CN112711033B - Slope safety monitoring and early warning device and method - Google Patents
Slope safety monitoring and early warning device and method Download PDFInfo
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- CN112711033B CN112711033B CN202011428765.7A CN202011428765A CN112711033B CN 112711033 B CN112711033 B CN 112711033B CN 202011428765 A CN202011428765 A CN 202011428765A CN 112711033 B CN112711033 B CN 112711033B
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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
- G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
- G01S17/88—Lidar systems specially adapted for specific applications
- G01S17/89—Lidar systems specially adapted for specific applications for mapping or imaging
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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
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/48—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S17/00
- G01S7/497—Means for monitoring or calibrating
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/50—Depth or shape recovery
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F2218/00—Aspects of pattern recognition specially adapted for signal processing
- G06F2218/02—Preprocessing
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T2207/00—Indexing scheme for image analysis or image enhancement
- G06T2207/10—Image acquisition modality
- G06T2207/10028—Range image; Depth image; 3D point clouds
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- General Physics & Mathematics (AREA)
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Abstract
The embodiment of the invention discloses a slope safety monitoring and early warning device and an early warning method, wherein the device comprises the following components: a holder; the laser radar is arranged on the holder and used for acquiring point cloud data of the target slope in real time; the camera is arranged on the holder and used for acquiring image data of the target slope in real time, and the laser radar and the camera are pre-calibrated; the controller is used for carrying out filtering processing on the point cloud data and eliminating outliers, and is also used for carrying out operation fusion on the point cloud data with the outliers eliminated and the image data through a conversion matrix to obtain color image data with three-dimensional coordinates; the controller is further used for monitoring depth change of the slope surface according to the color image data, and giving an early warning to a cloud when the target slope is monitored to be in disaster or deformation. Compared with the traditional slope monitoring means, the slope monitoring method has the advantages of high slope modeling precision, convenience in device layout and low cost.
Description
Technical Field
The embodiment of the invention relates to the technical field of slope safety, in particular to a slope safety monitoring and early warning device and method.
Background
Along with the rapid development of highway construction, highway side slope geological disasters occur occasionally, and natural disasters such as collapse, landslide, debris flow, ground cracks and the like easily occur in regions mainly concentrated in southwest and other regions with complex geological environments. The potential safety hazards of the side slope in other areas are distributed along the two sides of the highway and the railway and the two banks of the dam area, and the difficulty of monitoring the side slope is increased due to the characteristic of large span of line engineering. The loss caused by the slope disaster is huge, and the damage to highway facilities caused by the geological disaster caused by the instability of the slope is heavy; the slope instability seriously affects the normal operation of the road, and causes great social influence.
The traditional side slope monitoring method needs a large number of sensors, and is high in cost, complex in installation and difficult in maintenance.
Disclosure of Invention
The embodiment of the invention aims to provide a slope safety monitoring and early warning device and method, which are used for solving the problems of large quantity of sensors, high cost, complex installation and difficult maintenance in the conventional slope monitoring method.
In order to achieve the above object, the embodiments of the present invention mainly provide the following technical solutions:
in a first aspect, an embodiment of the present invention provides a slope safety monitoring and early warning device, including:
a holder;
the laser radar is arranged on the holder and used for acquiring point cloud data of the target slope in real time;
the camera is arranged on the holder and used for acquiring image data of the target slope in real time, and the laser radar and the camera are pre-calibrated;
the controller is used for carrying out filtering processing on the point cloud data and eliminating outliers, and is also used for carrying out operation fusion on the point cloud data with the outliers eliminated and the image data through a conversion matrix to obtain color image data with three-dimensional coordinates; the controller is further used for monitoring depth change of the slope surface according to the color image data, and giving an early warning to a cloud when the target slope is monitored to be in disaster or deformation.
According to one embodiment of the invention, the fields of view of the lidar and the camera differ by a preset range.
According to one embodiment of the invention, a holder box for fixing the relative positions of the laser radar and the camera is arranged on the holder.
According to one embodiment of the invention, the cradle further comprises a support frame for supporting and stabilizing the holder box.
In a second aspect, an embodiment of the present invention further provides a slope safety monitoring and early warning method, including:
acquiring point cloud data of a target slope in real time through a laser radar, and acquiring image data of the target slope in real time through a camera;
filtering the point cloud data, eliminating outliers, and fusing the point cloud data with the outliers eliminated and the image data through conversion matrix operation to obtain color image data with three-dimensional coordinates;
and monitoring the depth change of the slope surface according to the color image data, and giving an early warning to a cloud when the target slope is monitored to be in a disaster or deformed.
According to an embodiment of the present invention, before the acquiring, by the camera, the image data of the target slope in real time, the method further includes:
providing a standard black and white checkerboard;
acquiring a plurality of checkerboard images of the camera at different poses;
and calculating external parameters and internal parameters of the camera by using a Zhangyingyou calibration method.
According to an embodiment of the present invention, after calculating external parameters and internal parameters of the camera, and before acquiring point cloud data of a target slope in real time by a laser radar and acquiring image data of the target slope in real time by the camera, the method further includes:
fixing the relative positions of the laser radar and the camera in a pan-tilt box;
acquiring a color image of the target slope and point cloud data comprising a plurality of point locations;
acquiring three-dimensional coordinates of actual positions of the point cloud data comprising a plurality of point locations and corresponding pixel coordinates of the point cloud data comprising a plurality of point locations in the color image;
and solving a transformation relation matrix between the camera coordinate system and the radar coordinate system according to the three-dimensional coordinates and the pixel coordinates.
According to an embodiment of the present invention, the depth change monitoring of the slope surface according to the color image data, and the early warning to the cloud when the disaster or deformation of the target slope is monitored, include:
replacing the original gray data with the depth data by using a preset background modeling algorithm;
monitoring whether the target slope is in disaster or deformation according to the depth change information;
and when monitoring that the target slope is in a disaster or deformed, early warning is carried out on the cloud end, and the video sending fragments are uploaded to the cloud end.
According to an embodiment of the present invention, further comprising: and carrying out displacement monitoring on the fixed point of the target slope, recording the three-dimensional coordinates of the point location once per hour, and carrying out eight-neighborhood mean filtering and outlier filtering.
According to an embodiment of the present invention, further comprising: and analyzing the historical coordinates of the point positions, and performing landslide early warning when the variation is larger than a threshold value in 30 days.
The technical scheme provided by the embodiment of the invention at least has the following advantages:
compared with the traditional slope monitoring means, the slope safety monitoring early warning device and the slope safety monitoring early warning method provided by the embodiment of the invention have the advantages of high slope modeling precision, convenience in device layout and low cost.
Drawings
Fig. 1 is a block diagram of a slope safety monitoring and early warning device according to an embodiment of the present invention.
Fig. 2 is a flowchart of a slope safety monitoring and early warning method according to an embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention is provided for illustrative purposes, and other advantages and effects of the present invention will become apparent to those skilled in the art from the present disclosure.
In the following description, for purposes of explanation and not limitation, specific details are set forth such as particular system structures, interfaces, techniques, etc. in order to provide a thorough understanding of the present invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.
In the description of the present invention, it is to be understood that the terms "center", "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", and the like, indicate orientations or positional relationships based on those shown in the drawings, and are used only for convenience in describing the present invention and for simplicity in description, and do not indicate or imply that the referenced devices or elements must have a particular orientation, be constructed and operated in a particular orientation, and thus, are not to be construed as limiting the present invention.
In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in specific cases to those skilled in the art.
Fig. 1 is a block diagram of a slope safety monitoring and early warning device according to an embodiment of the present invention. As shown in fig. 1, the slope safety monitoring and early warning device according to the embodiment of the present invention includes: a pan/tilt head 100, a laser radar 200 and a camera 300 provided on the pan/tilt head 100, and a controller 400. Wherein the lidar 200 and the camera 300 are pre-calibrated. The laser radar 200 is used for acquiring point cloud data of a target slope in real time. The camera 300 is used to acquire image data of a target slope in real time. The controller 400 may be an industrial personal computer, networked with routers through switches, and powered by a switching power supply.
Furthermore, the laser radar 200 and the camera 300 need to be close in visual field for selection, so that radar data and color images can be better fused.
Further, a pan/tilt head box for fixing the relative positions of the laser radar 200 and the camera 300 is disposed on the pan/tilt head 100, so as to perform joint calibration.
Further, side slope safety monitoring early warning device is still including being used for supporting and stabilizing the support frame of cloud platform box, makes cloud platform 100 stable, does not receive the interference of the bad weather of strong wind.
Furthermore, the slope safety monitoring and early warning device is also provided with a distribution box which is used for uniformly storing equipment such as a switching power supply, a switch, a router, an industrial personal computer server and the like, so that the slope safety monitoring and early warning device is not influenced by rain and snow weather and sunshine insolation.
Specifically, a mounting point position is selected at a proper position opposite to the target slope, and the point position is selected according to the length of the slope and the camera view, so that the camera view covers the whole slope and is symmetrically distributed in the center of an image.
And constructing a platform by using concrete at the selected point position, wherein the platform is used for piling and installing a tripod head support, encapsulating the laser radar and the camera in the tripod head, adjusting the visual angle and fixing the laser radar and the camera on the support. A distribution box is arranged beside the support, an industrial personal computer, a switch, a 4G router and a switching power supply are arranged in the distribution box, the connection and wiring are finished, and the device can be electrified and operated.
Before the device starts monitoring and early warning, the camera and the laser radar need to be calibrated.
When monitoring and early warning are performed, the controller 400 is configured to perform filtering processing on point cloud data acquired in real time, remove outliers, and then perform calculation fusion on the point cloud data from which the outliers are removed and image data through a conversion matrix to obtain color image data with three-dimensional coordinates, which is referred to as six-dimensional point cloud (XYZRGB) for short. Specifically, a three-dimensional coordinate point P (x, y, z) is transformed by a transformation matrix and projected to a two-dimensional image position Q (u, v), where the point Q has three-dimensional coordinates based on the original RGB color information. The traditional background modeling algorithm (vibe) is improved, in the vibe model, a sample set is stored in the background model for each background point, and then each new pixel value is compared with the sample set to judge whether the background point belongs to or not. It can be seen that if a new observed value belongs to a background point it should be relatively close to the sample value in the sample set. Specifically, let v (x) be the pixel value at point x; m (x) ═ V1,V2,…VNIs the background sample set at x (sample set size N); SR (V (x): the area with x as the center R as the radius, if M (x) [ { SR (V (x)) ] n { V [ ]1,V2,…VN}}]Greater than a given threshold min, then point x is considered to belong to the backgroundThe scenic spots, otherwise, the foreground moving objects. According to the embodiment of the invention, the gray data of the sample set in the original algorithm is replaced by the depth data, moving targets such as rockfall, landslide and the like are detected by using depth change, depth change monitoring on the surface of the side slope is realized, the foreground target exceeding a threshold value is subjected to alarm processing, an alarm image and videos before and after occurrence are stored, and the alarm image and the videos before and after occurrence are uploaded to the cloud so as to facilitate viewing and tracing.
It should be noted that other structures and functions of the slope safety monitoring and early warning device according to the embodiment of the present invention are known to those skilled in the art, and are not described in detail for reducing redundancy.
Fig. 2 is a flowchart of a slope safety monitoring and early warning method according to an embodiment of the present invention. As shown in fig. 2, the slope safety monitoring and early warning method according to the embodiment of the present invention includes:
s0: and calibrating the laser radar and the camera.
Specifically, firstly, calibrating a color camera, printing a standard black and white checkerboard, acquiring 20 checkerboard images of different poses under the camera, and calculating external parameters and internal parameters of the camera by using a Zhang Zhengyou calibration method.
Installing a radar and a camera device in a holder box, fixing relative positions, respectively acquiring a color image and 5s point cloud data of a monitored slope, selecting more than 10 point positions, acquiring a three-dimensional coordinate of an actual position and a pixel coordinate corresponding to the three-dimensional coordinate in the color image, and solving a transformation relation matrix M between a camera coordinate system and a radar coordinate system according to the following equation, wherein (u, v) represents an image coordinate, (x, y, z) represents the three-dimensional coordinate, and f represents the three-dimensional coordinateu,fv,uc,vcIs the camera intrinsic parameter, and R, t are the rotation and translation matrices, respectively.
S1: and acquiring point cloud data of the target slope in real time through a laser radar, and acquiring image data of the target slope in real time through a camera.
S2: and filtering the point cloud data, eliminating outliers, and then performing conversion matrix operation fusion on the point cloud data and the image data after the outliers are eliminated to obtain color image data with three-dimensional coordinates, which is called six-dimensional point cloud (XYZRGB) for short.
S3: and monitoring the depth change of the surface of the slope according to the six-dimensional point cloud data, and giving an early warning to the cloud when the target slope is monitored to be in a disaster or deformation. The method has the advantages that the original gray data is replaced by the depth data by using an improved vibe background modeling algorithm, moving targets such as rockfall, landslide and the like are detected by using depth change, alarm processing is carried out, incident video segments are recorded and uploaded to the cloud, and source tracing is facilitated. The algorithm has the advantages of accurate detection and strong anti-interference capability.
In one embodiment of the present invention, further comprising: and (4) carrying out displacement monitoring on the fixed point, recording the three-dimensional coordinates of the point once per hour, carrying out 8-neighborhood mean filtering and outlier filtering, and reducing the data jitter.
In one embodiment of the present invention, further comprising: and analyzing the historical coordinates of the point positions, and performing landslide early warning if the variation is larger than a threshold value in 30 days.
The above-mentioned embodiments, objects, technical solutions and advantages of the present invention are further described in detail, it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention, and are not intended to limit the scope of the present invention, and any modifications, equivalent substitutions, improvements and the like made on the basis of the technical solutions of the present invention should be included in the scope of the present invention.
Claims (8)
1. The utility model provides a side slope safety monitoring early warning device which characterized in that includes:
a holder;
the laser radar is arranged on the holder and used for acquiring point cloud data of the target slope in real time;
the camera is arranged on the holder and used for acquiring image data of the target slope in real time, and the laser radar and the camera are pre-calibrated;
the difference between the fields of view of the laser radar and the camera is within a preset range;
the controller is used for carrying out filtering processing on the point cloud data and eliminating outliers, and is also used for carrying out operation fusion on the point cloud data with the outliers eliminated and the image data through a conversion matrix to obtain color image data with three-dimensional coordinates; the controller is further used for monitoring depth change of the slope surface according to the color image data, and giving an early warning to a cloud when the target slope is monitored to be in disaster or deformation.
2. The slope safety monitoring and early warning device according to claim 1, wherein a holder box for fixing the relative position of the laser radar and the camera is arranged on the holder.
3. The slope safety monitoring and early warning device according to claim 2, further comprising a support frame for supporting and stabilizing the cradle head box.
4. A slope safety monitoring and early warning method is characterized by comprising the following steps:
acquiring point cloud data of a target slope in real time through a laser radar, and acquiring image data of the target slope in real time through a camera;
filtering the point cloud data, eliminating outliers, and fusing the point cloud data with the outliers eliminated and the image data through conversion matrix operation to obtain color image data with three-dimensional coordinates;
monitoring the depth change of the slope surface according to the color image data, and giving an early warning to a cloud when monitoring that the target slope is in disaster or deformation, wherein the monitoring comprises the following steps:
replacing the original gray data with the depth data by using a preset background modeling algorithm;
monitoring whether the target slope is in disaster or deformation according to the depth change information;
and when monitoring that the target slope is in a disaster or deformed, early warning is carried out on the cloud end, and the incident video clip is uploaded to the cloud end.
5. The slope safety monitoring and early warning method according to claim 4, before the image data of the target slope is acquired in real time by the camera, the method further comprises:
providing a standard black and white checkerboard;
acquiring a plurality of checkerboard images of the camera at different poses;
and calculating external parameters and internal parameters of the camera by using a Zhangyingyou calibration method.
6. The slope safety monitoring and early warning method according to claim 5, after calculating external parameters and internal parameters of the camera, and before acquiring point cloud data of a target slope in real time through a laser radar and acquiring image data of the target slope in real time through the camera, further comprising:
fixing the relative positions of the laser radar and the camera in a pan-tilt box;
acquiring a color image of the target slope and point cloud data comprising a plurality of point locations;
acquiring three-dimensional coordinates of actual positions of the point cloud data comprising a plurality of point locations and corresponding pixel coordinates of the point cloud data comprising a plurality of point locations in the color image;
and solving a transformation relation matrix between the camera coordinate system and the radar coordinate system according to the three-dimensional coordinates and the pixel coordinates.
7. The slope safety monitoring and early warning method according to claim 4, further comprising:
and carrying out displacement monitoring on the fixed point of the target slope, recording the three-dimensional coordinates of the point location once per hour, and carrying out eight-neighborhood mean filtering and outlier filtering.
8. The slope safety monitoring and early warning method according to claim 7, further comprising:
and analyzing the historical coordinates of the point positions, and performing landslide early warning when the variation is larger than a threshold value in 30 days.
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| CN113192084A (en) * | 2021-05-07 | 2021-07-30 | 中国公路工程咨询集团有限公司 | Machine vision-based highway slope micro-displacement deformation monitoring method |
| CN113240887A (en) * | 2021-05-14 | 2021-08-10 | 深圳市安泰数据监测科技有限公司 | Slope rockfall collapse monitoring method, device and equipment |
| CN113218321A (en) * | 2021-05-31 | 2021-08-06 | 西南石油大学 | Remote visual monitoring method for slope deformation |
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| CN113899405A (en) * | 2021-10-20 | 2022-01-07 | 中煤科工集团沈阳设计研究院有限公司 | Integrated online slope intelligent monitoring and early warning system and early warning method |
| CN114267155A (en) * | 2021-11-05 | 2022-04-01 | 国能大渡河革什扎水电开发有限公司 | Geological disaster monitoring and early warning system based on video recognition technology |
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| CN115223337A (en) * | 2022-06-30 | 2022-10-21 | 山东大学 | Automatic monitoring and early warning system and method for dike seepage |
| CN115079166B (en) * | 2022-07-27 | 2022-11-01 | 南京隼眼电子科技有限公司 | Millimeter wave radar disaster monitoring method and system and electronic equipment |
| CN115762067B (en) * | 2022-11-25 | 2023-10-03 | 中国科学院空天信息创新研究院 | Landslide monitoring system based on laser point cloud and video data fusion |
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