無線傾度感測網路（WSN）用於邊坡環境變異的適用性研究

Applicability Study of Wireless Tilting Sensor Network with Slope Environmental Variations

10.6840/cycu201300827

翁竣鴻

無線感測網路 ； 傾度計 ； 坡地監測 ； Slop monitoring ； Wireless Sensor Network ； Incline Meter

中原大學土木工程學系學位論文

2013年

碩士

張達德

繁體中文

台灣多險峻山川，且位處每年太平洋颱風可能行經之路徑範圍，因此常發生如土石流、順向坡滑動、落石、斷橋及道路崩塌等土石災害，均使土建防災的專業人員受到了強烈的挑戰與衝擊。過去傳統的土建監測設備，若採用全自動化監測，則面臨系統規劃龐大、價格昂貴、後續維護困難、系統之耐久性、即時性、全自動化性、全面佈設性等問題，遭遇到了很大的瓶頸。 無線感測網路（Wireless Sensor Network, WSN）為一種具有感知能力、計算能力和通信能力的微型感測器。本研究應用無線感測網路結合加速度規所建構的WSN傾度計，以新思維的表徵式變異提前掌握邊坡滑動訊息，並結合遠端管理平台，清楚呈現歷時傾度數據的趨勢。 此系統已於國道三號3.1公里處上、下邊坡運作近一年，系統運作大致穩定，但部分感測器的傾度數據產生異常跳動，因此本研究期望探討數據異常的原因，針對外在環境因素對傾度計造成的影響進行相關室內試驗及現地數據比對，對WSN用於邊坡傾度預警監測提出改善與建議。

Taiwan has a lot of steep mountains and located at the path of the annual Pacific typhoon , so will occur mudflows, the dip slope sliding, falling rocks, broken bridge ,and road collapses ,etc. As a result , the civil disaster prevention professionals under the intense challenges and shocks . If the traditional monitoring systems are changed to fully automated monitoring systems ,it will be facing a lot of troubles such as huge system's planning, expensive, difficult to maintain the system's durability, real-time, fully automated, comprehensive layout and other matter.　 Wireless Sensor Network is kind of microsensor that has perception, calculation and communication capabilities. This study will build a WSN's Incline Meter that's combine with Wireless Sensor Networks and accelerometer. We try a new thinking of ground surface variation to control landslide information and combine with Remote management platform. Then, we can clearly display which lasted tilt trends in the data. The WSN system has operated mostly stable at National Highway No.3 3.1K upper and lower slop for recently year. However , some WSN's Incline meter data generated abnormal beating so this study expects to investigate the cause of abnormal data , and focus on external environmental factors affect tilt meter in contrast to indoor experiment and the related situ data. Then, putting forward Wireless Tilting Sensor Network early monitoring warning of slope.

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