Early Warning System and Method of Landslides using stress change in soil by rainfall infiltration

The present invention is a landslide forecasting and warning system performed by a computer with a control server and a database connected through a network, wherein the control server includes: a first monitoring unit (100) which performs landslide forecasting by comparing soil stress and shear str...

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Bibliographic Details
Main Author LEE, KWANG WOO
Format Patent
LanguageEnglish
Korean
Published 04.04.2023
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Summary:The present invention is a landslide forecasting and warning system performed by a computer with a control server and a database connected through a network, wherein the control server includes: a first monitoring unit (100) which performs landslide forecasting by comparing soil stress and shear strength calculated through ground material property information obtained from soil samples collected in a target area and rainfall forecast information in the target area; and a second monitoring unit (200) which, after receiving an operation signal from the first monitoring unit (100), calculates the soil stress through the ground material property information measured in real time by a field sensor, and when an inflection point of the soil stress occurs, compares the soil stress by the field sensor and the shear strength to forecast and issue a warning about rainfall infiltration. The first monitoring unit conducts primary landslide monitoring through rainfall forecast values, and the second monitoring unit conducts secondary landslide monitoring through real-time measurements from field sensors, utilizing the field sensor when necessary. 본 발명은 제어서버와 데이터베이스가 네트워크로 연결된 컴퓨터에 의해 수행되는 산사태 예ㆍ경보 시스템으로서, 제어서버는 대상지역에서 수집된 토양시료에서 취득한 지반물성정보 및 대상 지역의 강수량예측정보를 통해 산정된 지중응력과 전단강도를 비교하여 산사태 예보를 수행하는 제1 모니터링부(100); 및 제1 모니터링부(100)로부터 작동신호를 받은후, 현장센서에서 실시간으로 측정된 지반물성정보를 통해 지중응력을 산정하고, 지중응력의 변곡점이 발생되면, 현장센서에 의한 지중응력과 상기 전단강도를 비교하여 산사태 예ㆍ경보를 하는 제2 모니터링부(200)를 포함하는 것을 특징으로 하는 강우침투에 의한 지반의 응력변화를 이용한 산사태 예ㆍ경보 시스템이다.
Bibliography:Application Number: KR20210127902