CN103453936A - Debris flow disaster early monitoring system based on internet of things - Google Patents

Abstract

Translated fromChinese

本发明公开了一种基于物联网的泥石流临灾监测系统，包括物联网云端服务器，以及与云端服务器通信连接的气象中心，所述云端服务器通信连接无线传感网，所述无线传感网包括网络节点、土壤水分传感器、土壤内部压力传感器以及定位装置，所述土壤水分传感器、土壤内部压力传感器和定位装置检测的数据均通过网络节点传输至云端服务器。通过需要监控泥石流的地区布设无线传感网，通过无线传感网中的土壤水分传感器、土壤内部压力传感器对土壤的检测，以及定位装置对土壤移动位移的检测，以及结合气象中心采集的周围的气象数据，经过云端处理器的计算和模拟，达到了对泥石流灾害进行，实时监控且精确度高的目的。

The invention discloses a debris flow disaster monitoring system based on the Internet of Things, which includes a cloud server of the Internet of Things and a meteorological center connected to the cloud server in communication, the cloud server is connected to a wireless sensor network through communication, and the wireless sensor network includes The network node, the soil moisture sensor, the soil internal pressure sensor and the positioning device, the data detected by the soil moisture sensor, the soil internal pressure sensor and the positioning device are all transmitted to the cloud server through the network node. Deploy wireless sensor networks in areas where debris flow needs to be monitored, detect the soil through the soil moisture sensor in the wireless sensor network, the soil internal pressure sensor, and the detection of soil movement and displacement by the positioning device, and combine the surrounding data collected by the meteorological center Meteorological data, through the calculation and simulation of cloud processors, achieves the purpose of real-time monitoring of debris flow disasters with high accuracy.

Description

Translated fromChinese

基于物联网的泥石流临灾监测系统Debris Flow Immediate Disaster Monitoring System Based on Internet of Things

技术领域technical field

本发明涉及泥石流检测领域，具体地，涉及一种基于物联网的泥石流临灾监测系统。 The invention relates to the field of mud-rock flow detection, in particular to a mud-rock flow disaster monitoring system based on the Internet of Things. the

背景技术Background technique

目前，物联网的出现，实现了全球亿万种物品之间的互连，将不同行业、不同地域、不同应用、不同领域的物理实体按其内在关系紧密地关联在一起。作为崭新的综合性信息系统，物联网并不是单纯的，它包括信息的感知、传输、处理决策、服务等多个方面，呈现出自身显著的特点；物联网是一个由云端组成的一个庞大网络，随着传感器网络大规模部署，各种终端就像蓝海一样，分布到各种各样基础设施上收集信息，在通过各种网络将这些信息发送到云端进行计算和处理，经过计算和处理的信息最后到了应用层为不同的领域各种各样行的支撑服务。 At present, the emergence of the Internet of Things has realized the interconnection between hundreds of millions of items around the world, and closely related physical entities in different industries, different regions, different applications, and different fields according to their intrinsic relationships. As a brand-new comprehensive information system, the Internet of Things is not simple, it includes information perception, transmission, processing decision-making, service and other aspects, showing its own remarkable characteristics; the Internet of Things is a huge network composed of clouds , with the large-scale deployment of sensor networks, various terminals are distributed to various infrastructures to collect information like a blue ocean, and these information are sent to the cloud through various networks for calculation and processing. After calculation and processing The information finally arrives at the application layer to provide support services for various fields in different fields. the

物联网的关键核心技术就是无线传感器网络（Wireless Sensor Network，WSN）技术，该是二十一世纪最有影响力的二十一项技术之一、改变世界的十大技术之一和全球未来的三大高科技之一。这些美誉的接踵而至为无线传感器网络开启了广阔的发展前景和应用空间。 The key core technology of the Internet of Things is the Wireless Sensor Network (WSN) technology, which is one of the twenty-one most influential technologies in the 21st century, one of the top ten technologies that change the world, and the future of the world. One of the three high-tech. The succession of these reputations has opened up broad development prospects and application space for wireless sensor networks. the

高效的数据融合、云计算等先进技术能够实现海量数据存储与智能高效决策，与无线传感器网络技术的有机结合将目前物联网的应用得到了更大的扩展，不仅仅限于农业，医疗，更适用于交通，环境等广泛应用，将逐步实现真正的“万物互联互通”。 Efficient data fusion, cloud computing and other advanced technologies can realize massive data storage and intelligent and efficient decision-making, and the organic combination with wireless sensor network technology has greatly expanded the current application of the Internet of Things, not only limited to agriculture and medical care, but also more applicable It is widely used in transportation, environment, etc., and will gradually realize the real "interconnection of all things". the

我国是世界上泥石流灾害最为严重的国家之一，甘肃省尤为严重，特别是2010年发生的甘肃舟曲特大泥石流灾害造成了巨大的人员伤亡及经济损失。为了有效预防滑坡和泥石流，政府相关部门相继采取了多项措施，不断健全泥石流监测预警技术，并取得了一些成果。 my country is one of the countries with the most serious debris flow disasters in the world, especially in Gansu Province, especially the large debris flow disaster in Zhouqu, Gansu Province in 2010, which caused huge casualties and economic losses. In order to effectively prevent landslides and mudslides, relevant government departments have taken a number of measures to continuously improve the monitoring and early warning technology of mudslides, and have achieved some results. the

在泥石流监测方面，国内科研人员已经研发出了一些针对泥石流的监测预警，目前国内已经获得批准的泥石流的监测预警技术繁多如下： In terms of debris flow monitoring, domestic researchers have developed some monitoring and early warning systems for debris flows. At present, there are a variety of monitoring and early warning technologies for debris flows that have been approved in China:

专利号为CN200820185015，专利名称用于公路泥石流灾害自动发现与报警的交通监控设备，公开了用于公路泥石流灾害自动发现与报警的交通监控设备，其特征是：用于监控泥石流易发山体区域的交通监控摄像机与工业控制计算机相互连接，实时监控泥石流易发区域的山体，工业控制计算机连续接收、分析山体图像信息， 一旦发生泥石流灾害，工业控制计算机向交通信号灯发送红灯命令，阻止公路双向行驶的机动车通行，同时向公路管理部门发送报警信号。The patent number is CN200820185015, and the patent name is traffic monitoring equipment for automatic discovery and alarm of highway debris flow disasters. It discloses traffic monitoring equipment for automatic discovery and alarm of highway debris flow disasters. It is characterized in that it is used for monitoring debris flow prone mountain areas The traffic monitoring camera and the industrial control computer are connected to each other to monitor the mountains in areas prone to mudslides in real time. The industrial control computer continuously receives and analyzes the image information of the mountains. Once a mudslide disaster occurs, the industrial control computer sends a red light command to the traffic lights to prevent two-way driving on the road Motor vehicles pass through, and at the same time send an alarm signal to the highway management department.

该监测报警系统具备实时环境的图像监控与数据接收，包含图像监控模块、图像分析模块以及通信模块四大模块。其中图像监控可获得实时图像，也可将监控图像传回控制中心，并可根据图像信息通过控制交通信号灯来控制公路的交通状况。但此系统仅能进行山体的图像监控，无法对山体其它数据进行具体监测，比如土壤含水量，土壤位移等等。也无法对泥石流进行预测继而进行预警。此系统仅适用与山体部分路段的泥石流监控并不适用城市周边的泥石流监测预警。 The monitoring and alarm system has real-time environment image monitoring and data reception, including four modules: image monitoring module, image analysis module and communication module. Among them, the image monitoring can obtain real-time images, and can also transmit the monitoring images back to the control center, and can control the traffic conditions of the highway by controlling the traffic lights according to the image information. However, this system can only monitor the image of the mountain, and cannot monitor other data of the mountain, such as soil moisture content, soil displacement and so on. It is also impossible to predict and then give early warning to mudslides. This system is only applicable to the monitoring of debris flow in some sections of the mountain and not applicable to the monitoring and early warning of debris flow around the city. the

专利号CN1996054，名称为基于全方位视觉的泥石流预警预报装置主要由雨量检测单元、泥石流发生检测单元、雨量雨强计算单元、泥石流相关水文气象历史记录记忆单元、泥石流预警预报单元、统计预警预报模型、泥石流预警预报信息发布单元等构成；根据所计算得到的10分钟雨强、一小时雨强、实效雨量作为状态输入，通过统计预警预报模型判断在该状态条件下发生泥石流的概率以及不发生泥石流的概率以及泥石流灾害的严重性和紧急程度；将判断结果用网络及其他各种手段及时发布给下游的灾害危险区的居民，使居民可以及时得到预警信息，从而可以提前采取预防措施回避损失，减轻泥石流的灾害。 Patent No. CN1996054, titled Debris Flow Early Warning and Forecasting Device Based on Omnidirectional Vision Mainly consists of a rainfall detection unit, a debris flow occurrence detection unit, a rainfall intensity calculation unit, a debris flow-related hydrometeorological historical record memory unit, a debris flow early warning and forecasting unit, and a statistical early warning and forecasting model , Debris flow early warning and forecasting information release unit, etc.; according to the calculated 10-minute rain intensity, one-hour rain intensity, and actual rainfall as the state input, the probability of occurrence of debris flow and the absence of debris flow under the state conditions are judged through the statistical early warning and forecasting model The probability of the disaster and the severity and urgency of the debris flow disaster; the judgment results are released to the residents in the downstream disaster risk area in time through the network and other various means, so that the residents can get early warning information in time, so that they can take preventive measures in advance to avoid losses. Mitigate the disaster of mudslides. the

预报装置包括用于监视待测山体和雨量收集装置水位的全方位视觉传感器、雨量收集装置和用于根据视频信号进行灾害检测的微处理器，此装置可通过降雨量的监测根据泥石流预警模型判断该条件下是否发生泥石流的概率以及泥石流灾害的严重性和紧急程度，但因为只能监测降雨量因此仅适用于泥石流的中长期监测，并不能适用于泥石流的短期监测预警，不具备预测精确度高，预警实时性的特点。 The forecasting device includes an omnidirectional visual sensor for monitoring the water level of the mountain to be measured and the rain collection device, a rain collection device and a microprocessor for disaster detection based on the video signal. This device can be judged according to the debris flow early warning model through the rainfall monitoring The probability of debris flow occurring under these conditions and the severity and urgency of debris flow disasters, but because it can only monitor rainfall, it is only suitable for medium and long-term monitoring of debris flows, not suitable for short-term monitoring and early warning of debris flows, and does not have prediction accuracy. High, the characteristics of real-time early warning. the

公开号CN102542731A，名称为泥石流地声监测报警装置公开了一种泥石流地声监测报警装置，包括设置在被监测现场且用于测试现场岩土体振动强度的探头，探头包括壳体和设置在壳体内部的曲线形支架，曲线形支架一端固定在壳体内壁上，曲线形支架另一端固定连接振子，曲线形支架内侧相对的两个面上分别设置有多个变形齿一和多个变形齿二，变形齿一与变形齿二之间呈交错对应布设，变形齿一与变形齿二的头部之间形成曲线形通道，曲线形通道内部穿设有信号光纤，信号光纤的两端中至少有一端连接测试单元，测试单元还与处理单元相接，处理单元还与声光报警装置相接。 Publication No. CN102542731A, titled Debris Flow Geoacoustic Monitoring and Alarming Device, discloses a debris flow geoacoustic monitoring and alarming device, including a probe installed at the site to be monitored and used to test the vibration strength of rock and soil at the site. A curved bracket inside the body, one end of the curved bracket is fixed on the inner wall of the housing, the other end of the curved bracket is fixedly connected to the vibrator, and a plurality of deformed teeth and a plurality of deformed teeth are respectively arranged on the two opposite surfaces inside the curved bracket 2. Deformed teeth 1 and deformed teeth 2 are arranged in a staggered manner. A curved channel is formed between the heads of deformed teeth 1 and 2. A signal optical fiber is threaded inside the curved channel. At least one of the two ends of the signal optical fiber One end is connected to the test unit, the test unit is also connected to the processing unit, and the processing unit is also connected to the sound and light alarm device. the

泥石流报警装置主要用来监测泥石流发生过程中所产生的地声，该装置结构设计合理、成本低且使用灵活，同时适应性强，能有效监测泥石流的产生、运动中所发出的地声信号。但是不具备监测信号的远程传输和发送功能，使该设备的应用场合受到了一定的限制。 The debris flow alarm device is mainly used to monitor the ground sound generated during the occurrence of debris flow. The device has a reasonable structure design, low cost, flexible use, and strong adaptability. It can effectively monitor the generation of debris flow and the ground sound signal during movement. However, it does not have the function of remote transmission and sending of monitoring signals, which limits the application of the device to a certain extent. the

公开号：CN102271245A，名称为泥石流视频监测3G网络传输装置公开了一种泥石流视频监测3G网络传输装置。所述装置包括数字化摄像机和网络传输主机，其中：所述数字化摄像机包括视频采集模块、核心处理器和网卡模块，所述视频采集模块利用摄像头采集模拟视频信号并转换为数字信号，所述核心处理器压缩处理所述数字信号，并通过所述网卡模块将处理后的压缩信号输出到所述网络传输主机；所述网络传输主机包括网卡模块、处理器模块和3G传输模块，所述网卡模块接收所述数字化摄像机发送来的压缩视频信号，并通过3G传输模块利用3G网络将压缩视频信号发送到异地进行存储与查看。 Publication number: CN102271245A, titled 3G network transmission device for debris flow video monitoring, discloses a 3G network transmission device for debris flow video monitoring. The device includes a digital camera and a network transmission host, wherein: the digital camera includes a video acquisition module, a core processor and a network card module, the video acquisition module utilizes a camera to collect analog video signals and converts them into digital signals, and the core processing The device compresses and processes the digital signal, and outputs the processed compressed signal to the network transmission host through the network card module; the network transmission host includes a network card module, a processor module and a 3G transmission module, and the network card module receives The compressed video signal sent by the digitized camera is sent to a different place for storage and viewing through the 3G network through the 3G transmission module. the

泥石流视频监测3G网络传输装置中，数字化摄像机和传输主机相互配合，能够在3G网络覆盖的地区进行无人值守的实时监测工作，通过互联网远程实时查看和存储现场的图像，在泥石流发生时能够进行实时报警。但是在一些偏远山沟中，由于交流电力供应受限，不能采用这种装置对泥石流进行有效的监测。 In the 3G network transmission device for debris flow video monitoring, the digital camera and the transmission host cooperate with each other to carry out unattended real-time monitoring work in the area covered by the 3G network, remotely view and store the on-site images in real time through the Internet, and perform real-time monitoring when the debris flow occurs. Real-time alarm. However, in some remote mountain valleys, due to the limited AC power supply, this device cannot be used to effectively monitor debris flow. the

公开号，CN202120410U ，名称为多通道泥石流断线监测预警装置公开了一种多通道泥石流断线监测预警装置，所述预警装置包括若干断线、监测采集点及监测站点；所述断线两端固定于泥石流沟道的断面两侧壁并与所述监测采集点形成闭合电路；所述监测采集点包括一GPRS数据采集模块，所述数据采集模块和监测站点无线连接。 Publication number, CN202120410U, titled multi-channel debris flow disconnection monitoring and early warning device discloses a multi-channel debris flow disconnection monitoring and early warning device, the early warning device includes a number of broken lines, monitoring collection points and monitoring stations; It is fixed on the side walls of the section of the debris flow channel and forms a closed circuit with the monitoring collection point; the monitoring collection point includes a GPRS data collection module, and the data collection module is wirelessly connected to the monitoring station. the

针对我国普遍存在的非均质泥石流，通过严密的理论推导求出泥石流泥位阈值，具有高度的科学性及实践性，同时泥位阈值的计算对于泥石流淹没成灾范围的划定很有意义，该实用新型为山洪泥石流灾害分级监测预警系统的建立提供了科学依据。但是该监测预警装置具有高成本的缺点，首先需要在泥石流高发区域部署相应的监测设备和器件，且需要一定数量的监测设备，网络部署成本较高。 In view of the ubiquitous heterogeneous debris flow in our country, it is highly scientific and practical to calculate the mud level threshold of debris flow through rigorous theoretical derivation. The utility model provides a scientific basis for the establishment of a classified monitoring and early warning system for mountain torrent and debris flow disasters. However, the monitoring and early warning device has the disadvantage of high cost. First, corresponding monitoring equipment and devices need to be deployed in areas with high incidence of debris flow, and a certain number of monitoring equipment is required, and the network deployment cost is relatively high. the

公开号：CN202903327U，名称为一种泥石流地声监测装置公开了一种泥石流地声监测装置。针对现有泥石流地声参数检测仪存在无法实现空间三轴震动强度值同时监测的缺陷，本发明提供了一种能够更准确获取泥石流爆发过程中地声数据的泥石流检测仪。该泥石流地声监测装置包括依次联接的监测端、中心端、控制端；其中，监测端是地声信号检测设备，采用MEMS三轴数字加速度计芯片作为传感元件，中心端是控制端与监测端之间的信号传输装置，控制端是地声信号处理与控制指令操作装置。本发明还提供一种利用上述泥石流地声监测装置实现的泥石流龙头流速测量装置。 Publication number: CN202903327U, titled as a kind of debris flow geoacoustic monitoring device discloses a debris flow geoacoustic monitoring device. In view of the defect that existing debris flow geoacoustic parameter detectors cannot realize simultaneous monitoring of spatial three-axis vibration intensity values, the present invention provides a debris flow detector capable of more accurately obtaining geoacoustic data during debris flow outbreaks. The debris flow geoacoustic monitoring device includes a monitoring terminal, a central terminal, and a control terminal connected in sequence; the monitoring terminal is a geoacoustic signal detection device, and a MEMS three-axis digital accelerometer chip is used as a sensing element, and the central terminal is a control terminal and a monitoring terminal. The signal transmission device between the terminals, and the control terminal is the geoacoustic signal processing and control instruction operation device. The present invention also provides a flow velocity measurement device for a debris flow faucet realized by using the above-mentioned debris flow geoacoustic monitoring device. the

能够实时测量每个采样点上x、y、z三个方向的加速度数据，计算得到的地声强度更准确，并且体积小、重量轻、抗干扰、能耗低。但是不具备监测信号的远程传输和发送功能，使该设备的应用场合受到了一定的限制。 It can measure the acceleration data in the three directions of x, y, and z at each sampling point in real time, and the calculated ground sound intensity is more accurate, and it is small in size, light in weight, anti-interference, and low in energy consumption. However, it does not have the function of remote transmission and sending of monitoring signals, which limits the application of the device to a certain extent. the

公开号：CN201716821U，名称为一种泥石流监测预警装置公开了一种泥石流监测预警装置，包括红外监测模块、主控制器、无线数据传输模块、太阳能发电模块、电源管理模块、蓄电池组模块、人机接口模块和声音报警模块。所述红外监测模块监测泥石流的产生；所述红外监测模块与主控制器相连接；所述主控制器分别与无线数据传输模块、人机接口模块、电源管理模块和声音报警模块相连接；所述无线数据传输模块包括无线数据收发处理模块和天线；所述太阳能发电模块经电源管理模块后分别系统供电和蓄电池组充电；所示蓄电池组在光照强度不足时对系统供电。 Publication number: CN201716821U, titled A Debris Flow Monitoring and Early Warning Device A debris flow monitoring and early warning device is disclosed, including an infrared monitoring module, a main controller, a wireless data transmission module, a solar power generation module, a power management module, a battery pack module, a man-machine Interface module and sound alarm module. The infrared monitoring module monitors the generation of debris flow; the infrared monitoring module is connected with the main controller; the main controller is respectively connected with the wireless data transmission module, the man-machine interface module, the power management module and the sound alarm module; The wireless data transmission module includes a wireless data sending and receiving processing module and an antenna; the solar power generation module is powered by the power management module and charged by the battery pack; the battery pack is used to supply power to the system when the light intensity is insufficient. the

该泥石流监测预警装置非常适用于地质灾害监测、预警、救灾等领域，具有结构简单合理、价格低廉、操作方便等优点。但是该发明中主要采用红外装置对泥石流进行监测，由于红外感应准确度较低，因此对泥石流灾害的发生规模和波及范围的预测不是很准确。 The debris flow monitoring and early warning device is very suitable for geological disaster monitoring, early warning, disaster relief and other fields, and has the advantages of simple and reasonable structure, low price, convenient operation and the like. However, in this invention, an infrared device is mainly used to monitor the debris flow. Due to the low accuracy of infrared sensing, the prediction of the occurrence scale and the scope of the debris flow disaster is not very accurate. the

综上所述，现有的泥石流监测预警装置和系统，都存在以下弊端：监测设备单一固定，系统缺乏统一的数据管理与共享，无法进行海量数据管理，监测数据精确性与可靠度不够高，实时性较差，设备成本太高等。 To sum up, the existing debris flow monitoring and early warning devices and systems have the following disadvantages: the monitoring equipment is single and fixed, the system lacks unified data management and sharing, cannot manage massive data, and the accuracy and reliability of monitoring data are not high enough. The real-time performance is poor, and the equipment cost is too high. the

发明内容Contents of the invention

本发明的目的在于，针对上述问题，提出一种基于物联网的泥石流临灾监测系统，以实现实时监控且精确度高的优点。 The object of the present invention is to propose a debris flow disaster monitoring system based on the Internet of Things to achieve the advantages of real-time monitoring and high accuracy in view of the above problems. the

为实现上述目的，本发明采用的技术方案是： To achieve the above object, the technical scheme adopted in the present invention is:

一种基于物联网的泥石流临灾监测系统，包括物联网云端服务器，以及与云端服务器通信连接的气象中心，所述云端服务器通信连接无线传感网，所述无线传感网包括网络节点、土壤水分传感器、土壤内部压力传感器以及定位装置，所述土壤水分传感器、土壤内部压力传感器和定位装置检测的数据均通过网络节点传输至云端服务器。A debris flow disaster monitoring system based on the Internet of Things, including an Internet of Things cloud server, and a meteorological center connected to the cloud server in communication, the cloud server is connected to a wireless sensor network, and the wireless sensor network includes network nodes, soil The moisture sensor, the soil internal pressure sensor and the positioning device, the data detected by the soil moisture sensor, the soil internal pressure sensor and the positioning device are all transmitted to the cloud server through the network node.

根据本发明的优选实施例，所述网络节点通过3G网络与云端服务器通信。 According to a preferred embodiment of the present invention, the network node communicates with the cloud server through a 3G network. the

根据本发明的优选实施例，所述土壤水分传感器包括第一电源模块、第一处理器模块、第一通信模块和第一传感器模块，所述第一通信模块和第一传感器模块均与第一处理器模块电连接，所述第一电源模块为第一处理器模块、第一通信模块和第一传感器模块提供直流电源。 According to a preferred embodiment of the present invention, the soil moisture sensor includes a first power supply module, a first processor module, a first communication module and a first sensor module, and both the first communication module and the first sensor module are connected to the first The processor modules are electrically connected, and the first power supply module provides DC power for the first processor module, the first communication module and the first sensor module. the

根据本发明的优选实施例，所述土壤水分传感器封装在环氧树脂纯胶体内。 According to a preferred embodiment of the present invention, the soil moisture sensor is packaged in a pure epoxy resin body. the

根据本发明的优选实施例，所述土壤内部压力传感器包括第二电源模块、第二处理器模块、第二通信模块和第二传感器模块，所述第二通信模块和第二传感器模块均与第二处理器模块电连接，所述第二电源模块为第二处理器模块、第二通信模块和第二传感器模块提供直流电源。 According to a preferred embodiment of the present invention, the soil internal pressure sensor includes a second power supply module, a second processor module, a second communication module and a second sensor module, and the second communication module and the second sensor module are both connected to the first The two processor modules are electrically connected, and the second power supply module provides DC power for the second processor module, the second communication module and the second sensor module. the

根据本发明的优选实施例，所述第二传感器模块由两层衬底构成，该两层衬底的内表面均覆盖导体材料，在导体材料上覆盖对压力敏感的墨水，所述两层衬底的内表面通过粘合剂粘合在一起。 According to a preferred embodiment of the present invention, the second sensor module is composed of two layers of substrates, the inner surfaces of the two layers of substrates are covered with conductive materials, and the conductive materials are covered with pressure-sensitive ink. The inner surfaces of the bottom are bonded together by an adhesive. the

根据本发明的优选实施例，所述定位装置包括第三电源模块、第三处理器模块、第三通信模块和第三传感器模块，所述第三通信模块和第三传感器模块均与第三处理器模块电连接，所述第三电源模块为第三处理器模块、第三通信模块和第三传感器模块提供直流电源，所述第三传感器模块至少集成加速度传感器、方向传感器、地磁传感器和GPS。 According to a preferred embodiment of the present invention, the positioning device includes a third power supply module, a third processor module, a third communication module and a third sensor module, and the third communication module and the third sensor module are both connected to the third processing The controller module is electrically connected, and the third power supply module provides DC power for the third processor module, the third communication module and the third sensor module, and the third sensor module at least integrates an acceleration sensor, an orientation sensor, a geomagnetic sensor and a GPS. the

根据本发明的优选实施例，所述云端服务器根据定位装置的数据进行节点位移计算方法如下： According to a preferred embodiment of the present invention, the cloud server calculates the node displacement according to the data of the positioning device as follows:

步骤1：由上述加速度传感器获取节点加速度值，该加速度值分别为相对节点界面m、n、l三个方向的加速度数值 

、

、

，设定采样率对上述节点加速度值

、

、

进行采样；Step 1: Obtain the acceleration value of the node by the above acceleration sensor, and the acceleration value is the acceleration value in the three directions of m, n and l relative to the node interface

,

,

, set the sampling rate to the above node acceleration values

,

,

to sample;

步骤2：利用上述方向传感器获取节点姿态，得到节点界面三个方向与地面空间坐标系在x、y、z之间的夹角数值，分别为

、

、，通过与上述获取节点加速度值相同的采样率进行采样，得到坐标变换矩阵如下：Step 2: Use the above direction sensor to obtain the node attitude, and obtain the angle values between the three directions of the node interface and the ground space coordinate system between x, y, and z, which are respectively

,

, , sampling at the same sampling rate as the node acceleration value obtained above, the coordinate transformation matrix is obtained as follows:

 ， ,

步骤3：投影计算：将上述采用得到的节点加速度数值投影到地面空间坐标系中并分别计算，得出节点在地面空间坐标系中的加速度值为

、

、

，Step 3: Projection calculation: Project the node acceleration value obtained above into the ground space coordinate system and calculate separately, and obtain the acceleration value of the node in the ground space coordinate system

,

,

,

                                   

                                   

步骤4：得出节点在x、y、z三个方向上的位移增量记为

、

、

，Step 4: Obtain the displacement increment of the node in the three directions of x, y, and z as

,

,

,

                                           

                                           

步骤5：则节点的位移增量如下： Step 5: The displacement increment of the node is as follows:

                                   

                                   

上述计算公式中起始速度

， 

为传感器采样时间，为

时间点的传感器移动速度；The starting speed in the above calculation formula

,

is the sensor sampling time, for

The sensor moving speed at the point in time;

步骤6：从而得出长时间段内节点的位移数值，如公式所示：Step 6: Thus, the displacement value of the node in a long time period is obtained, as shown in the formula:

                                                                    

                                                                    

上式中

初始值为0，

为

时刻之后的位移。In the above formula

The initial value is 0,

for

Displacement after time.

本发明的技术方案具有以下有益效果： Technical scheme of the present invention has the following beneficial effects:

本发明的技术方案，通过需要监控泥石流的地区布设无线传感网，通过无线传感网中的土壤水分传感器、土壤内部压力传感器对土壤的检测，以及定位装置对土壤移动位移的检测，以及结合气象中心采集的周围的气象数据，经过云端处理器的计算和模拟，达到了对泥石流灾害进行，实时监控且精确度高的目的。In the technical solution of the present invention, a wireless sensor network is deployed in areas where debris flow needs to be monitored, the soil moisture sensor and the soil internal pressure sensor in the wireless sensor network are used to detect the soil, and the positioning device detects the displacement of the soil, and combines The surrounding meteorological data collected by the meteorological center is calculated and simulated by the cloud processor to achieve the purpose of real-time monitoring of debris flow disasters with high accuracy.

下面通过附图和实施例，对本发明的技术方案做进一步的详细描述。 The technical solutions of the present invention will be described in further detail below with reference to the accompanying drawings and embodiments. the

附图说明Description of drawings

图1为本发明实施例所述的基于物联网的泥石流临灾监测系统原理示意图； Fig. 1 is the principle schematic diagram of the debris flow imminent disaster monitoring system based on the Internet of Things described in the embodiment of the present invention;

图2为本发明实施例所述的土壤水分传感器的原理框图；Fig. 2 is the functional block diagram of the soil moisture sensor described in the embodiment of the present invention;

图3为本发明实施例所述的土壤内部压力传感器的原理框图；Fig. 3 is the functional block diagram of the soil internal pressure sensor described in the embodiment of the present invention;

图4为本发明实施例所述的定位装置的原理框图；FIG. 4 is a functional block diagram of a positioning device according to an embodiment of the present invention;

图5为本发明实施例所述的位移计算示意图；Fig. 5 is a schematic diagram of displacement calculation described in an embodiment of the present invention;

图6为本发明实施例所述的感知精度和节点个数对照图；Fig. 6 is a comparison diagram of perception accuracy and the number of nodes described in the embodiment of the present invention;

图7为本发明实施例所述的布网成本和节点个数的对照图；Fig. 7 is a comparison diagram of the network deployment cost and the number of nodes described in the embodiment of the present invention;

图8为本发明实施例所述的定位方法的精度对照图。Fig. 8 is a comparison chart of the accuracy of the positioning method described in the embodiment of the present invention.

结合附图，本发明实施例中附图标记如下： In conjunction with the accompanying drawings, the reference signs in the embodiments of the present invention are as follows:

1-网络节点；2-气象中心；3-3G基站。1-network node; 2-meteorological center; 3-3G base station.

具体实施方式Detailed ways

以下结合附图对本发明的优选实施例进行说明，应当理解，此处所描述的优选实施例仅用于说明和解释本发明，并不用于限定本发明。 The preferred embodiments of the present invention will be described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described here are only used to illustrate and explain the present invention, and are not intended to limit the present invention. the

如图1所示，一种基于物联网的泥石流临灾监测系统，包括物联网云端服务器，以及与云端服务器通信连接的气象中心，云端服务器通信连接无线传感网，无线传感网包括网络节点、土壤水分传感器、土壤内部压力传感器以及定位装置，土壤水分传感器、土壤内部压力传感器和定位装置检测的数据均通过网络节点传输至云端服务器。 As shown in Figure 1, a debris flow disaster monitoring system based on the Internet of Things includes an Internet of Things cloud server and a meteorological center connected to the cloud server. The cloud server communicates with a wireless sensor network, and the wireless sensor network includes network nodes. , soil moisture sensor, soil internal pressure sensor and positioning device, the data detected by the soil moisture sensor, soil internal pressure sensor and positioning device are all transmitted to the cloud server through the network node. the

其中，网络节点通过3G网络与云端服务器通信。 Wherein, the network node communicates with the cloud server through the 3G network. the

如图2所示，土壤水分传感器包括第一电源模块、第一处理器模块、第一通信模块和第一传感器模块，第一通信模块和第一传感器模块均与第一处理器模块电连接，第一电源模块为第一处理器模块、第一通信模块和第一传感器模块提供直流电源。土壤水分传感器封装在环氧树脂纯胶体内。携带方便，安装、操作及维护简单。结构设计合理，不绣钢探针保证使用寿命。外部以环氧树脂纯胶体封装，密封性好，可直接埋入土壤中使用，且不受腐蚀。土质影响较小，应用地区广泛。测量精度高，性能可靠，土壤水分传感器的各项具体参数如表一所示， As shown in Figure 2, the soil moisture sensor comprises a first power supply module, a first processor module, a first communication module and a first sensor module, and the first communication module and the first sensor module are all electrically connected to the first processor module, The first power supply module provides DC power for the first processor module, the first communication module and the first sensor module. The soil moisture sensor is encapsulated in the pure epoxy body. Easy to carry, easy to install, operate and maintain. The structure design is reasonable, and the stainless steel probe guarantees the service life. The exterior is encapsulated with epoxy resin pure colloid, which has good sealing performance and can be directly buried in the soil for use without corrosion. The influence of soil quality is small, and the application area is wide. The measurement accuracy is high and the performance is reliable. The specific parameters of the soil moisture sensor are shown in Table 1.

 表一、土壤水分传感器具体参数表：Table 1. Specific parameter table of soil moisture sensor:

。

.

如图3所示，土壤内部压力传感器包括第二电源模块、第二处理器模块、第二通信模块和第二传感器模块，第二通信模块和第二传感器模块均与第二处理器模块电连接，第二电源模块为第二处理器模块、第二通信模块和第二传感器模块提供直流电源。第二传感器模块由两层衬底构成，衬底可由聚脂纤维薄膜组成(高温传感器用的是聚酰亚胺)构成，第二传感器模块由两层衬底构成，该两层衬底的内表面均覆盖导体材料，在导体材料上覆盖对压力敏感的墨水，然后用粘合剂把两层衬底压在一起。压力传感器是将施加在FSR传感器薄膜区域的压力值转换成电阻值的变化，从而获得压力信息。压力越大，电阻越低。土壤内部压力传感器的各项具体参数如表二所示， As shown in Figure 3, the soil internal pressure sensor includes a second power supply module, a second processor module, a second communication module and a second sensor module, and the second communication module and the second sensor module are electrically connected to the second processor module , the second power supply module provides DC power for the second processor module, the second communication module and the second sensor module. The second sensor module is composed of two layers of substrates, the substrate can be made of polyester fiber film (polyimide is used for high temperature sensors), the second sensor module is composed of two layers of substrates, the inner layer of the two layers of substrates Both surfaces are covered with conductive material, the conductive material is covered with pressure-sensitive ink, and then the two substrates are pressed together with an adhesive. The pressure sensor is to convert the pressure value applied to the film area of the FSR sensor into the change of the resistance value, so as to obtain the pressure information. The greater the pressure, the lower the resistance. The specific parameters of the soil internal pressure sensor are shown in Table 2.

表二、土壤内部压力传感器参数表：Table 2. Soil internal pressure sensor parameter table:

。

.

如图4所示，定位装置包括第三电源模块、第三处理器模块、第三通信模块和第三传感器模块，第三通信模块和第三传感器模块均与第三处理器模块电连接，第三电源模块为第三处理器模块、第三通信模块和第三传感器模块提供直流电源，第三传感器模块至少集成加速度传感器、方向传感器、地磁传感器和GPS。 As shown in Figure 4, the positioning device includes a third power supply module, a third processor module, a third communication module and a third sensor module, the third communication module and the third sensor module are electrically connected to the third processor module, the third The three power supply modules provide DC power for the third processor module, the third communication module and the third sensor module, and the third sensor module integrates at least an acceleration sensor, an orientation sensor, a geomagnetic sensor and a GPS. the

位移的计算分为线位移的计算和角位移的计算两个部分。如图5所示，线位移和角位移的计算主要分为计算和校准过程。位移的计算主要通过积分过程来完成的。提取到的三个轴向的加速度值联合提取到的方向角度值，投影到地球空间坐标系中，再经过二次积分就得到的三个轴向的位移数值，再计算合位移就得到运动过程中的直线距离。 The calculation of the displacement is divided into two parts: the calculation of the linear displacement and the calculation of the angular displacement. As shown in Figure 5, the calculation of linear displacement and angular displacement is mainly divided into calculation and calibration process. The calculation of the displacement is mainly done through the integration process. The extracted acceleration values of the three axes are combined with the extracted direction angle values, projected into the earth space coordinate system, and then the displacement values of the three axes are obtained through the second integration, and then the combined displacement is calculated to obtain the motion process The straight-line distance in . the

三轴加速度传感器得到三个相对节点面板方向上加速度的数值，由于加速度的数值的方向总是沿着节点姿态的方向，就需要利用方向传感器得到节点的姿态，方向传感器的返回值是三个角度值，这三个角度分别是节点坐标系相对于地面空间坐标系的三个方向的夹角，这三个量表征节点姿态，利用这三个量将加速度值投影到空间坐标系，然后逐个方向计算位移。 The three-axis acceleration sensor obtains three acceleration values relative to the direction of the node panel. Since the direction of the acceleration value is always along the direction of the node attitude, it is necessary to use the direction sensor to obtain the attitude of the node. The return value of the direction sensor is three angles Values, these three angles are the angles between the node coordinate system and the three directions of the ground space coordinate system, these three quantities represent the node attitude, use these three quantities to project the acceleration value to the space coordinate system, and then direction by direction Calculate the displacement. the

位移计算过程如下： The displacement calculation process is as follows:

由三轴加速度传感器获取加速度值，分别是相对节点界面m、n、l三个方向的加速度数值

、

、

，在获取的时候设置获取的，采样率越高位移计算越精确，采样率暂且设置成60 microseconds（一百万分之一秒），提取一次数值。采用方向传感器获取节点姿态，得到节点界面x、y、z三个方向与地面空间坐标系之间的夹角数值，分别为

、

、

，这个采样率和加速度传感器的采样率保持一致。由此可以得到坐标变换矩阵如下：The acceleration values obtained by the three-axis acceleration sensor are the acceleration values in the three directions of m, n, and l relative to the node interface

,

,

, set the acquisition at the time of acquisition, the higher the sampling rate, the more accurate the displacement calculation, the sampling rate is temporarily set to 60 microseconds (one millionth of a second), and the value is extracted once. The orientation sensor is used to obtain the node attitude, and the angle values between the x, y, and z directions of the node interface and the ground space coordinate system are obtained, which are respectively

,

,

, this sampling rate is consistent with the sampling rate of the acceleration sensor. From this, the coordinate transformation matrix can be obtained as follows:

    （1）

(1)

投影计算：将加速度数值投影到地面空间坐标系中分别计算，地面空间坐标系中的加速度值为

、

、

，Projection calculation: Project the acceleration value into the ground space coordinate system and calculate separately. The acceleration value in the ground space coordinate system is

,

,

,

                       (2) 

(2)

位移增量计算：三个方向上的位移增量记为

、、

，Calculation of displacement increments: the displacement increments in three directions are recorded as

, ,

,

            (3)               

(3)

则合位移增量计算如下： Then the combined displacement increment is calculated as follows:

          (4)         

(4)

上述计算公式中起始速度

， 

为传感器采样时间，为

时间点的传感器移动速度。

采用是大约设置为采样间隔60 microseconds，这个时间间隔可由处理器获取。位移在计算的时候采用累加方式计算，即通过积分的方式得到长时间段内的位移数值，如公式所示：The starting speed in the above calculation formula

,

is the sensor sampling time, for

The sensor movement speed at the point in time.

Adoption is set approximately to a sampling interval of 60 microseconds, which is captured by the processor. The displacement is calculated in an accumulative way, that is, the displacement value in a long period of time is obtained by means of integration, as shown in the formula:

             (5)                                   

(5)

上式中

初始值为0，为

时刻之后的位移。In the above formula

The initial value is 0, for

Displacement after time.

地磁传感器即陀螺仪，陀螺仪和方向传感器之间存在联系，陀螺仪中获得的是三个轴向的角速度，角速度与时间的乘积就是夹角增量值，利用这个关系获得节点姿态，用于投影计算。 The geomagnetic sensor is the gyroscope, and there is a connection between the gyroscope and the direction sensor. The gyroscope obtains the angular velocity of the three axes, and the product of the angular velocity and time is the angle increment value. This relationship is used to obtain the node attitude, which is used for projection calculations. the

本发明技术方案中各个电器件的价格如表三所示，可见本发明的技术方案成本低， The price of each electrical device in the technical solution of the present invention is as shown in Table 3, it can be seen that the cost of the technical solution of the present invention is low,

表三、无线传感器网络中元器件价格表：Table 3. Price list of components in wireless sensor networks:

。

.

表4、无线传感器网络中元器件型号表： Table 4. Component model list in wireless sensor network:

布置无线传感网是，首先综合考虑地区的人口密度、经济密度、地质构造、项目建设等情况，当敏感区域的降雨量变化较大时，部署无线传感器网络对地质灾害易发区域进行临灾监测。无线传感器网络主要包括土壤内部压力传感器节点、土壤水分传感器节点、定位装置节点、M2M网关等设备，最后将采集到的相关信息数据发送到数据处理中心，做进一步的分析处理工作，为临灾预测提供信息依据。系统将无线传感器网络监测收集到的数据结合气象监测收集到的数据存储在云端服务器，并进行计算处理，根据泥石流灾害预测模型进行分析推演，模拟出泥石流灾情并对灾情进行评估。通过网络将灾情数据、图表以及泥石流模拟视频传输到相关主管部门单位进行灾情预报，做出最终抗灾、防灾、减灾等决策。When deploying a wireless sensor network, the population density, economic density, geological structure, project construction, etc. of the area should be considered comprehensively. When the rainfall in sensitive areas changes greatly, the wireless sensor network should be deployed to provide emergency response to geological disaster-prone areas. monitor. The wireless sensor network mainly includes soil internal pressure sensor nodes, soil moisture sensor nodes, positioning device nodes, M2M gateways and other equipment. Finally, the collected relevant information data is sent to the data processing center for further analysis and processing to provide disaster prediction Provide information basis. The system stores the data collected by wireless sensor network monitoring combined with the data collected by meteorological monitoring in the cloud server, and performs calculation and processing, analyzes and deduces according to the debris flow disaster prediction model, simulates the debris flow disaster situation and evaluates the disaster situation. Through the network, the disaster data, charts, and debris flow simulation videos are transmitted to relevant competent departments for disaster forecasting, and final disaster prevention, disaster prevention, and disaster reduction decisions are made.

在无线传感网上集成土壤水分传感器、土壤内部压力传感器来实时监测敏感区域的土壤内部的关键参数的变化；在泥石流发生的过程中，网络节点会随着泥石流的移动而移动，对泥石流内部参数进行实时跟踪监测并实时向外传输数据。其中定位装置上，我们集成了加速度传感器、方向传感器、地磁传感器和GPS等器件，对节点进行精确定位，并根据节点的位移来计算泥石流的流速；当泥石流即将发生以及发生初期，其内部各种参数会出现急剧变化，将产生海量的异构数据，并采用云存储、高效数据融合及高性能自治计算等手段，对监测到的数据进行高效管理，结合泥石流发生预警模型，对泥石流的爆发进行可靠精确地预测；根据处理结果对泥石流的爆发进行反演，在客户端可直接观看到数据变化情况，数据变化曲线图，模拟泥石流爆发的状况及区域，利用互联网、3G网络等与相关气象预报单位、地方政府及社会公共安全等单位进行数据组网，形成一个泥石流灾情预报网络。 Soil moisture sensors and soil internal pressure sensors are integrated on the wireless sensor network to monitor the changes of key parameters inside the soil in sensitive areas in real time; during the process of debris flow, the network nodes will move with the movement of the debris flow, and the internal parameters of the debris flow Carry out real-time tracking and monitoring and transmit data to the outside world in real time. Among them, on the positioning device, we integrated acceleration sensors, direction sensors, geomagnetic sensors, GPS and other devices to accurately locate the nodes, and calculate the flow velocity of the debris flow according to the displacement of the nodes; Parameters will change drastically, and a large amount of heterogeneous data will be generated. Cloud storage, efficient data fusion, and high-performance autonomous computing are used to efficiently manage the monitored data. Combined with the early warning model of debris flow, the outbreak of debris flow Reliable and accurate prediction; inversion of the outbreak of debris flow according to the processing results, the data changes and data change curves can be directly viewed on the client side, the situation and area of the debris flow outbreak can be simulated, and related weather forecasts can be made using the Internet and 3G networks Units, local governments, and social public security units conduct data networking to form a debris flow disaster forecasting network. the

在无线传感网上的监测节点上集成土壤水分传感器、土壤内部压力传感器来实时监测敏感区域的土壤内部的关键参数的变化；在泥石流发生的过程中，网络节点会随着泥石流的移动而移动，对泥石流内部参数进行实时跟踪监测并实时向外传输数据。其中监测节点的定位装置上，我们集成了加速度传感器、方向传感器、地磁传感器和GPS等器件，对节点进行精确定位，并根据节点的位移来计算泥石流的流速。 Integrate soil moisture sensors and soil internal pressure sensors on the monitoring nodes on the wireless sensor network to monitor the changes of key parameters inside the soil in sensitive areas in real time; during the occurrence of debris flow, the network nodes will move with the movement of the debris flow, Real-time tracking and monitoring of internal parameters of debris flow and real-time transmission of data. Among them, on the positioning device of the monitoring node, we integrated acceleration sensors, direction sensors, geomagnetic sensors and GPS to accurately locate the nodes, and calculate the flow velocity of the debris flow according to the displacement of the nodes. the

如图 6、图7所示，定义感知精度=监测面积/节点个数，布网成本=节点单价×数量+网关成本，当监测面积为100m×100m，节点个数为30时，感知精度为333.33，布网总成本为24000元，单位面积布网成本为2.40元。相比现有的泥石流监测设备，本发明技术方案的传感器节点具有低成本的特性。 As shown in Figure 6 and Figure 7, define the perception accuracy = monitoring area/number of nodes, network deployment cost = node unit price × quantity + gateway cost, when the monitoring area is 100m×100m, and the number of nodes is 30, the perception accuracy is 333.33 , the total cost of netting is 24,000 yuan, and the cost of netting per unit area is 2.40 yuan. Compared with the existing debris flow monitoring equipment, the sensor node of the technical solution of the present invention has the characteristics of low cost.

如图8所示，多传感器定位在小于5m范围定位误差约为10%，多传感器定位即采用加速传感器、方向传感器和地磁传感器的定位方法，适合小范围定位。GPS定位精度在5-10m之间，适合较大范围定位。两种定位方位联合使用，互相补充，可以较为精确地跟踪流速小于10m/s的泥石流。 As shown in Figure 8, the positioning error of multi-sensor positioning is about 10% within a range of less than 5m. Multi-sensor positioning uses the positioning method of acceleration sensor, direction sensor and geomagnetic sensor, which is suitable for small-scale positioning. The GPS positioning accuracy is between 5-10m, which is suitable for large-scale positioning. The two positioning azimuths are used in combination and complement each other, and can more accurately track debris flows whose velocity is less than 10m/s. the

最后应说明的是：以上所述仅为本发明的优选实施例而已，并不用于限制本发明，尽管参照前述实施例对本发明进行了详细的说明，对于本领域的技术人员来说，其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分技术特征进行等同替换。凡在本发明的精神和原则之内，所作的任何修改、等同替换、改进等，均应包含在本发明的保护范围之内。 Finally, it should be noted that: the above is only a preferred embodiment of the present invention, and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, for those skilled in the art, it still The technical solutions recorded in the foregoing embodiments may be modified, or some technical features thereof may be equivalently replaced. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present invention shall be included within the protection scope of the present invention. the

Claims (8)

1. the rubble flow based on Internet of Things faces the calamity monitoring system, comprise the Internet of Things cloud server, the hereinafter referred cloud server, and with the forecast center of cloud server communication connection, it is characterized in that, described cloud server communication connection wireless sense network, described wireless sense network comprises network node, soil moisture sensor, soil internal pressure sensor and locating device, and the data that described soil moisture sensor, soil internal pressure sensor and locating device detect all transfer to cloud server by network node.

2. the rubble flow based on Internet of Things according to claim 1 faces the calamity monitoring system, it is characterized in that, described network node is communicated by letter with cloud server by 3G network.

3. the rubble flow based on Internet of Things according to claim 1 and 2 faces the calamity monitoring system, it is characterized in that, described soil moisture sensor comprises the first power module, first processor module, first communication module and first sensor module, described first communication module and first sensor module all are electrically connected to the first processor module, and described the first power module provides direct supply for first processor module, first communication module and first sensor module.

4. the rubble flow based on Internet of Things according to claim 3 faces the calamity monitoring system, it is characterized in that, described soil moisture sensor is encapsulated in the pure colloid of epoxy resin.

5. the rubble flow based on Internet of Things according to claim 1 and 2 faces the calamity monitoring system, it is characterized in that, described soil internal pressure sensor comprises second source module, the second processor module, second communication module and the second sensor assembly, described second communication module and the second sensor assembly all are electrically connected to the second processor module, and described second source module provides direct supply for the second processor module, second communication module and the second sensor assembly.

6. the rubble flow based on Internet of Things according to claim 5 faces the calamity monitoring system, it is characterized in that, described the second sensor assembly consists of two-layer substrate, the inside surface of this two-layer substrate all covers conductor material, on conductor material, cover pressure-sensitive ink, the inside surface of described two-layer substrate is bonded together by bonding agent.

7. the rubble flow based on Internet of Things according to claim 1 and 2 faces the calamity monitoring system, it is characterized in that, described locating device comprises the 3rd power module, the 3rd processor module, third communication module and the 3rd sensor assembly, described third communication module and the 3rd sensor assembly all are electrically connected to the 3rd processor module, described the 3rd power module provides direct supply for the 3rd processor module, third communication module and the 3rd sensor assembly, and described the 3rd sensor assembly is Integrated Accelerometer, direction sensor, geomagnetic sensor and GPS at least.

8. the rubble flow based on Internet of Things according to claim 1 and 2 faces the calamity monitoring system, it is characterized in that, it is as follows that described cloud server carries out the nodal displacement computing method according to the data of locating device:

Step 1: obtain the node accekeration by above-mentioned acceleration transducer, this accekeration is respectively the acceleration value of relative node interface m, n, tri-directions of l

,

,

, set sampling rate to above-mentioned node accekeration

,

,

sampled;

Step 2: utilize above-mentioned direction sensor to obtain the node attitude, obtain three, node interface direction and the ground space coordinate system angle numerical value between x, y, z, be respectively

,

,

, by with above-mentioned, obtain the sampling rate that the node accekeration is identical and sampled, obtain transformation matrix of coordinates as follows:

，

Step 3: projection is calculated: the node acceleration value that above-mentioned employing is obtained projects in the ground space coordinate system and calculates respectively, obtains the accekeration of egress in the ground space coordinate system and is

,

,

,

Step 4: obtain the displacement increment of egress on three directions of x, y, z and be designated as

,,

,

Step 5: the displacement increment of node is as follows:

Starting velocity in above-mentioned computing formula,

for the sensor sample time,

forthe sensor translational speed of time point;

Step 6: thus draw the displacement numerical value of long-time section interior nodes, as shown in formula:

In above formula

initial value is 0,for

displacement constantly.

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