CN113899405A - Integrated online slope intelligent monitoring and early warning system and early warning method - Google Patents
Integrated online slope intelligent monitoring and early warning system and early warning method Download PDFInfo
- Publication number
- CN113899405A CN113899405A CN202111218179.4A CN202111218179A CN113899405A CN 113899405 A CN113899405 A CN 113899405A CN 202111218179 A CN202111218179 A CN 202111218179A CN 113899405 A CN113899405 A CN 113899405A
- Authority
- CN
- China
- Prior art keywords
- monitoring
- module
- early warning
- coordinate system
- 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.)
- Pending
Links
- 238000012544 monitoring process Methods 0.000 title claims abstract description 132
- 238000000034 method Methods 0.000 title claims description 26
- 238000006073 displacement reaction Methods 0.000 claims abstract description 58
- 238000004891 communication Methods 0.000 claims abstract description 9
- 230000010354 integration Effects 0.000 claims abstract description 5
- 238000006243 chemical reaction Methods 0.000 claims description 17
- 238000013519 translation Methods 0.000 claims description 6
- 238000012806 monitoring device Methods 0.000 claims description 5
- 230000004913 activation Effects 0.000 claims 2
- 230000007547 defect Effects 0.000 abstract description 3
- 238000011161 development Methods 0.000 abstract description 3
- 239000003245 coal Substances 0.000 abstract description 2
- 238000012545 processing Methods 0.000 description 10
- 230000006698 induction Effects 0.000 description 7
- 230000005540 biological transmission Effects 0.000 description 5
- 238000004458 analytical method Methods 0.000 description 4
- 238000007726 management method Methods 0.000 description 4
- 230000004927 fusion Effects 0.000 description 3
- 238000012937 correction Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 238000004519 manufacturing process Methods 0.000 description 2
- 238000005065 mining Methods 0.000 description 2
- 238000012351 Integrated analysis Methods 0.000 description 1
- 230000001133 acceleration Effects 0.000 description 1
- 238000013473 artificial intelligence Methods 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
- 238000013079 data visualisation Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000012423 maintenance Methods 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 239000011435 rock Substances 0.000 description 1
- 238000012216 screening Methods 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
- 238000012800 visualization Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/88—Radar or analogous systems specially adapted for specific applications
- G01S13/886—Radar or analogous systems specially adapted for specific applications for alarm systems
-
- 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
- G08B21/18—Status alarms
- G08B21/182—Level alarms, e.g. alarms responsive to variables exceeding a threshold
-
- 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
- G08B21/18—Status alarms
- G08B21/24—Reminder alarms, e.g. anti-loss alarms
Landscapes
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Business, Economics & Management (AREA)
- Emergency Management (AREA)
- Electromagnetism (AREA)
- Computer Networks & Wireless Communication (AREA)
- Radar Systems Or Details Thereof (AREA)
- Emergency Alarm Devices (AREA)
Abstract
The invention discloses an integrated online slope intelligent monitoring and early warning system, which is characterized in that: including side slope radar module, unmanned aerial vehicle module, earth's surface displacement monitoring module and deep displacement monitoring module, still including monitoring early warning platform, the communication is connected between monitoring early warning platform and each module to in leading-in the unified world coordinate system with the monitoring data of each module. The system generates a model through integration of a coordinate system, and outputs signal prompts of various levels and arrangement of monitoring means through monitoring displacement change of points in the model. The scheme can optimize and integrate the defects of the existing independent monitoring system in the aspect of solving the intelligent side slope monitoring of the strip mine, provides effective technical support for the implementation of intelligent mines, and really achieves efficient and intensive intelligent development of coal mines.
Description
Technical Field
The invention relates to the technical field of strip mine slope engineering, in particular to an integrated online slope intelligent monitoring and early warning system and an early warning method.
Background
The deformation monitoring of strip mine side slopes is always an important work of safe production of mines, usually, a ground surface displacement monitoring system (GNSS) is adopted to monitor the displacement of each side slope, only anchor cables are added to the strip mine with poor geological conditions for monitoring the displacement change of deep rock masses, and the index-yielding capability of the strip mine with a synthetic aperture radar and a real aperture radar is adopted. Although the synthetic aperture radar can achieve all-weather, high-resolution and continuous space coverage characteristics, the synthetic aperture radar only forecasts geological disasters such as ground settlement and landslide, and for the strip mine with high mining speed, the synthetic aperture radar cannot monitor displacement variation caused by deep stratum stress-strain variation brought by mining.
Therefore, the slope monitoring of the strip mine only carries out a point or point-surface independent displacement monitoring system on the slope which possibly has potential safety hazards. Because interfaces of different equipment manufacturers are not uniform, respective data systems and service logics exist, and the problems that interconnection and intercommunication cannot be achieved among information systems, data sharing and circulation are not smooth and the like are caused, namely the problem that system linkage and cooperation are difficult. Various types of monitoring systems cannot be intelligently converted, fused and resolved, data cannot be in a unified format and can be uploaded, summarized and summarized in time, mass data cannot be subjected to integrated analysis and modeling through the Internet means, the release of data value is seriously influenced, and finally real-time monitoring of whole fusion of the strip mine slope space cannot be formed. Meanwhile, an integrated software platform of a monitoring and early warning system is not available at present, data are subjected to hierarchical processing, automatic induction, threshold value setting and early warning, and the requirement of the state on intelligent mines cannot be met.
Disclosure of Invention
In view of the defects of the existing slope monitoring technology, through research, the invention aims to provide a slope monitoring and early warning system capable of realizing intelligent conversion and hierarchical induction, solve the problems that data of each monitoring system is incompatible and cannot be converted and the like, and finally establish an integrated online slope intelligent monitoring and early warning system capable of realizing intelligent conversion and hierarchical induction.
The invention is realized by the following technical scheme:
integration online side slope intelligent monitoring early warning system, its characterized in that: including side slope radar module, unmanned aerial vehicle module, earth's surface displacement monitoring module and deep displacement monitoring module, still including monitoring early warning platform, the communication is connected between monitoring early warning platform and each module to in leading-in the unified world coordinate system with the monitoring data of each module.
The invention also provides an integrated online slope intelligent monitoring and early warning method, which is characterized by comprising the following steps: the method comprises the following steps:
step 1, respectively connecting a slope radar module, an unmanned aerial vehicle module, a ground surface displacement monitoring module and a deep displacement monitoring module with a monitoring and early warning platform in a communication manner, and receiving monitoring data of each module;
(1) converting a world coordinate system and an unmanned aerial vehicle coordinate system:
wherein X, Y, Z is a coordinate value, c is an unmanned aerial vehicle, w is a world coordinate system, and T is a three-dimensional translation vector; m1 is a rotation and translation coefficient of two coordinate systems;
(2) world and radar coordinate system conversion:
wherein: r is the radius range between the monitoring target and the monitoring equipment; h is the plane distance, Z0Is an initial coordinate, and alpha is an included angle between the target point and the Z axis;
(3) unmanned aerial vehicle and radar coordinate system conversion:
wherein f is the focal length;
wherein: k. p is a distortion coefficient;
and 4, converting the image and the pixel coordinate system:
wherein u and v are transformed coordinates;
wherein S is a displacement amount, BXTThe coordinate position is T time;
and 6, comparing the data with a set value, and judging the safety level according to the comparison result.
Further, step 7 is included, according to the judged safety level, corresponding output is carried out.
Further, before step 1, the method further comprises a pre-step, specifically as follows:
pre-step 1: connecting each monitoring device to a computer through a wireless network, so that the devices can upload information to the computer, and the computer can control the devices;
a pre-step 2: determining the size of the strip mine through radar ranging, and generating a simple strip mine model;
a pre-step 3: manually determining the range of the dangerous surface; determining the minimum number of monitoring equipment, the optimal number of monitoring equipment and the position of the monitoring equipment according to the strip mine information;
a front step 4: dividing the scanning area of the monitoring equipment, automatically controlling the scanning frequency and setting parameter values corresponding to different alarm levels.
Further, the data collected by the surface displacement monitoring module and the deep displacement monitoring module are integrated into a pixel coordinate system after being processed in the steps 3 and 4.
Further, the safety level comprises a safety level, a warning level, a danger level and an alarm level.
Further, the output include slope radar module, unmanned aerial vehicle module, earth's surface displacement monitoring module and deep displacement monitoring module open and the frequency of opening.
Compared with the prior art, the invention has the advantages that: the scheme can optimize and integrate the defects of the existing independent monitoring system in the aspect of solving the intelligent side slope monitoring of the strip mine, provides effective technical support for the implementation of intelligent mines, and really achieves efficient and intensive intelligent development of coal mines.
Drawings
The invention is further described below with reference to the accompanying drawings.
Fig. 1 is a schematic view of the overall structure of the present invention.
Detailed Description
As shown in figure 1, the invention discloses an integrated online slope intelligent monitoring and early warning system, which is characterized in that: including side slope radar module, unmanned aerial vehicle module, earth's surface displacement monitoring module and deep displacement monitoring module, still including monitoring early warning platform, the communication is connected between monitoring early warning platform and each module to in leading-in the unified world coordinate system with the monitoring data of each module.
Preferably, the system further comprises a satellite in communication connection with each module.
The invention also discloses an integrated online slope intelligent monitoring and early warning method, which is characterized by comprising the following steps: the method comprises the following steps:
step 1, respectively connecting a slope radar module, an unmanned aerial vehicle module, a ground surface displacement monitoring module and a deep displacement monitoring module with a monitoring and early warning platform in a communication manner, and receiving monitoring data of each module;
(1) converting a world coordinate system and an unmanned aerial vehicle coordinate system:
wherein X, Y, Z is a coordinate value, c is an unmanned aerial vehicle, w is a world coordinate system, and T is a three-dimensional translation vector; m1 is a rotation and translation coefficient of two coordinate systems;
(2) world and radar coordinate system conversion:
wherein: r is the radius range between the monitoring target and the monitoring equipment; h is the plane distance, Z0Is an initial coordinate, and alpha is an included angle between the target point and the Z axis;
(3) unmanned aerial vehicle and radar coordinate system conversion:
wherein f is the focal length;
wherein: k. p is a distortion coefficient; the distortion vector is a five-dimensional vector comprising k1、k2、k3、p1、p2After the monitored terrain is determined, each coefficient is a constant and can be calculated according to the specific terrain;
and 4, converting the image and the pixel coordinate system:
wherein u and v are transformed coordinates;
wherein S is a displacement amount, BXTThe coordinate position is T time;
and 6, comparing the data with a set value, and judging the safety level according to the comparison result.
Preferably, the method further comprises a step 7 of outputting corresponding according to the judged safety level, wherein the output comprises the opening frequency and the opening frequency of the slope radar module, the unmanned aerial vehicle module, the earth surface displacement monitoring module and the deep displacement monitoring module.
Preferably, a pre-step is further included before step 1, specifically as follows:
pre-step 1: connecting each monitoring device to a computer through a wireless network, so that the devices can upload information to the computer, and the computer can control the devices;
a pre-step 2: determining the size of the strip mine through radar ranging, and generating a simple strip mine model;
a pre-step 3: manually determining the range of the dangerous surface; determining the minimum number of monitoring equipment, the optimal number of monitoring equipment and the position of the monitoring equipment according to the strip mine information;
a front step 4: dividing the scanning area of the monitoring equipment, automatically controlling the scanning frequency and setting parameter values corresponding to different alarm levels.
Preferably, the data collected by the surface displacement monitoring module and the deep displacement monitoring module are integrated into a pixel coordinate system after being processed in the steps 3 and 4.
Preferably, the safety level comprises a safety level, a warning level, a danger level and an alarm level.
Examples
This embodiment online side slope intelligent monitoring early warning system of integration includes:
1. acquisition, intelligent conversion and visualization processing of monitoring data
According to the slope radar 1, the unmanned aerial vehicle 2, the earth surface displacement monitoring 3 and the deep displacement monitoring 4 systems in the figure 1, the data acquisition channels independent of the monitoring systems are used for uploading to the server through the wireless network. Meanwhile, according to the difference of the transmission interfaces of the independent monitoring systems, the data transmitted to the server can be automatically downloaded to the platform through the multifunctional data transmission interface provided by the monitoring and early warning platform, and the data are intelligently converted into a platform compatible format. The user can select the functional items in the system management according to actual conditions. Wherein a satellite 5 may also be provided in communication with each module.
The early warning system of the embodiment, the early warning method thereof, specifically operates as follows:
the method comprises the following steps: the monitoring devices are integrated into a unified coordinate system through the following steps, and conversion among five coordinate systems including a world coordinate system, an unmanned aerial vehicle coordinate system, a camera coordinate system, an image coordinate system and a pixel coordinate system is involved.
(1) Converting a world coordinate system and an unmanned aerial vehicle coordinate system:
(2) unmanned aerial vehicle and camera coordinate system conversion:
wherein: r is the radius range between the monitoring target and the monitoring equipment; h is the plane distance.
(3) And (3) converting a camera and an image coordinate system:
(4) using image distortion removal:
wherein: k. p is a distortion coefficient. The distortion vector is a five-dimensional vector comprising k1、k2、k3、p1、p2。
(5) Image and pixel coordinate system conversion:
step two: calculating the displacement of each point of the slope by an image difference method, wherein the mathematical expression is as follows:
and gives the position displacement vector and velocity.
Step three: and importing monitoring data into a computer, integrating the monitoring data after the coordinate system is converted through a formula I to a formula V, removing errors, and generating a data visualization interface. The method comprises the following steps: the method comprises the steps of real-time slope three-dimensional live-action models, slope displacement cloud pictures, slope displacement vector pictures, slope speed cloud pictures, slope stratum deep stress strain cloud pictures and the like. The slope model can be amplified and details can be checked; the side slope model can be cut into sections and the side slope section model can be checked; the displacement change and the speed change of the slope at a certain point in a period of time can be checked.
2. Hierarchical processing, automatic induction management
The system has the functions of hierarchical processing and automatic induction management, can reflect the data of displacement variation of the monitored object according to different monitoring systems, hierarchically process the monitoring data obtained by the different monitoring systems, and provide reliable basic data for automatically setting monitoring limit threshold values.
Monitoring change data in the monitoring and early warning platform are displayed visually by using a curve; the monitoring and early warning platform is provided with a displacement deformation and acceleration analysis system, a historical data query system, a grading processing system, an automatic induction system and a grading automatic early warning system. The monitoring structure diagram, the monitoring point layout diagram and the like can be displayed, and the platform storage module can store mass data.
Through analysis of the curve, a reasonable alarm threshold value is given and set in the platform, and the computer performs classification processing on the region according to the monitored information. The information may be displacement of a point, velocity or a combination of displacement and velocity, such as displacement multiplied by velocity. See table 1 for details.
The classified and summarized data are downloaded to a mobile phone or a computer terminal, the data are intelligently analyzed, parameters such as monitoring limit threshold values, change rates and displacement vector changes are automatically set according to program steps, the system automatically judges dangerous areas, a series of manual operations are omitted, the situations that execution work is not in place are avoided, the intelligent level of slope monitoring is improved, and the production operation efficiency is improved.
The platform storage module can automatically summarize and sort the monitoring data, images and the like according to categories and time, and provides functions of historical data query and download. If the red alarm occurs, the platform can apply for uploading authorized basic information to the cloud, so that big data sorting and intelligent analysis are facilitated, and references are provided for automatic setting of warning threshold values and other artificial intelligence functions of a computer in the future.
3. Hierarchical automatic early warning and information push
The monitoring and early warning platform has a grading automatic early warning function, can set alarm parameters of different grades according to different monitored objects of the system, and can send the alarm parameters to related personnel in a network transmission mode. The specific operation is as follows:
the method comprises the following steps: each monitoring device is connected to a computer through a wireless network, the devices can upload information to the computer, and the computer can control the devices.
Step two: and (4) radar ranging, determining the size of the strip mine, and generating a simple model of the strip mine.
Step three: and manually determining the range of the dangerous surface, and determining the minimum number of monitoring equipment, the optimal number of monitoring equipment and the position arrangement of the monitoring equipment by the computer according to the information of the strip mine.
Step four: the computer automatically divides the scanning area of the monitoring equipment, automatically controls the scanning frequency, prompts the increase and decrease of the equipment and the like according to the information of the strip mine.
By monitoring the deformation development trend of the deformation body and combining multi-parameter early warning correction analysis, overrun automatic early warning is carried out, so that the early warning accuracy is guaranteed, and false alarms are reduced. The monitoring and early warning platform can be connected in real time through a mobile phone network, and deformation data and early warning states can be displayed in real time.
This scheme is resolved through multisource data interface's intelligent conversion and fusion, optimizes the integration with technical equipment such as slope radar, unmanned aerial vehicle, earth's surface displacement monitoring and deep displacement monitoring, and slope radar realizes data intelligent conversion with oblique photography module or radar that unmanned aerial vehicle carried on, and integrated "earth's surface displacement and deep level displacement integrated monitoring system" simultaneously accomplishes acquireing, intelligent conversion, stage treatment, the automatic management that sums up, automatic early warning etc. to the monitoring data. The monitoring and early warning platform supports the identification and correction of true three-dimensional monitoring images and can realize multi-polarization, multi-wave band and multi-working mode for the slope radar. The unmanned aerial vehicle has the functions of accurate three-dimensional air route planning, three-dimensional real-time flight monitoring, visual monitoring and the like, and can provide cloud services such as intelligent maintenance and information pushing. The slope monitoring multi-source data fusion calculation is completed through the intelligent data conversion and transmission of the multi-monitoring system, and an integrated online slope intelligent monitoring early warning system capable of realizing intelligent conversion and hierarchical induction is formed. The system realizes the functions of clustering, local area network connection, inter-group sharing and the like. The data processing method has the function of processing the acquired data in blocks, so that the dependence of data processing on the storage space of a host can be reduced, the frequent transmission of the data is reduced, and the data processing efficiency is improved. Under the control of the monitoring and early warning platform, the results of the data can be partitioned and combined, so that the screening and eliminating requirements of a large amount of data are met. And meanwhile, cluster resources are fully utilized to meet the functional requirements of multi-project and multi-task priority processing.
Claims (8)
1. Integration online side slope intelligent monitoring early warning system, its characterized in that: including side slope radar module, unmanned aerial vehicle module, earth's surface displacement monitoring module and deep displacement monitoring module, still including monitoring early warning platform, the communication is connected between monitoring early warning platform and each module to in leading-in the unified world coordinate system with the monitoring data of each module.
2. An integrated online slope intelligent monitoring and early warning method is characterized in that: the method comprises the following steps:
step 1, respectively connecting a slope radar module, an unmanned aerial vehicle module, a ground surface displacement monitoring module and a deep displacement monitoring module with a monitoring and early warning platform in a communication manner, and receiving monitoring data of each module;
step 2, converting the data acquired by each module, specifically as follows:
(1) converting a world coordinate system and an unmanned aerial vehicle coordinate system:
wherein X, Y, Z is a coordinate value, c is an unmanned aerial vehicle, w is a world coordinate system, and T is a three-dimensional translation vector; m1 is a rotation and translation coefficient of two coordinate systems;
(2) world and radar coordinate system conversion:
wherein: r is the radius range between the monitoring target and the monitoring equipment; h is the plane distance, Z0Is an initial coordinate, and alpha is an included angle between the target point and the Z axis;
(3) unmanned aerial vehicle and radar coordinate system conversion:
wherein f is the focal length;
step 3, using image distortion removal for the acquired data:
wherein: k. p is a distortion coefficient;
and 4, converting the image and the pixel coordinate system:
wherein u and v are transformed coordinates;
step 5, calculating the displacement of each selected point of the slope by an image difference method, and calculating a position vector and a displacement speed:
wherein S is a displacement amount, BXTThe coordinate position is T time;
and 6, comparing the data with a set value, and judging the safety level according to the comparison result.
3. The method according to claim 2, further comprising a step 7 of performing a corresponding output according to the determined security level.
4. The method according to claim 2, characterized by further comprising a preceding step before step 1, in particular as follows:
pre-step 1: connecting each monitoring device to a computer through a wireless network, so that the devices can upload information to the computer, and the computer can control the devices;
a pre-step 2: determining the size of the strip mine through radar ranging, and generating a simple strip mine model;
a pre-step 3: manually determining the range of the dangerous surface; determining the minimum number of monitoring equipment, the optimal number of monitoring equipment and the position of the monitoring equipment according to the strip mine information;
a front step 4: dividing the scanning area of the monitoring equipment, automatically controlling the scanning frequency and setting parameter values corresponding to different alarm levels.
5. The method of claim 2, wherein the data collected by the surface displacement monitoring module and the deep displacement monitoring module are integrated into a pixel coordinate system after being processed by the steps 3 and 4.
6. The method of claim 2, wherein the security level comprises a security level, an alert level, a hazard level, and an alarm level.
7. The method of claim 3, wherein the output includes the activation of the slope radar module, the drone module, the surface displacement monitoring module, and the deep displacement monitoring module and the frequency of activation.
8. The system of claim 1, further comprising a satellite communicatively coupled to each module.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111218179.4A CN113899405A (en) | 2021-10-20 | 2021-10-20 | Integrated online slope intelligent monitoring and early warning system and early warning method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111218179.4A CN113899405A (en) | 2021-10-20 | 2021-10-20 | Integrated online slope intelligent monitoring and early warning system and early warning method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN113899405A true CN113899405A (en) | 2022-01-07 |
Family
ID=79192864
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111218179.4A Pending CN113899405A (en) | 2021-10-20 | 2021-10-20 | Integrated online slope intelligent monitoring and early warning system and early warning method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113899405A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115050163A (en) * | 2022-06-15 | 2022-09-13 | 中铁第四勘察设计院集团有限公司 | Slope monitoring and early warning system |
| CN116596381A (en) * | 2023-05-18 | 2023-08-15 | 中国自然资源航空物探遥感中心 | Underground mining mine environment evaluation system based on remote sensing image |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105957311A (en) * | 2016-06-01 | 2016-09-21 | 中国水利水电科学研究院 | Adaptive expansion slope stability intelligent monitoring early warning system |
| CN110307790A (en) * | 2019-07-04 | 2019-10-08 | 深圳市富源信息技术有限公司 | Camera shooting machine detecting device and method applied to safety monitoring slope |
| CN111752825A (en) * | 2020-05-26 | 2020-10-09 | 江苏大学 | Plug-and-play software platform for intelligent electric vehicle and detection method thereof |
| US20210048294A1 (en) * | 2019-08-15 | 2021-02-18 | China Institute Of Water Resources And Hydropower Research | System and method for monitoring deformation of dam slope |
| CN112562405A (en) * | 2020-11-27 | 2021-03-26 | 山东高速建设管理集团有限公司 | Radar video intelligent fusion and early warning method and system |
| CN112711033A (en) * | 2020-12-09 | 2021-04-27 | 中科视语(北京)科技有限公司 | Slope safety monitoring and early warning device and method |
| CN112857246A (en) * | 2021-02-05 | 2021-05-28 | 中国矿业大学(北京) | Strip mine slope deformation online monitoring method utilizing ground three-eye video matching |
| CN112967501A (en) * | 2021-02-23 | 2021-06-15 | 长安大学 | Early warning system and method for dangerous driving-off behavior of vehicles on ramp |
| CN113156421A (en) * | 2021-04-07 | 2021-07-23 | 南京邮电大学 | Obstacle detection method based on information fusion of millimeter wave radar and camera |
| CN113340192A (en) * | 2021-05-27 | 2021-09-03 | 长沙理工大学 | Multi-technology combined slope surface deformation monitoring system and method |
-
2021
- 2021-10-20 CN CN202111218179.4A patent/CN113899405A/en active Pending
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105957311A (en) * | 2016-06-01 | 2016-09-21 | 中国水利水电科学研究院 | Adaptive expansion slope stability intelligent monitoring early warning system |
| CN110307790A (en) * | 2019-07-04 | 2019-10-08 | 深圳市富源信息技术有限公司 | Camera shooting machine detecting device and method applied to safety monitoring slope |
| US20210048294A1 (en) * | 2019-08-15 | 2021-02-18 | China Institute Of Water Resources And Hydropower Research | System and method for monitoring deformation of dam slope |
| CN111752825A (en) * | 2020-05-26 | 2020-10-09 | 江苏大学 | Plug-and-play software platform for intelligent electric vehicle and detection method thereof |
| CN112562405A (en) * | 2020-11-27 | 2021-03-26 | 山东高速建设管理集团有限公司 | Radar video intelligent fusion and early warning method and system |
| CN112711033A (en) * | 2020-12-09 | 2021-04-27 | 中科视语(北京)科技有限公司 | Slope safety monitoring and early warning device and method |
| CN112857246A (en) * | 2021-02-05 | 2021-05-28 | 中国矿业大学(北京) | Strip mine slope deformation online monitoring method utilizing ground three-eye video matching |
| CN112967501A (en) * | 2021-02-23 | 2021-06-15 | 长安大学 | Early warning system and method for dangerous driving-off behavior of vehicles on ramp |
| CN113156421A (en) * | 2021-04-07 | 2021-07-23 | 南京邮电大学 | Obstacle detection method based on information fusion of millimeter wave radar and camera |
| CN113340192A (en) * | 2021-05-27 | 2021-09-03 | 长沙理工大学 | Multi-technology combined slope surface deformation monitoring system and method |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115050163A (en) * | 2022-06-15 | 2022-09-13 | 中铁第四勘察设计院集团有限公司 | Slope monitoring and early warning system |
| CN115050163B (en) * | 2022-06-15 | 2023-10-03 | 中铁第四勘察设计院集团有限公司 | Slope monitoring and early warning system |
| CN116596381A (en) * | 2023-05-18 | 2023-08-15 | 中国自然资源航空物探遥感中心 | Underground mining mine environment evaluation system based on remote sensing image |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN111537515B (en) | Iron tower bolt defect display method and system based on three-dimensional live-action model | |
| CN110689705B (en) | Comprehensive application system for mine geological environment management | |
| Khan et al. | UAV-based traffic analysis: A universal guiding framework based on literature survey | |
| US9389084B1 (en) | Detecting changes in aerial images | |
| CN112256589B (en) | Simulation model training method and point cloud data generation method and device | |
| US20190130768A1 (en) | Aerial vehicle inspection path planning | |
| CN113899405A (en) | Integrated online slope intelligent monitoring and early warning system and early warning method | |
| CN111291697B (en) | Method and device for detecting obstacles | |
| CN110196454B (en) | Geological survey integrated system based on unmanned aerial vehicle | |
| CN107613248A (en) | Monitoring unmanned system and method based on BIM | |
| KR102414307B1 (en) | 3D map change area update system and method | |
| CN114419231B (en) | Traffic facility vector identification, extraction and analysis system based on point cloud data and AI technology | |
| CN111126873A (en) | Shield TBM big data platform system based on Hadoop cluster architecture and construction method | |
| CN115456206A (en) | BIM + GIS-based tunnel construction visual control method and system | |
| CN111866453A (en) | Barrier dam emergency monitoring and early warning method based on artificial intelligence and BIM | |
| CN114020043A (en) | Unmanned aerial vehicle building project supervision system and method, electronic equipment and storage medium | |
| EP3940666A1 (en) | Digital reconstruction method, apparatus, and system for traffic road | |
| CN112381041A (en) | Tree identification method and device for power transmission line and terminal equipment | |
| CN114783188A (en) | Inspection method and device | |
| CN116050277A (en) | Underground coal mine scene reality capturing sensing and simulating method and equipment | |
| CN116468869A (en) | Live-action three-dimensional modeling method, equipment and medium based on remote sensing satellite image | |
| CN115580708A (en) | Unmanned aerial vehicle inspection method for optical cable line | |
| CN116122356B (en) | Deep foundation pit safety monitoring system based on multi-model fusion | |
| CN114359494A (en) | Mining area three-dimensional map collecting and updating method and system | |
| CN114844925B (en) | Unmanned mine universe intelligent monitoring system |
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 |