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Monitoring and recognition of debris flow infrasonic signals

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Abstract

Low frequency infrasonic waves are emitted during the formation and movement of debris flows, which are detectable in a radius of several kilometers, thereby to serve as the precondition for their remote monitoring. However, false message often arises from the simple mechanics of alarms under the ambient noise interference. To improve the accuracy of infrasound monitoring for early-warning against debris flows, it is necessary to analyze the monitor information to identify in them the infrasonic signals characteristic of debris flows. Therefore, a large amount of debris flow infrasound and ambient noises have been collected from different sources for analysis to sum up their frequency spectra, sound pressures, waveforms, time duration and other correlated characteristics so as to specify the key characteristic parameters for different sound sources in completing the development of the recognition system of debris flow infrasonic signals for identifying their possible existence in the monitor signals. The recognition performance of the system has been verified by simulating tests and long-term in-situ monitoring of debris flows in Jiangjia Gully, Dongchuan, China to be of high accuracy and applicability. The recognition system can provide the local government and residents with accurate precautionary information about debris flows in preparation for disaster mitigation and minimizing the loss of life and property.

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Authors and Affiliations

  1. Key Laboratory of Mountain Hazards and Earth Surface Process, Chinese Academy of Sciences, Chengdu, 610041, China

    Dun-long Liu

  2. Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu, 610041, China

    Dun-long Liu, Xiao-peng Leng, Fang-qiang Wei, Shao-jie Zhang & Yong Hong

  3. University of Chinese Academy of Science, Beijing, 100049, China

    Dun-long Liu

  4. College of Information Science and Technology, Chengdu University of Technology, Chengdu, 610059, China

    Xiao-peng Leng

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  1. Dun-long Liu
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  2. Xiao-peng Leng
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  4. Shao-jie Zhang
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  5. Yong Hong
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Correspondence to Fang-qiang Wei.

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Liu, Dl., Leng, Xp., Wei, Fq. et al. Monitoring and recognition of debris flow infrasonic signals. J. Mt. Sci. 12, 797–815 (2015). https://doi.org/10.1007/s11629-015-3471-4

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  • DOI: https://doi.org/10.1007/s11629-015-3471-4

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