软土环境下基于MEMS技术超长线状地下结构性能智能感知机理与方法

Rail transportation is like a lifeline of a city's transportation. The structure health service of its tunnel is certainly important for the normal operation of the city, which is increasingly widespread concerned. Today, it is required to sense the tunnel structure safety in the entire subway network on full coverage and full time, just like the nerve endings of human, to perceive structural performance. Subway tunnel of the soft soil area compared with the upper structure, the structure damage is not only affected by soil displacement and groundwater, but also affected by the vibration of high-density metro run, which induce that positions of structural damage are difficultly judged in advance, so we urgently need economic and efficient means to monitor the structure performance on full coverage. These new demands are almost impossible to achieve for the traditional monitoring methods. Aimed the health service issue of the subway tunnel structure of the soft soil area, the project firstly researched the suitable wireless sensor network topology model for the subway tunnel long linear structure, secondly research accurate fast, easy IntelliSense parameters and node layout optimization methods to sense the performance of the tunnel structure and finally research damage identification methods for performance self-sensing of the tunnel structure based the MEMS technology. The project is establishing real-time sense theories and methods for the structural performance of urban rail transit tunnel in soft soil environment, in order to break through the intellectual sense problem for rail transport tunnel structure in channel clutter and high electromagnetic compatibility environment, and has valuable application prospects.

轨道交通作为城市的交通命脉，其隧道结构健康服役对于城市正常运转至关重要，日益引起广泛的关注，需要对整个地铁网络隧道结构全覆盖与全天候监测，像神经末梢一样，时刻感知结构性能。软土地区地铁隧道与上部结构相比，结构性能损伤与土体位移及地下水密切相关，同时受高密度地铁循环振动影响，结构损伤点位置复杂难判，迫切需要采用经济，高效的监测手段与方法，全覆盖智能感知隧道结构性能，这些新需求对于传统监测手段几乎是不可能实现的。本项目针对软土地区地铁隧道结构中存在的健康服役问题，研究适合于地铁隧道超长线状结构无线传感网络拓扑结构模型；研究适合隧道结构性能准确、快速、简便的智能感知参数与节点布置优化方法；研究基于MEMS技术的隧道结构性能自感知损伤识别方法。以期建立起软土环境下城市轨道交通隧道结构性能实时感知理论与方法，突破轨道交通隧道结构信道杂乱和电磁兼容性要求高条件下的智慧感知难题，具有广泛的应用前景。

轨道交通作为城市的交通命脉，其隧道结构健康服役对于城市正常运转至关重要，日益引起广泛的关注，需要对整个地铁网络隧道结构全覆盖与全天候监测，像神经末梢一样，时刻感知结构性能。软土地区地铁隧道与上部结构相比，结构性能损伤与土体位移及地下水密切相关，同时受高密度地铁循环振动影响，结构损伤点位置复杂难判，迫切需要采用经济，高效的监测手段与方法，全覆盖智能感知隧道结构性能，这些新需求对于传统监测手段几乎是不可能实现的。本项目针对软土地区地铁隧道结构中存在的健康服役问题，研究适合于地铁隧道超长线状结构无线传感网络拓扑结构模型；研究适合隧道结构性能准确、快速、简便的智能感知参数与节点布置优化方法；研究基于MEMS技术的隧道结构性能自感知损伤识别方法。建立了软土环境下城市轨道交通隧道结构性能实时感知理论与方法，突破了轨道交通隧道结构信道杂乱和电磁兼容性要求高条件下的智慧感知难题，具有广泛的应用前景。