基于电磁-声互协阵列的地下围压空间水文广域监测

Concealment and time-variation of groundwater in confining pressure environment lead to wide-area monitoring problem, and it presents a serious challenge to the current technology. Through recording the features of the ambient acoustic energy inspired from music and exploring the space-time collaboration mechanism of electromagnetic-acoustic, a wide area monitoring model for hydrologic in underground space with confining pressure is proposed based on electromagnetic-acoustic cooperation array. First, the features of the ambient acoustic energy are mapped to the music memory space, and a five-line memory spectrum model of energy is proposed for pattern recognition of hydro-acoustic energy. Second, a collaborative model is established which contains the acoustic emission with self-waking ability and the excited time domain reflectometry of electromagnetic wave. The model adopts the collaborative mechanisms of passive detection and active detection, area measurement and point measurement, to achieve controlling the system energy consumption while ensuring the real-time feature. Third, the electromagnetic-acoustic array for hydrological monitoring is established. Then a bored sensor hierarchical layout architecture and a visualization reel planning method for monitoring space are proposed. A self-organizing distributed monitoring system is formed afterwards. Finally, a hydrological memory sensing and causal reasoning model is established to form an integration mechanism for adapting hydrological time-varying signal, intelligent controlling the scale of the measurement data, reasoning and predicting the potential water damage. The proposed model and the device in this project will provide the new theories and key technologies for early warning and disaster prevention of hydrologic in underground space, thus it has important scientific significance and application prospect.

地下水文在围压环境下的隐蔽性、时变性引出广域监测难题，对当前技术提出严峻挑战。本项目通过探索环境声能量特征乐谱化记忆以及电磁-声时空协作机理，提出基于电磁-声互协阵列的地下围压空间水文广域监测模型。该模型将地下水文环境声能量特征映射到乐谱记忆空间，提出以能量五线记忆谱实现水文声能量模式识别新思路。进而构建自唤醒声发射及受激电磁波时域反射协同模型，以被动探测和主动探测、区域测量和点测量的协同机制实现兼顾实时性的系统能耗控制。在此基础上构建电磁-声水文监测阵列，提出钻埋式传感器分层布设架构和卷轴式监测空间可视规划方法，形成自组织分布式监测体系。最后建立水文记忆感测因果推理模型，构建监测系统对水文时变信号自适应、对测量数据规模智能控制、对潜在水害推理预测的信息综合处理机制。项目构建的模型及装置将为地下空间水文监测提供防灾预警的新理论方法和关键技术，具有重要的科学意义和应用价值。

地下水文在围压环境下的隐蔽性、时变性引出广域监测难题，对当前技术提出挑战。本项目通过探索环境声能量特征乐谱化记忆以及电磁-声时空协作机理，构建了基于电磁-声互协阵列的地下围压空间水文广域监测方法。. 项目首先建立了声发射能量五线记忆谱模型，将声发射能量特征映射到乐谱记忆空间，通过对记忆音符模式识别分析岩土含水状态，实现对不同含水率岩石受压变形激发声发射的信号变换及含水率渐变状态下的水文声场能量模式识别。. 项目进而研制了系列化仪器板卡，研究了环境声能量的低功耗捕获采集方法，建立了声发射监测系统自唤醒工作模式。研究了电磁波时/频域反射长周期监测与激发监测共存方法，建立了被动探测和主动探测协同机制。对声发射信号的特征参量进行研究进而反演声发射源的信息，探索了声发射源的二维平面定位方法。结合CT裂纹特征的量化指标和声发射信号的变化规律量化印证了岩石含水率与声发射信号之间的关联，确定了含水率与损伤程度的匹配关系。. 此后，项目设计了传感器分层布设监测架构，搭建了电磁-声分布式水文监测阵列，基于模糊数学理论研究了监测数据信息融合和地下围压空间潜在水害的空间定位方法。设计了声发射参数的自动筛选方法，建立了结构损伤定位结果的视觉警示机制。. 最后，为完成结构健康监测中破坏源定位、损伤等级评估和海量数据规模管理，项目从记忆推理功能出发，建立了基于拟人记忆和因果推理的结构损伤定位与评估机制。通过模拟记忆推理过程，将监测数据处理与损伤评估分为多个映射区，在短时记忆区完成数据约简，在长期记忆区中提出支持度指标，完成损伤源推理定位。基于信息熵与概率统计理论，综合不确定性理论提出结构损伤信息熵向量，结合损伤力学推导提出疲劳度指标，完成岩样含水损伤评估。. 项目构建的模型及装置将为地下空间水文监测提供防灾预警的新理论方法和关键技术，具有重要的科学意义和应用价值。