology to automatically identify avalanche events requires further innovative solutions to problematic ambient wind noise and interfering signals.
机译:能够识别雪崩发生的能力对于在运输走廊中积极进行雪崩管理至关重要,并且是雪崩预测的基本要素。过去的研究表明,移动的雪崩在低频次声频谱中发出可检测到的亚听声音特征。在美国落基山西部进行的次声雪崩监测实验证明了单传感器和多传感器系统的雪崩事件识别能力。单个传感器监视系统的雪崩识别性能会根据环境噪声和信号水平而有所不同。尽管单传感器自动相关信号处理算法可以识别雪崩活动,但不确定性(即错误的负标识和错误的正标识)会随着风噪声的增加而增加,并且由于距离的增加或信号源的减小而导致信号电平的降低。使用多个传感器系统进行监视可以显着提高在大风和嘈杂条件下的雪崩事件识别能力,同时还可以对雪崩事件进行位置估计。通过传感器阵列监控系统演示了互相关和相似性的雪崩事件识别和定位功能。还演示了次声监视系统分布式网络的雪崩识别和定位功能。将获得的知识移植到将在怀俄明州杰克逊霍尔进行操作的近实时原型系统中。原型操作将在实际的高速公路和休闲区设置中提供性能评估。要可靠地实施次声监视技术来自动识别雪崩事件,就需要进一步创新的解决方案来解决有问题的环境风噪声和干扰信号。

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