CN109389807B - Intelligent monitoring and early warning system for creep type landslide - Google Patents
Intelligent monitoring and early warning system for creep type landslide Download PDFInfo
- Publication number
- CN109389807B CN109389807B CN201710664056.0A CN201710664056A CN109389807B CN 109389807 B CN109389807 B CN 109389807B CN 201710664056 A CN201710664056 A CN 201710664056A CN 109389807 B CN109389807 B CN 109389807B
- Authority
- CN
- China
- Prior art keywords
- landslide
- monitoring
- early warning
- tangential angle
- displacement
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B21/00—Alarms responsive to a single specified undesired or abnormal condition and not otherwise provided for
- G08B21/02—Alarms for ensuring the safety of persons
- G08B21/10—Alarms for ensuring the safety of persons responsive to calamitous events, e.g. tornados or earthquakes
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/02—Protocols based on web technology, e.g. hypertext transfer protocol [HTTP]
- H04L67/025—Protocols based on web technology, e.g. hypertext transfer protocol [HTTP] for remote control or remote monitoring of applications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W84/00—Network topologies
- H04W84/18—Self-organising networks, e.g. ad-hoc networks or sensor networks
Landscapes
- Engineering & Computer Science (AREA)
- Signal Processing (AREA)
- Computer Networks & Wireless Communication (AREA)
- Business, Economics & Management (AREA)
- Environmental & Geological Engineering (AREA)
- Emergency Management (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Geology (AREA)
- General Life Sciences & Earth Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Health & Medical Sciences (AREA)
- Computing Systems (AREA)
- General Health & Medical Sciences (AREA)
- Medical Informatics (AREA)
- Testing Or Calibration Of Command Recording Devices (AREA)
- Pit Excavations, Shoring, Fill Or Stabilisation Of Slopes (AREA)
- Emergency Alarm Devices (AREA)
Abstract
The invention discloses a creep type landslide intelligent monitoring and early warning system, which relates to the field of geological disaster monitoring. According to the invention, a landslide prediction method for acquiring the critical sliding tangent line angle at the constant-speed deformation rate of the landslide creep is adopted, and the critical sliding tangent line angle of the landslide can be obtained only by determining the stage of the landslide and the constant-speed deformation rate, so that a better early warning and prediction effect on the damage and instability of the landslide can be achieved.
Description
Technical Field
The invention relates to the field of geological disaster monitoring, in particular to an intelligent monitoring and early warning system for a creep type landslide.
Background
In recent years, along with continuous extension and build-up of railways and highways; the construction such as the excavation of resident building and city tourism development has destroyed primary geology, landform to a certain extent, especially in disorder forest, the underground mineral resources of random exploitation lead to water and soil to run off in a large number, geological disasters frequently take place, landslide event is frequent. Landslide disasters occur in an countless number each year, cause great harm to lives and properties of human beings, seriously affect social progress of the human beings, and restrict national economic development. Although the mechanism research, prevention and control technology and early warning and forecasting level of landslide disasters are continuously improved, casualties and economic losses caused by landslide are not obviously reduced.
With rapid development of computer technology, communication technology, network technology, electronic technology, bus technology, internet of things technology and embedded technology, automatic monitoring of landslide at home and abroad has been greatly developed. The United States Geological Survey (USGS) and the United States National Weather Service (USNWS) (1985) jointly establish a set of real-time landslide warning system, which predicts and predicts landslide during the storm in san francisco bay area and issues the first public regional landslide early warning in the united states; the United States Geological Survey (USGS) and the Eldorado national forest park (1996) jointly monitor multiple landslide on two sides along the No. 50 expressway in California, and a landslide real-time monitoring system is designed and realized; aiming at the defect of high cost of landslide real-time monitoring, canada Danisch et al (2004), a set of high-quality and low-cost landslide real-time monitoring system is developed; maso YAMADA et al in Japan perform remote monitoring of various modes based on network technology, and develop a related monitoring system for real-time landslide monitoring; come card and American AGI company, in order to meet the market demand of monitoring the side (landslide), produced systems such as GeoMoS and Slope-Sentry;
since the 80 s, a large number of landslide monitoring systems are continuously emerging in China, and various monitoring means, model methods and the like are adopted, and certain achievements are obtained. Among them, hong Kong (1997) developed a first version of landslide warning system (Landslip Warning System, LWS); zhang Yonghui and the like monitor the displacement of the side slope surface through a guy cable trigger type displacement meter, and real-time transmit test data to a remote monitoring center by utilizing GPRS, so that the monitoring has the characteristics of full automation and low cost; he Xiufeng based on the computer control technology, the microwave communication technology and the GPRS technology, a GPS one-machine multi-antenna slope remote automatic deformation monitoring system is developed; the wireless sensor monitoring network is established in the mountain monitoring area based on the wireless sensor network technology and the GPRS communication technology. Processing and analyzing the monitoring data to realize the safety precaution of landslide; long Jianhui and the like are based on high-end monitoring instruments, data processing technology, wireless communication technology, computer network technology and the like, and a landslide automatic monitoring system is developed.
Based on the previous research, the method further develops a research on analysis and theory of a large number of landslide monitoring data, provides an accurate and effective theoretical evaluation model, develops the research around aspects of sensor data acquisition, communication networking, algorithm analysis, system development and debugging, indoor and outdoor testing, system evaluation and the like, develops a set of intelligent monitoring and early warning system with independent intellectual property rights, low cost, high automation degree and low false alarm rate, is used for intelligent monitoring and evaluation analysis of landslide geological disasters, and has important social significance for guiding engineering design and reducing economic losses caused by landslide disasters.
Disclosure of Invention
The invention aims to provide a system capable of carrying out intelligent monitoring and early warning on a creep type landslide. The system adopts an advanced distributed system architecture, has the characteristics of high customization degree, flexible distribution, strong real-time performance, comprehensive functions, full life cycle coverage and the like, and can perform temporary slip early warning and forecasting on landslide and supporting side slopes.
The technical proposal adopted by the invention for solving the technical problems is that the creep type landslide intelligent monitoring and early warning system is characterized by comprising a server, a sensor and an information transmission part,
the sensor and the server form communication connection through an information transmission part,
the sensor comprises a displacement sensor and a rainfall sensor,
the server comprises a tangential angle data processing module and an early warning module, wherein the tangential angle data processing module is used for calculating a tangential angle according to displacement data and judging whether to send early warning according to whether the tangential angle exceeds a threshold value.
2. The intelligent creep type landslide monitoring and early warning system according to claim 1, wherein the tangential angle data processing module is judged in the following manner:
according to the formulaCalculating the critical slip tangential angle alpha Max If the current tangential angle is larger than the critical tangential angle, giving an early warning;
current tangential angle alpha i The calculation mode of (a) is as follows:
wherein delta epsilon (i) is the sliding slope displacement in the current monitoring period,
at the same rate of deformation at a constant rate,
t i for the current moment of monitoring,
t i-1 at t i Is a previous monitoring instant of time (a).
The server also comprises a rainfall data storage, and the rainfall data storage is connected with the tangential angle data processing module.
Compared with the prior art, the invention has the beneficial effects that: (1) The system adopts a general modular design, and can perform optimal combination on the on-site monitoring equipment according to on-site geological conditions, reinforcing measures and user requirements, and overall and local stability monitoring is considered; (2) The system adopts a sensor wireless ad hoc network technology, so that the layout and data acquisition have high flexibility, and the system is suitable for any complex terrain environment; (3) The system has the function of adaptively adjusting the monitoring frequency to correspond to the emergency; (4) The GPRS or Beidou module remote communication is supported, and a more convenient channel is provided for controlling on-site acquisition; (5) By adopting a landslide prediction method for acquiring the critical sliding tangent line angle at the constant-speed deformation rate of the landslide, the critical sliding tangent line angle of the landslide can be obtained only by determining the stage of the landslide and the constant-speed deformation rate, and the method has better early warning and prediction effects on the damage and instability of the landslide; (6) The acquisition instrument has the functions of active and passive sensor communication, data noise reduction, variable frequency control, firmware upgrading and the like, so that the sampling precision is greatly improved, the data processing is timely and accurate, the first time early warning of landslide disaster occurrence is achieved to the greatest extent, and the life and property safety of people is ensured.
Drawings
FIG. 1 is a schematic diagram of a creep type landslide intelligent monitoring and early warning system;
FIG. 2 is a network structure and layout diagram of a creep type landslide intelligent monitoring and early warning system;
FIG. 3 is a flow chart of real-time calculation and analysis of the intelligent monitoring and early warning system for the creep type landslide.
FIG. 4 is a plan view of a sensor for intelligent monitoring of a tailor's rock landslide.
FIG. 5 is a layout diagram of the main shaft section of the intelligent monitoring sensor for the tailor's rock landslide.
FIG. 6 is a graph of cumulative displacement versus time for tailor rock landslide.
And 7, an intelligent monitoring and early warning level diagram of the tailor's landslide.
Detailed Description
The invention is a three-level architecture system consisting of a plurality of sensors, acquisition units and a central system. The sensor can be monitored and laid according to on-site geological conditions, reinforcing measures and user requirements; the acquisition unit is a complete data acquisition device and comprises an acquisition instrument slave station and an acquisition instrument master station, and a wireless ad hoc network is arranged between the acquisition instrument slave station and the acquisition instrument master station, so that the acquisition unit is compatible with various types of sensors. The secondary station of the acquisition instrument is a child node of the wireless networking, is directly connected with the sensor, is arranged at the corresponding monitoring position of the landslide and the side slope, is responsible for acquiring the observation data of different observation points and comprehensively calculating and analyzing the data, and is transmitted to the primary station of the acquisition instrument in a wireless transmission mode; the acquisition instrument master station is a central master node of the wireless networking and is used for controlling the uploading frequency of slave station data in the wireless network and responding to an emergency, and the acquisition instrument master station is connected with the GPRS or the Beidou module to form a complete data acquisition transmission channel. The central system comprises an intelligent monitoring application server and a database server, and is responsible for storing monitoring data and early warning information and pushing client data.
Preferably, the monitoring types of the sensor comprise earth surface displacement monitoring, deep displacement monitoring and evoked factor monitoring (such as rainfall and groundwater level), the earth surface displacement meter collects accumulated displacement values of creep type landslide, the deep displacement meter collects creep accumulated displacement values of different depths of the landslide above a sliding belt, the rainfall meter collects rainfall of landslide areas, and the groundwater level meter collects elevation change of the groundwater level of the landslide.
Preferably, the layout principle of the multi-sensor should be based on monitoring of the overall stability of the landslide, and monitoring of the local stability should be considered. And selecting the section of the landslide main shaft as a main monitoring section, and other sections as auxiliary monitoring sections. The surface displacement meter is arranged at the rear edge of the landslide, and the datum point is positioned in the slope body structure stabilizing area at the rear edge of the landslide. The deep displacement meters are distributed at the front part, the middle part and the rear part of the section of the landslide, the datum points are embedded under the sliding surface for 2m, and the deep displacement meters are distributed on the sliding body at certain intervals. The underground water level meters and the deep displacement meters are distributed correspondingly, and the change of the underground water level corresponding to the deep displacement is obtained. The strain gauge is arranged on a supporting structure (such as a slide-resistant pile, an anchor rod, an anchor rope and the like). The rain gauge is arranged in a slope body structure stable area at the rear edge of the landslide so as to monitor the change of the rain gauge and control the on-site sampling frequency.
The sensor and the acquisition unit are powered by solar energy.
The wireless networking adopts a 433Mhz wireless communication module, has the LORA spread spectrum technology, and can realize wireless communication with the length of 1.5Km under the condition of extremely low power consumption.
The acquisition unit is provided with bidirectional interaction, data noise reduction, variable frequency control and firmware remote upgrading which are combined with active and passive data.
The invention adopts a creep type landslide constant speed deformation rate-based dynamic threshold early warning method, which comprises the following steps:
the method comprises the steps that an acquisition unit acquires an earth surface accumulated displacement value and a deep accumulated displacement value of a landslide;
the acquisition unit carries out self-adaptive Kalman filtering noise reduction processing on the acquired data, adjusts the data acquisition frequency of the acquisition instrument through a rainfall threshold value, removes interference signals and improves the sampling precision;
the system comprises a monitoring data uploading server (a central system), wherein the central system carries out real-time calculation and analysis on the uploaded data, and the specific steps are as follows:
(1) Calculating deformation rate according to the current acquired data, determining the development stage of the current creep type landslide and determining the constant-speed deformation rate;
(2) Performing equivalent class conversion on the monitored accumulated displacement;
(3) And calculating the critical sliding tangential angle of the landslide according to the creep type landslide dynamic early warning model. The early warning model is that Wherein: alpha Max Is the critical sliding tangent angle of the creep type landslide, < >>Is the deformation rate of the constant-speed deformation stage;
(4) And the critical sliding tangent angle is an early warning value of the landslide, and alarm information is generated when the critical sliding tangent angle reaches the early warning value.
According to the invention, the ground surface displacement monitoring points, the deep displacement monitoring points and the corresponding acquisition instrument secondary stations are respectively distributed on the rear edge of the landslide and the main shaft of the landslide body, and the acquisition instrument primary station is installed in a slope body structure stable area outside the landslide range. The data acquisition unit acquires the accumulated displacement value and the rainfall value of the landslide, the acquisition unit carries out self-adaptive Kalman filtering noise reduction processing on the monitoring data, and the monitoring data is transmitted to the central system through the GPRS or the Beidou module. The central system performs calculation analysis on the monitoring data and pushes the monitoring data and the early warning information to the client.
More specifically, the description is as follows:
the working process of the system of the invention comprises the following steps:
1) Presetting the period unit time length of a monitoring period, detecting the displacement in N periods, and calculating the constant-speed deformation rateConstant rate of deformation->Taking the average value of deformation rates measured in each monitoring period as the constant-speed creep stage if the difference value of displacement amounts measured in each monitoring period is in a preset range, and entering a step 2), wherein N is an integer larger than 4;
2) By the formulaCalculating the critical slip tangential angle alpha Max ，-16≤x≤-13,80≤y≤89；
3) Continuously detecting the displacement and calculating the tangential angle alpha according to the following formula i ：
Wherein delta epsilon (i) is the sliding slope displacement in the current monitoring period,
at the same rate of deformation at a constant rate,
t i for the current monitoring time，
t i-1 At t i Is the previous monitoring time of the (a);
4) Comparing the tangent angle alpha i And critical tangent angle alpha Max If the tangential angle alpha i Is greater than the critical tangent angle alpha Max A forecast signal is sent out.
Preferably, x= -14.57, y= 85.92.
The Δε (i) is the sliding displacement in the current monitoring period, and is illustrated as follows: taking the long-distance fixed datum point as a reference, setting the measured displacement in the first monitoring period as L1, namely, the displacement with the length of L1 occurs in the first monitoring period; the displacement is measured as L2 during the second monitoring period, i.e. a displacement of length L2-L1 occurs during the second monitoring period, i.e. a displacement of L2 occurs in combination with the first period and the second period. If the second monitoring period is taken as the current monitoring period, the sliding displacement in the current monitoring period refers to the displacement with the length of L2-L1.
Explanation of the constant-speed creep phase: the constant-speed creep stage refers to a stage in which displacement speeds are equal, or a stage in which displacement is uniform. However, it is obvious that an ideal uniform motion is very unlikely to occur, and therefore, it is reasonable to consider a phase in which the speed variation is smaller than a certain preset range as "constant speed", that is, "a constant speed creep phase if the difference in the displacement amounts measured for each monitoring period is within the preset range" as described above. In a common manner, the displacement obtained from the previous monitoring is calculated as a mean value, and if the difference between the displacement (new displacement) in the current period and the mean value is smaller than a preset range, the displacement is still considered as a constant velocity.
In the invention, the magnitude of the rainfall can influence the frequency of displacement detection, or the duration of the monitoring period, when the rainfall is large, the monitoring period is shortened, the detection frequency is improved, and the detection frequencies of the rainfall and the displacement are positively correlated. For example, if the rainfall exceeds a first preset value, the detection frequency is increased to a first level; and if the rainfall exceeds a second preset value, the detection frequency is increased to a second level. The period of the second stage detection frequency is smaller than that of the first stage.
The technical solutions of the present invention will be clearly and completely described in connection with preferred embodiments, and the described embodiments are only some of the embodiments of the present invention.
Example 1: FIG. 4 is a plan view of the layout of the intelligent monitoring sensor for the tailor's rock landslide. The intelligent monitoring and early warning system provided by the invention is used for monitoring and early warning the tailor rock landslide.
The tailor's rock landslide is a rock ancient landslide, is located in low mountain gorge valley district, and loose bank river right bank, natural slope is 10 ~ 35. The lithology of the main stratum is a completely new system slope residual layer (Q) 4 dl+el ) Landslide accumulation (Q) 4 del ) Layer of slope collapse (Q) 4 dl+dol ) The method comprises the steps of carrying out a first treatment on the surface of the The bedrock is the Shaxi temple group (J) on the dwarfism system 2 s) mudstone and sandstone, and the occurrence is N45 DEG E/10-20 DEG NW. The length of the main shaft of the landslide is about 460m, the width is about 90-100 m, the thickness of the sliding body is about 10-35 m, and the volume is about 120 multiplied by 10 4 m 3 Belongs to a huge ancient landslide, and the main shaft direction is about 270 degrees. From the 60 s of the 20 th century, the soil body at the front part of the slope is subjected to creep deformation such as pulling crack, partial collapse, water leakage of the fish pond and the like. In 1998, 2007 and 2014, the slope has the deformation aggravating phenomenon, and strong deformation characteristics such as ground cracking, local collapse and the like appear in the middle and front parts of the slope. The landslide is destroyed and unstably in 28 days of 6 months of 2016, and Z-shaped arc-shaped stretching cracks with the width of about 50m, the depth of 30m and the length of about 250m are formed at the rear edge, so that the operation of Chuan Qian railways and the life and property safety of local residents are caused.
In order to further obtain the deformation damage trend of the tailor-made landslide, the railway emergency and operation safety are ensured, and the life and property safety of local residents are ensured, so that intelligent monitoring and early warning are carried out on the landslide. A group of deep displacement meters and a water level meter are respectively arranged along the front part, the middle part and the rear part of the landslide main shaft for monitoring, and an earth surface displacement meter is arranged at the rear edge of the landslide for monitoring the accumulated deformation of the deep part and the earth surface of the landslide body and the change of the underground water level. And a rain gauge is arranged in a slope body structure stable area at the rear edge of the landslide so as to monitor the change of the rain, and meanwhile, the on-site sampling frequency is controlled, and the specific arrangement is shown in fig. 4 and fig. 5.
And arranging a collector slave station at the corresponding position of the sensor, and arranging a collector master station at the stable position of the rear edge of the landslide.
The intelligent monitoring accumulated displacement-time curve and filtering curve of the tailor's landslide are shown in figure 6, and the intelligent early warning grade of the landslide is shown in figure 7.
By analyzing the curve characteristics, the landslide is affected by heavy rainfall in 2016 month 9, the groundwater level is swelled for 0.8m, the accumulated displacement for 3 days is 20mm, the deformation rate is 6.7mm/d, and the early warning level is a dangerous level. Later, the landslide deformation rate is reduced by about 0.16.7mm/d, and the landslide deformation rate tends to be stable, and basically can be judged to be in a constant-speed deformation stage.
Claims (2)
1. The intelligent monitoring and early warning system for the creep type landslide is characterized by comprising a server, a sensor and an information transmission part,
the sensor and the server form communication connection through an information transmission part,
the sensor comprises a displacement sensor and a rainfall sensor,
the server comprises a tangential angle data processing module and an early warning module, wherein the tangential angle data processing module is used for calculating a tangential angle according to displacement data and judging whether to send out early warning according to whether the tangential angle exceeds a threshold value;
the tangential angle data processing module is judged in the following manner:
according to the formulaCalculating the critical slip tangential angle alpha Max If the current tangential angle is larger than the critical tangential angle, giving an early warning;
current tangential angle alpha i The calculation mode of (a) is as follows:
wherein delta epsilon (i) is the sliding slope displacement in the current monitoring period,
at the same rate of deformation at a constant rate,
t i for the current moment of monitoring,
t i-1 at t i Is a previous monitoring instant of time (a).
2. The intelligent creep type landslide monitoring and early warning system of claim 1, wherein the server further comprises a rainfall data storage, and the rainfall data storage is connected with the tangential angle data processing module.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710664056.0A CN109389807B (en) | 2017-08-06 | 2017-08-06 | Intelligent monitoring and early warning system for creep type landslide |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201710664056.0A CN109389807B (en) | 2017-08-06 | 2017-08-06 | Intelligent monitoring and early warning system for creep type landslide |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109389807A CN109389807A (en) | 2019-02-26 |
| CN109389807B true CN109389807B (en) | 2023-09-26 |
Family
ID=65413002
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201710664056.0A Active CN109389807B (en) | 2017-08-06 | 2017-08-06 | Intelligent monitoring and early warning system for creep type landslide |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109389807B (en) |
Families Citing this family (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110149601B (en) * | 2019-05-15 | 2021-08-03 | 青岛农业大学 | Data assembly method for big data communication of Beidou short message |
| CN110166958B (en) * | 2019-05-15 | 2021-11-09 | 青岛农业大学 | Method for carrying out big data communication by using Beidou short message |
| CN110149600B (en) * | 2019-05-15 | 2021-09-03 | 青岛农业大学 | Communication method based on Beidou system |
| CN110879053A (en) * | 2019-12-20 | 2020-03-13 | 湖北楚航电子科技有限公司 | Multi-sensor integrated automatic slope deformation monitoring device |
| CN111259605B (en) * | 2020-02-14 | 2023-04-07 | 中铁二院工程集团有限责任公司 | Soil landslide monitoring, early warning and evaluating method |
| CN111947605B (en) * | 2020-08-20 | 2023-05-09 | 上海同禾工程科技股份有限公司 | Slope safety monitoring system and monitoring method thereof |
| CN115035690A (en) * | 2021-03-05 | 2022-09-09 | 重庆市地质灾害防治中心 | Geological disaster monitoring and early warning method |
| CN114333249A (en) * | 2022-01-14 | 2022-04-12 | 四川九洲北斗导航与位置服务有限公司 | Landslide early warning method and device |
| CN114659442A (en) * | 2022-03-10 | 2022-06-24 | 北京愚公道路养护有限公司 | Visual slope deformation intelligent monitoring and early warning system |
| CN115376284B (en) * | 2022-08-23 | 2023-08-18 | 辽宁工程技术大学 | Sliding surface identification and landslide early warning method based on surface and deep displacement monitoring |
| CN115240371B (en) * | 2022-09-23 | 2023-01-10 | 西北大学 | Mountain landslide real-time monitoring system based on data analysis |
| CN115638767B (en) * | 2022-11-07 | 2023-10-03 | 北京航空航天大学合肥创新研究院(北京航空航天大学合肥研究生院) | Ground subsidence monitoring method |
| CN115854854A (en) * | 2022-12-26 | 2023-03-28 | 中国科学院西北生态环境资源研究院 | Multi-physical-field permafrost region landslide monitoring system and monitoring method |
| CN115798181B (en) * | 2023-02-08 | 2023-04-25 | 西南交通大学 | Landslide early warning method, device, equipment and medium based on declination ratio |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2003214812A (en) * | 2001-11-19 | 2003-07-30 | Yoshikazu Hayakawa | Method for quantitatively measuring displacement of landslide layer |
| CN102013150A (en) * | 2010-09-28 | 2011-04-13 | 浙江工业大学 | System for predicting geologic hazard based on rainfall intensity, moisture content of slope soil and deformation |
| CN103646181A (en) * | 2013-12-20 | 2014-03-19 | 青岛理工大学 | Determination method for stability coefficient and early warning criterion of creeping type artificial slope |
| CN104615846A (en) * | 2014-12-14 | 2015-05-13 | 励春亚 | Wavelet recognition method for landslide deformation sudden change abnormity |
| CN106599372A (en) * | 2016-11-18 | 2017-04-26 | 中国电建集团成都勘测设计研究院有限公司 | Method for determining angle of contingence of displacement time curve in slope deformation stage |
-
2017
- 2017-08-06 CN CN201710664056.0A patent/CN109389807B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2003214812A (en) * | 2001-11-19 | 2003-07-30 | Yoshikazu Hayakawa | Method for quantitatively measuring displacement of landslide layer |
| CN102013150A (en) * | 2010-09-28 | 2011-04-13 | 浙江工业大学 | System for predicting geologic hazard based on rainfall intensity, moisture content of slope soil and deformation |
| CN103646181A (en) * | 2013-12-20 | 2014-03-19 | 青岛理工大学 | Determination method for stability coefficient and early warning criterion of creeping type artificial slope |
| CN104615846A (en) * | 2014-12-14 | 2015-05-13 | 励春亚 | Wavelet recognition method for landslide deformation sudden change abnormity |
| CN106599372A (en) * | 2016-11-18 | 2017-04-26 | 中国电建集团成都勘测设计研究院有限公司 | Method for determining angle of contingence of displacement time curve in slope deformation stage |
Non-Patent Citations (1)
| Title |
|---|
| 重大突发性滑坡灾害预测预报研究;曾裕平;《中国博士学位论文全文数据库基础科学辑》;全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN109389807A (en) | 2019-02-26 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109389807B (en) | Intelligent monitoring and early warning system for creep type landslide | |
| CN102943459B (en) | Remote smart monitoring and three-dimensional early warning method and system for deformation stability of deep foundation pit | |
| CN103743441B (en) | The polynary of a kind of side slope safety is coupling in line monitoring system and method | |
| CN101477207B (en) | Intelligent geological calamity synthetic monitoring system and multi-stage prediction analysis method | |
| CN101118687A (en) | System and method for real time remote wireless monitoring slope landslide | |
| CN208027544U (en) | Landslide monitoring early warning system | |
| CN102979071B (en) | Remote intelligent monitoring and three-dimensional early warning method and system for stress stability of deep foundation pit | |
| CN103646157B (en) | Method for evaluating transmission line fault caused by rainstorm | |
| CN103810524A (en) | Method for predicting ground subsidence in underground metro construction process | |
| CN104834012B (en) | Electromagnetic radiation monitoring early warning method of mine roof water inrush | |
| CN202925536U (en) | Deep foundation pit stress stability remote intelligent monitoring and three-dimensional early-warning system | |
| CN103471647A (en) | Long-distance automatic monitoring method for shield tunnel | |
| CN110487243A (en) | A kind of airfield runway sedimentation monitoring system and its laying and application method | |
| CN202969361U (en) | Remote intelligent monitoring and three-dimensional pre-warning system for deformation stability of deep foundation pit | |
| CN103061322B (en) | Deep foundation ditch stability remote intelligent monitoring 3-dimensional digital comprehensive pre-warning method and system | |
| CN203034434U (en) | Remote intelligent monitoring three-dimensional digital comprehensive early warning system for stability of deep foundation pit | |
| CN111489526A (en) | Loess landslide monitoring and early warning system and method based on wireless sensor network | |
| CN103046525A (en) | Facility and method for mechanical stability remote intelligent monitoring and three-dimensional early warning of deep foundation pit | |
| CN202706066U (en) | An online monitoring system for a high-altitude tundra power transmission line iron tower base | |
| CN109889600A (en) | A kind of groundwater in arid region matter monitoring device | |
| CN209085710U (en) | A kind of online remote supervision system of drainage pipeline networks liquid level | |
| CN116337001A (en) | Goaf high-speed railway roadbed settlement monitoring and early warning system and goaf high-speed railway roadbed settlement monitoring and early warning method | |
| CN203587544U (en) | Landslide monitoring sensor | |
| CN208172969U (en) | A kind of high slope surface deformation monitoring and warning system | |
| CN210351669U (en) | Mountain landslide monitoring and early warning system based on wireless sensor network |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |