For geological disasters, various industrial applications of various monitoring techniques, but all existing monitoring and control of a single data flow , monitoring frequency, monitoring elements are not flexible, especially in the event of sudden disasters, such as earthquakes, sudden heavy rainfall , human activities such as coping ability, can not be implemented autonomous intelligent monitoring . This study focused on improving the status of geological disaster monitoring unidirectional passive monitoring to avoid internal monitoring time to deal with unexpected situations untimely omissions monitoring to ensure the integrity and effectiveness of the monitoring data , focusing on intelligent closed-loop self- monitoring . Select the crack surface slope of the end- displacement multi-point monitoring research project , based on flexible multi- use monitoring technology magnetostrictive displacement effects, solve complex terrain slope displacement of surface cracks effective access to data ; using intelligent objects associated technologies, Research autonomous intelligent closed-loop reverse closed loop monitoring , data analysis, implementation of self-control ; Finally, based on monitoring data , in order to change the slope surface displacement velocity, acceleration , and contextual factors , such as analysis of trends in technology and methods of early warning research , and ultimately to the slope table crack displacement of the closed-loop multi-point monitoring and trend intelligence warning, and then expand the application to geological disaster monitoring industry , to achieve regional autonomy intelligent monitoring .
针对地质灾害频发,各行业应用了大量监测技术手段,但现有各监测的数据流向与控制方式单一,监测频次、监测要素不灵活, 尤其突发性灾害事件比如地震、突发强降雨、人为活动等应对能力差,不能实施自主智能监测。本研究着眼于改善地质灾害监测技术单向、被动监测的现状,避免监测时间内因突发情况应对不及时等漏项监测,确保监测数据的完整性与有效性,重点研究实现闭环自主智能监测。选取边坡地表裂缝位移多点监测为本项目研究的落脚点,利用基于磁致伸缩效应的柔性多点位移监测技术,解决边坡复杂地形的地表裂缝位移数据有效获取;利用智能物联技术,研究闭环自主智能监测的反向闭环、数据分析、自主控制的实现方法;最后根据监测数据,以边坡地表位移变化速度、加速度及背景因素等分析结果,研究趋势预警的技术方法,最终实现边坡地表多点裂缝位移的闭环智能监测与趋势预警,进而拓展应用到地质灾害监测行业,实现区域性的自主智能监测。
通过项目的实施,设计了基于雨量、裂缝位移、滑动面含水率等多要素的智能监测模型,实现根据雨量、位移量、滑动速度、加速度以及含水率变化趋势自主选择监测频次的动态闭环监测,避免了重大监测要素变化期间的漏项监测,开发了一套适用于边坡工程位移变形的智能化监测技术方法和设备,具有一定的科学意义和较好的应用前景,能够为我国地质灾害防灾减灾提供技术支撑。
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数据更新时间:2023-05-31
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