CN116499427A - Intelligent early warning method for slope landslide - Google Patents
Intelligent early warning method for slope landslide Download PDFInfo
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- 238000012216 screening Methods 0.000 claims abstract description 9
- 239000011435 rock Substances 0.000 claims description 12
- 238000004519 manufacturing process Methods 0.000 claims description 9
- 238000005422 blasting Methods 0.000 claims description 6
- 230000008569 process Effects 0.000 claims description 5
- 238000009412 basement excavation Methods 0.000 claims description 4
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- 239000004575 stone Substances 0.000 description 1
- 208000024891 symptom Diseases 0.000 description 1
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N7/00—Television systems
- H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
- H04N7/181—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a plurality of remote sources
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01C—MEASURING DISTANCES, LEVELS OR BEARINGS; SURVEYING; NAVIGATION; GYROSCOPIC INSTRUMENTS; PHOTOGRAMMETRY OR VIDEOGRAMMETRY
- G01C11/00—Photogrammetry or videogrammetry, e.g. stereogrammetry; Photographic surveying
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- 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
- G01S13/86—Combinations of radar systems with non-radar systems, e.g. sonar, direction finder
- G01S13/867—Combination of radar systems with cameras
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- 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
- G01S13/885—Radar or analogous systems specially adapted for specific applications for ground probing
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- 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
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B31/00—Predictive alarm systems characterised by extrapolation or other computation using updated historic data
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N23/00—Cameras or camera modules comprising electronic image sensors; Control thereof
- H04N23/95—Computational photography systems, e.g. light-field imaging systems
- H04N23/951—Computational photography systems, e.g. light-field imaging systems by using two or more images to influence resolution, frame rate or aspect ratio
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N5/00—Details of television systems
- H04N5/222—Studio circuitry; Studio devices; Studio equipment
- H04N5/262—Studio circuits, e.g. for mixing, switching-over, change of character of image, other special effects ; Cameras specially adapted for the electronic generation of special effects
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Abstract
The invention discloses an intelligent early warning method for slope landslide, which comprises the following steps: a. acquiring high-definition surface slope orthographic images and terrain raster data; b. a slope radar is arranged opposite to the open slope; c. installing a camera capable of intelligently cruising on the 1 st camera; d. the number of cameras is increased, and panoramic photos of the early warning area are synthesized by using photos shot by i cameras; e. increasing the number of cameras according to the slope radar monitoring period; f. determining a three-dimensional coordinate range and a central three-dimensional coordinate of each photo coverage area; g. and screening historical and real-time photos of the visual angle corresponding to the early warning area, and screening interference factors of the area based on an image artificial intelligent algorithm to realize intelligent early warning. The invention establishes the mapping relation between the camera view angle and the mine slope three-dimensional coordinate based on computer vision, and utilizes the artificial intelligent image processing algorithm to rapidly verify the early warning information, thereby greatly improving the working efficiency and reducing the labor intensity of personnel.
Description
Technical Field
The invention relates to a method for carrying out intelligent early warning on landslide of a strip mine by utilizing a side slope radar and a camera, and belongs to the technical field of mining.
Background
Along with the gradual improvement of the situation of the safety production in China, people have higher and higher understanding and expectations on the safety, particularly along with the continuous and rapid development of mining industry in recent years, mine practitioners have quite large scale, the country has paid great attention to the safety production of the mine, and the slope landslide monitoring and early warning technology of the strip mine has rapidly developed. The side slope has symptoms before sliding, including the characteristics of cracking of the slope, rolling of broken stone, extrusion deformation of the side slope, and the like. At present, various domestic large mines generally adopt side slope radars to monitor the characteristics, and the side slope radars can monitor the side slope monitoring area in real time at all times, all weather, long distance, large range, continuous space coverage, non-contact, planar and submillimeter level. The basic principle of the side slope radar is based on the ground-based synthetic aperture radar differential interferometry (DInSAR). The high resolution is realized by utilizing pulse compression in the distance direction and by utilizing beam sharpening in the azimuth direction through the foundation synthetic aperture radar technology, so that a two-dimensional high resolution image of an observation area is obtained; and combining the two-dimensional high-resolution images of the same target region and sequences acquired at different time by using a differential interferometry technology, and inverting the phase difference of each pixel point in the images to obtain high-precision deformation information of the region to be detected. And then the network remote control system is utilized to realize automatic monitoring, and disaster early warning can be sent out when the deformation quantity, the deformation rate and the deformation acceleration of the side slope reach the set early warning threshold level. However, because numerous interference factors exist in the current open stope, such as mine production equipment and personnel, ground stress release and rock loosening caused by rock excavation, instantaneous loosening deformation of the rock caused by impact and vibration generated by blasting, rock change caused by drilling, production and transportation operations in the mine stope, radar system errors and the like, the interference factors cause higher false alarm rate when radar early warning is carried out according to a monitoring early warning threshold value, and the radar does not have an investigation function of accurately or not early warning information, a field technician is usually required to carry out one-by-one inspection on radar early warning areas, and the problems of low working efficiency and large verification workload exist, and a large amount of early warning false warning information brings heavy burden to production units and technicians.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides an intelligent early warning method for slope landslide, which is used for rapidly verifying early warning information, improving low working efficiency and reducing the labor intensity of verification personnel.
In order to achieve the above purpose, the invention adopts the following technical scheme:
an intelligent early warning method for slope landslide, comprising the following steps:
a. acquiring high-definition surface slope orthographic images and terrain raster data through unmanned aerial vehicle oblique photogrammetry, wherein any pixel of the surface slope orthographic images corresponds to the terrain raster data one by one;
b. installing a slope radar on the opposite side of the open slope, so that a monitoring area of the slope radar corresponds to a shooting range of the acquired high-definition open slope orthographic image;
c. install camera 1 st can intelligent cruising camera:
the method comprises the steps of installing a 1 st camera capable of intelligent cruising on the opposite side of an open side slope, obtaining 360-degree visual angle intelligent cruising shooting pictures of the open side slope, using n to represent the number of pictures, wherein each picture corresponds to one visual angle, manually deleting the visual angle covering a radar monitoring area in the n visual angles, and assuming m 1 And, in order of m 1 Numbering the viewing angles;
d. when the 1 st camera can not cover the early warning area, the number of cameras is increased, and the panoramic photos of the early warning area are synthesized by using the photos shot by the i cameras:
by m 1 Synthesizing panoramic photos of the early warning area by photos at each visual angle, checking whether an uncovered area exists, if so, installing a 2 nd intelligent cruising camera on the side slope of the uncovered area, and repeating the step c for the camera to obtain m 2 Photographs of the individual perspectives; repeating the above process until the ith camera is installed, and using m 1 +m 2 +...+m i D, synthesizing a complete slope panoramic photo by the photos at the individual visual angles, and stopping the step d;
e. increasing the number of cameras according to the slope radar monitoring period:
j is used for representing a monitoring period of the side slope radar, the time used by the 1 st to i th cameras for intelligently cruising all visual angles of the camera is recorded respectively, the time used by the k th camera is assumed to be T minutes, k=1, 2, …, i, and when T is the same as the time used by the k th camera>In j, supplementing an additional camera at the kth camera, wherein the additional camera and the kth camera are cruising for m respectively k Half of the view angles in the pictures until the time used by each camera is less than or equal to j, stopping supplementing the additional cameras, and finally utilizing m after p represents the total number of the additional cameras to supplement the additional cameras 1 +m 2 +...+m p The photos at the various visual angles synthesize a complete slope panoramic photo;
f. determining a three-dimensional coordinate range and a central three-dimensional coordinate of each photo coverage area:
let m 1 +m 2 +...+m p The photos of the individual visual angles are respectively matched with high-definition surface slope orthographic images by adopting a deep learning image matching algorithm, and the three-dimensional coordinate range and the central three-dimensional coordinate of each photo coverage area are determined by combining with the topographic raster data;
g. screening a history and real-time photo of a visual angle corresponding to the early warning area according to the early warning area preliminarily determined by the on-line monitoring of the slope radar, screening interference factors of the area based on an image artificial intelligent algorithm, and if the interference factors exist, giving an early warning error report; if no interference factors exist, a standby camera is called, the slope condition of the area is monitored in real time, and intelligent early warning is realized.
According to the intelligent early warning method for the side slope landslide, the interference factors comprise mine production equipment and personnel, ground stress release and rock mass relaxation caused by rock mass excavation, instantaneous loosening deformation of the rock mass caused by impact and vibration caused by blasting, and rock mass change caused by drilling, loading and transporting operations in a mine stope.
According to the invention, the mapping relation between the camera view angle and the mine slope three-dimensional coordinate is established based on computer vision, real-time and historical high-definition numerical images of the radar early warning area are automatically selected, early warning information is rapidly verified by using an artificial intelligent image processing algorithm, false alarm caused by interference factors is eliminated, the working efficiency is greatly improved, and the labor intensity of personnel is reduced.
Drawings
The invention will be described in further detail with reference to the drawings and the detailed description.
FIG. 1 is a schematic view of a 1 st camera intelligent cruise shooting;
FIG. 2 is a flow chart for determining camera position and number based on coverage;
FIG. 3 is a flow chart for increasing the number of cameras according to a side slope radar cruise cycle;
FIG. 4 is a flow chart of determining the three-dimensional coordinate range and center three-dimensional coordinate of each picture coverage area;
fig. 5 is a flow chart of the present invention.
Detailed Description
Aiming at the problems of high false alarm rate, low manual checking efficiency and the like of the current strip mine adopting a single means of slope radar for monitoring and early warning, the invention provides the intelligent slope landslide early warning method combining the slope radar with the camera.
In the daily monitoring and early warning process of the strip mine side slope radar, due to the interference of complex process links such as drilling, blasting, production, transportation and the like in a mine stope, radar system errors and the like, the early warning false alarm rate of the radar according to the monitoring and early warning threshold is higher.
The method comprises the following specific steps:
step one, acquiring high-definition surface slope orthographic images and terrain raster data through unmanned aerial vehicle oblique photogrammetry, wherein any pixel of the surface slope orthographic images corresponds to the terrain raster data one by one;
step two, installing a slope radar on the opposite side of the outdoor slope, so that a monitoring area of the slope radar corresponds to the shooting range of the obtained high-definition outdoor slope orthographic image;
step three, installing a 1 st high-definition far-focus intelligent cruising camera (which can be installed by using part of mines) opposite to the open side slope (near a radar room), acquiring 360-degree visual angle intelligent cruising shooting pictures of the open side slope, and using n metersShowing the number of pictures, wherein each picture corresponds to one view angle, manually deleting the view angle covering the radar monitoring area in the n view angles, and assuming m 1 And, in order of m 1 The individual views are numbered as shown in fig. 1.
Step four, utilizing m 1 Synthesizing panoramic photos of the early warning area by photos at each visual angle, checking whether an uncovered area exists, if so, installing a 2 nd intelligent cruising camera on the side slope of the uncovered area, and repeating the step c for the camera to obtain m 2 Photographs of the individual perspectives; repeating the above process until the ith camera is installed, and using m 1 +m 2 +...+m i The photos at the various visual angles are synthesized into a complete slope, and the step four is stopped;
fifthly, assuming that the monitoring period of the side slope radar is j minutes, respectively recording the time used by the 1 st to i th cameras for intelligently cruising all visual angles, assuming that the time used by the k th camera is T minutes, and k=1, 2, …, i, and when T is the same as the time used by the k th camera>In j, an additional camera is required to be supplemented at the position of the kth camera, and each cruising m of the additional camera and the kth camera is required to be supplemented k Half of the view angles in the pictures are used until the time used by each camera is less than or equal to j, the additional cameras are stopped to be supplemented, the total number of the cameras is p after the additional cameras are supplemented, and m is finally utilized 1 +m 2 +...+m p The photos at the individual visual angles synthesize a complete slope panoramic photo, so that the intelligent cruising period is consistent with the radar monitoring period;
step six, m is carried out 1 +m 2 +...+m p The photos of the individual visual angles are respectively matched with high-definition outdoor slope orthographic images by adopting a deep learning image matching algorithm, the three-dimensional coordinate range and the central three-dimensional coordinate of each photo coverage area are determined by combining with terrain raster data, and the post-period needs an artificial intelligence algorithm to capture the coordinate changes before and after the images, so as to check whether displacement occurs or not, thereby verifying the slope landslide early warning condition.
Step seven, timely screening histories and real-time photos covering the visual angle of the area according to the early warning area preliminarily determined by the on-line monitoring of the slope radar, screening interference factors such as personnel, equipment, blasting excavation (the training is completed by collecting photo data sets such as mine production equipment, personnel, blasting and the like in advance) of the area based on an image artificial intelligent algorithm, and then eliminating early warning errors; and calling a standby camera to monitor the slope condition of the area in real time without interference factors after the image screening, so as to realize intelligent early warning.
Unless otherwise defined, all terms used herein are intended to have the meanings commonly understood by those skilled in the art.
The described embodiments of the present invention are intended to be illustrative only and not to limit the scope of the invention, and various other alternatives, modifications, and improvements may be made by those skilled in the art within the scope of the invention, and therefore the invention is not limited to the above embodiments but only by the claims.
Claims (2)
1. An intelligent early warning method for slope landslide is characterized by comprising the following steps:
a. acquiring high-definition surface slope orthographic images and terrain raster data through unmanned aerial vehicle oblique photogrammetry, wherein any pixel of the surface slope orthographic images corresponds to the terrain raster data one by one;
b. installing a slope radar on the opposite side of the open slope, so that a monitoring area of the slope radar corresponds to a shooting range of the acquired high-definition open slope orthographic image;
c. install camera 1 st can intelligent cruising camera:
the method comprises the steps of installing a 1 st camera capable of intelligent cruising on the opposite side of an open side slope, obtaining 360-degree visual angle intelligent cruising shooting pictures of the open side slope, using n to represent the number of pictures, wherein each picture corresponds to one visual angle, manually deleting the visual angle covering a radar monitoring area in the n visual angles, and assuming m 1 And, in order of m 1 Numbering the viewing angles;
d. when the 1 st camera can not cover the early warning area, the number of cameras is increased, and the panoramic photos of the early warning area are synthesized by using the photos shot by the i cameras:
by m 1 Photo composition early warning area with individual visual anglesChecking whether there is an uncovered area, if so, installing a 2 nd intelligent cruising camera on the slope of the uncovered area, and repeating the step c for the camera to obtain m 2 Photographs of the individual perspectives; repeating the above process until the ith camera is installed, and using m 1 +m 2 +...+m i D, synthesizing a complete slope panoramic photo by the photos at the individual visual angles, and stopping the step d;
e. increasing the number of cameras according to the slope radar monitoring period:
j is used for representing a monitoring period of the side slope radar, the time used by the 1 st to i th cameras for intelligently cruising all visual angles of the camera is recorded respectively, the time used by the k th camera is assumed to be T minutes, k=1, 2, …, i, and when T is the same as the time used by the k th camera>In j, supplementing an additional camera at the kth camera, wherein the additional camera and the kth camera are cruising for m respectively k Half of the view angles in the pictures until the time used by each camera is less than or equal to j, stopping supplementing the additional cameras, and finally utilizing m after p represents the total number of the additional cameras to supplement the additional cameras 1 +m 2 +...+m p The photos at the various visual angles synthesize a complete slope panoramic photo;
f. determining a three-dimensional coordinate range and a central three-dimensional coordinate of each photo coverage area:
let m 1 +m 2 +...+m p The photos of the individual visual angles are respectively matched with high-definition surface slope orthographic images by adopting a deep learning image matching algorithm, and the three-dimensional coordinate range and the central three-dimensional coordinate of each photo coverage area are determined by combining with the topographic raster data;
g. screening a history and real-time photo of a visual angle corresponding to the early warning area according to the early warning area preliminarily determined by the on-line monitoring of the slope radar, screening interference factors of the area based on an image artificial intelligent algorithm, and if the interference factors exist, giving an early warning error report; if no interference factors exist, a standby camera is called, the slope condition of the area is monitored in real time, and intelligent early warning is realized.
2. The intelligent early warning method for the side slope landslide according to claim 1, wherein the interference factors comprise mine production equipment and personnel, ground stress release and rock mass relaxation caused by rock mass excavation, instantaneous loosening deformation of the rock mass caused by impact and vibration caused by blasting, and rock mass change caused by drilling, loading and transporting operations in a mine stope.
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| CN202310290476.2A CN116499427A (en) | 2023-03-23 | 2023-03-23 | Intelligent early warning method for slope landslide |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117558106A (en) * | 2023-11-24 | 2024-02-13 | 中国地质科学院探矿工艺研究所 | Non-contact type surface deformation quantitative monitoring and early warning method and monitoring system |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN117558106A (en) * | 2023-11-24 | 2024-02-13 | 中国地质科学院探矿工艺研究所 | Non-contact type surface deformation quantitative monitoring and early warning method and monitoring system |
| CN117558106B (en) * | 2023-11-24 | 2024-05-03 | 中国地质科学院探矿工艺研究所 | Non-contact type surface deformation quantitative monitoring and early warning method and monitoring system |
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