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    Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/64827

    Title: 火炎山土石流之現地監測與影像及地聲分析
    Authors: 楊祥霖;YANG,HSIANG-LIN
    Contributors: 土木工程學系
    Keywords: 土石流流動形態;地聲;次聲;快速傅利葉;希爾伯特-黃轉換;behavior of debris;geophones;infrasound;Fast Fourier fransform;Hilbert-Huang transform
    Date: 2014-07-29
    Issue Date: 2014-10-15 14:28:42 (UTC+8)
    Publisher: 國立中央大學
    Abstract: 山區溪溝發生土石流時常造成嚴重之坡地災害,其土石流具速度快、埋深大和粗顆粒多之特性而產生強大破壞力。由探討土石流的流動形態,內部粒徑及流速可分析其對結構物的撞擊力與有效的防治工法配置,並進行危險區域的分級,以降低災害損失程度。本研究以地聲及次聲監測系統配合現場架設之影像系統,將土石流形態分類並與地聲訊號相互比較驗證,經由不同流動形態之土石流流量與地聲訊號比對以分析其相關性。本文主要研究2013/5/22滯留鋒面降雨引起之火炎山土石流事件。
    由監測資料顯示次聲之因素主要為風、雨聲,其特徵頻率為5Hz以下。地表逕流與土石流訊號分析得知地聲訊號反應較次聲良好,地表逕流頻譜的主頻分佈會比土石流頻譜高,本次事件地表逕流頻譜特性介於30 ~ 45Hz;土石流頻譜特性則在10 ~ 32Hz間。且藉由影像系統驗證雙聲系統,得知藉由地聲所測得之反應,分析頻譜以及判定訊號反應之延時,以作為土石流預警系統之根據。
    ;Debris flows from mountainous gulley often cause serious slope disasters, due to the destructive high velocities, larger buried depth and great number of coarse particles. By analyzing the debris flow pattern, its internal particle size and flow speed, we can analyze its impact force on buildings and set up effective prevention and control methods and classify the risk zone to reduce loss. The research employs geophones and acoustic sensors with the CCD-image system built on site to classify the behavior of debris and compare them with geophone signals. At last, it compares and analyzes the correlation between various debris flows and geophone signals.
    This paper studies the rainfall-induced debris-flow event at the Houyenshan on May 22, 2013. The current infrasound signals are mainly influenced by winds and rain noises, whose characteristic frequencies are less than 5Hz. Through analyzing signals of surface runoff and debris flows, it can find out that geophone signals are better than infrasound signals for debris-flow monitoring system . Frequency distribution of surface runoff is higher than that of debris-flow the frequency spectrum of surface runoffs are 30 to 45Hz; and the frequency spectrum of debris flows are 10 to 32Hz. Through testing both geophone and acoustic systems by CCD-image system, it can be concluded that the signals of geophone sensors, by frequency spectrum analysis and judging signal duration and their amplitudes can be regarded as the basis of debris-flow warning system.
    Appears in Collections:[土木工程研究所] 博碩士論文

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