비닐온실 폭설 방재 예·경보 시스템을 위한 설하중 센서 개발과 적설 경보 기준 분석
Development of Snow Load Sensor and Analysis of Warning Criterion for Heavy Snow Disaster Prevention Alarm System in Plastic Greenhouse
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초록
As the weather changes become frequent, weather disasters are increasing, causing more damage to plastic greenhouses. Among the damage caused byvarious disasters, damage by snow to the greenhouse takes a relatively long time, so if an alarm system is properly prepared, the damage can bereduced. Existing greenhouse design standards and snow warning systems are based on snow depth. However, even in the same depth, the load onthe greenhouse varies depending on meteorological characteristics and snow density. Therefore, this study aims to secure the structural safety ofgreenhouses by developing sensors that can directly measure snow loads, and analysing the warning criteria for load using a stochastic model. Markovchain was applied to estimate the failure probability of various types of greenhouses in various regions, which let users actively cope with heavysnowfall by selecting an appropriate time to respond. Although it was hard to predict the precise snow depth or amounts, it could successfully assessthe risk of structures by directly detecting the snow load using the developed sensor.
Abstract
As the weather changes become frequent, weather disasters are increasing, causing more damage to plastic greenhouses. Among the damage caused byvarious disasters, damage by snow to the greenhouse takes a relatively long time, so if an alarm system is properly prepared, the damage can bereduced. Existing greenhouse design standards and snow warning systems are based on snow depth. However, even in the same depth, the load onthe greenhouse varies depending on meteorological characteristics and snow density. Therefore, this study aims to secure the structural safety ofgreenhouses by developing sensors that can directly measure snow loads, and analysing the warning criteria for load using a stochastic model. Markovchain was applied to estimate the failure probability of various types of greenhouses in various regions, which let users actively cope with heavysnowfall by selecting an appropriate time to respond. Although it was hard to predict the precise snow depth or amounts, it could successfully assessthe risk of structures by directly detecting the snow load using the developed sensor.
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