Slope monitoring method, device, equipment, medium and product

Abstract

The invention provides a side slope monitoring method, device and equipment, a medium and a product, and the method comprises the steps: determining a first deformation parameter of a side slope monitoring region based on a radar image map; based on a laser scanner, performing multi-stage data acquisition on the slope monitoring area, and determining a second deformation parameter of the slope monitoring area; based on a high-bit-rate camera, performing multi-stage data acquisition on the slope monitoring area, and determining a third deformation parameter of the slope monitoring area; based on a binocular video camera, monitoring a preset checkerboard marker in the slope monitoring area, and determining a fourth deformation parameter of the slope monitoring area; and determining a slope deformation result of the slope monitoring area based on the first deformation parameter, the second deformation parameter, the third deformation parameter and the fourth deformation parameter. According to the method disclosed by the invention, the slope is detected by adopting satellite, air and ground multi-platform cooperation, so that the scientificity of slope monitoring and the accuracy of a monitoring result are improved.

Description

Technical Field

[0001] The present disclosure relates to the field of slope monitoring, and particularly to a slope monitoring method, device, equipment, medium and product. Background Art

[0002] With the continuous development of open-pit mining technology and equipment in China, its characteristics of large scale, high efficiency, low cost and high resource recovery rate are becoming more and more prominent. The dual factors of land shortage and production targets have forced the wide application of steep slope mining, resulting in prominent stability problems of high-steep slopes in open-pit mines and frequent geological disasters. Therefore, the stability evaluation of high-steep slopes in large open-pit mines is of great significance for the safe mining, sustainable production and geological disaster prevention of mines. The southwest waste dump of Weijiamao Open-pit Coal Mine is located on a thick Quaternary loess layer, which is a high-steep composite dip slope and is adjacent to the Guanzigou Industrial Square, so the research significance is great.

[0003] Generally speaking, the stability of high-steep slopes is mainly affected by factors such as geological conditions, meteorological environment and human activities. There are many domestic and foreign mine slope monitoring methods, such as surface displacement and deformation monitoring, underground borehole inclinometry and stress monitoring, acoustic emission and microseismic monitoring, groundwater monitoring and meteorological parameter monitoring, etc. Among them, geometric monitoring for displacement and deformation is the most commonly used method. Although the traditional geodetic geometric monitoring means has high accuracy, it has the disadvantages of large workload, high cost, difficult point layout and sparse measuring points. Under large-scale and complex terrain conditions, ground-based measurement is greatly limited, and it is difficult to obtain large-scale displacement and large deformation information of large open-pit mines, and it cannot provide comprehensive and accurate information guarantee for mine slope disaster prevention. Summary of the Invention

[0004] The present disclosure provides a slope monitoring method, device, equipment, medium and product to solve the problems in the related art and improve the scientificity of slope monitoring and the accuracy of monitoring results.

[0005] In a first aspect embodiment of the present disclosure, a slope monitoring method is proposed. The method includes: determining a first deformation parameter of a slope monitoring area based on a radar image; performing multi-period data acquisition on the slope monitoring area by a laser scanner to determine a second deformation parameter of the slope monitoring area; performing multi-period data acquisition on the slope monitoring area by a high-bitrate camera to determine a third deformation parameter of the slope monitoring area; monitoring a preset checkerboard marker in the slope monitoring area by a binocular video camera to determine a fourth deformation parameter of the slope monitoring area; and determining a slope deformation result of the slope monitoring area based on the first deformation parameter, the second deformation parameter, the third deformation parameter and the fourth deformation parameter.

[0006] In some embodiments of the present disclosure, determining the first deformation parameter of the slope monitoring area based on the radar image includes: obtaining the radar image of the slope monitoring area at a preset time point; determining the phase diagram of the radar image by using a preset phase algorithm based on the horizontal baseline and the vertical baseline in the radar image; determining the slope deformation rate of the slope monitoring area based on the baseline interferometry pair of the phase diagram, the time interval of the baseline interferometry pair, and the number of measurement pairs of the baseline interferometry pair; and determining the first deformation parameter based on the slope deformation rate.

[0007] In some embodiments of the present disclosure, performing multi-period data acquisition on the slope monitoring area based on the laser scanner and determining the second deformation parameter of the slope monitoring area includes: scanning the slope monitoring area based on the laser scanner by using the scanning method of fixed single-station coordinate points to obtain a laser point cloud image; determining a filtered point cloud image by using a preset filtering algorithm based on the laser point cloud image; and determining the second deformation parameter based on the filtered point cloud image.

[0008] In some embodiments of the present disclosure, determining the filtered point cloud image by using a preset filtering algorithm based on the laser point cloud image includes: removing the abnormal point cloud in the laser point cloud image by using a preset point cloud threshold based on the laser point cloud image to obtain a preprocessed point cloud image; determining a segmented point cloud image by using a point cloud segmentation algorithm based on the preprocessed point cloud image; meshing the segmented point cloud image to obtain a slope mesh image; performing plane fitting processing and plane rotation processing on the slope mesh image in sequence to obtain a processed mesh image; and filtering the processed mesh image by using an incremental encrypted triangular mesh filtering algorithm to obtain a filtered point cloud image.

[0009] In some embodiments of the present disclosure, performing multi-period data acquisition on the slope monitoring area based on the high-frame-rate camera and determining the third deformation parameter of the slope monitoring area includes: performing multi-period data acquisition on the slope monitoring area based on the high-frame-rate camera to obtain slope acquisition images; generating a three-dimensional color point cloud map by using digital photogrammetry technology based on the slope acquisition images; and determining the third deformation parameter by using a difference analysis algorithm based on the three-dimensional color point cloud map.

[0010] In some embodiments of the present disclosure, monitoring a preset checkerboard marker in the slope monitoring area based on the binocular video camera and determining the fourth deformation parameter of the slope monitoring area includes: constructing a reference coordinate system based on the preset checkerboard marker; obtaining the two-dimensional coordinates of the preset checkerboard marker in the reference coordinate system based on the binocular video camera; determining the three-dimensional coordinates of the preset checkerboard marker by using a triangulation processing algorithm based on the two-dimensional coordinates; and determining the fourth deformation parameter based on the three-dimensional coordinates.

[0011] A second aspect embodiment of the present disclosure provides a slope monitoring device, which includes: a first monitoring unit for determining a first deformation parameter of a slope detection area based on a radar image; a second monitoring unit for performing multi-period data acquisition on the slope detection area to be measured based on a laser scanner and determining a second deformation parameter of the slope monitoring area; a third monitoring unit for performing multi-period data acquisition on the slope detection area to be measured based on a high-frame rate camera and determining a third deformation parameter of the slope monitoring area; a fourth monitoring unit for monitoring a preset checkerboard marker in the slope detection area based on a binocular video camera and determining a fourth deformation parameter of the slope monitoring area; and a fusion unit for determining a slope deformation result of the slope detection area based on the first deformation parameter, the second deformation parameter, the third deformation parameter, and the fourth deformation parameter.

[0012] A third aspect embodiment of the present disclosure provides an electronic device, which includes: a processor and a memory for storing a computer program that can run on the processor. When the processor runs the computer program, it executes the method described in the first aspect embodiment of the present disclosure.

[0013] A fourth aspect embodiment of the present disclosure provides a non-transitory computer-readable storage medium storing computer instructions, where the computer instructions are used to cause a computer to execute the method described in the first aspect embodiment of the present disclosure.

[0014] A fifth aspect embodiment of the present disclosure provides a computer program product, which includes a computer program that implements the method described in the first aspect embodiment of the present disclosure when executed by a processor.

[0015] In summary, a slope monitoring method proposed according to the present disclosure includes: determining a first deformation parameter of a slope monitoring area based on a radar image; performing multi-period data acquisition on the slope monitoring area to be measured based on a laser scanner and determining a second deformation parameter of the slope monitoring area; performing multi-period data acquisition on the slope monitoring area to be measured based on a high-frame rate camera and determining a third deformation parameter of the slope monitoring area; monitoring a preset checkerboard marker in the slope monitoring area based on a binocular video camera and determining a fourth deformation parameter of the slope monitoring area; and determining a slope deformation result of the slope monitoring area based on the first deformation parameter, the second deformation parameter, the third deformation parameter, and the fourth deformation parameter. The method of the present disclosure improves the scientificity of slope monitoring and the accuracy of monitoring results by using multi-platform cooperation of satellite, aerial, and ground to detect slopes.

[0016] It should be understood that the above general description and the following detailed description are only exemplary and explanatory, and cannot limit the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] The accompanying drawings here are incorporated into the specification and form a part of this specification, showing embodiments consistent with the present disclosure, and are used together with the specification to explain the principles of the present disclosure, and do not constitute an undue limitation of the present disclosure.

[0018] Figure 1 It is a flowchart of a slope monitoring method provided for an embodiment of the present disclosure;

[0019] Figure 2 It is a flowchart of another slope monitoring method provided for an embodiment of the present disclosure;

[0020] Figure 3 It is a schematic structural diagram of a slope monitoring device provided for an embodiment of the present disclosure;

[0021] Figure 4 It is a schematic structural diagram of an electronic device provided for an embodiment of the present disclosure. Detailed Description of the Embodiment

[0022] The embodiments of the present disclosure will be described in detail below. The examples of the embodiments are shown in the accompanying drawings, where the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to explain the present disclosure, and should not be construed as a limitation of the present disclosure.

[0023] With the continuous development of open-pit mining technology and equipment in our country, its characteristics of large scale, high efficiency, low cost, and high resource recovery rate are becoming more and more prominent. The dual factors of land shortage and production goals have forced the wide application of steep slope mining, resulting in prominent stability problems of high-steep slopes in open-pit mines and frequent geological disasters. Therefore, the stability evaluation of high-steep slopes in large open-pit mines is of great significance for the safe mining, sustainable production, and geological disaster prevention of mines. The southwest waste dump of Weijiamao Open-pit Coal Mine is located on a thick Quaternary loess layer, which is a high-steep composite dip slope and is adjacent to the Guanzigou Industrial Square, so the research significance is great.

[0024] Generally speaking, the stability of high-steep slopes is mainly affected by factors such as geological conditions, meteorological environment, and human activities. There are many slope monitoring methods at home and abroad, such as surface displacement and deformation monitoring, underground borehole inclinometry and stress monitoring, acoustic emission and microseismic monitoring, groundwater monitoring, and meteorological parameter monitoring. Among them, geometric monitoring of displacement and deformation is the most commonly used method. Although the traditional geodetic geometric monitoring means have high accuracy, they have the disadvantages of large workload, high cost, difficult point layout, and sparse measuring points. Under large-scale and complex terrain conditions, ground-based measurement is greatly limited, and it is difficult to obtain large-scale displacement and large deformation information of large open-pit mines, and it cannot provide comprehensive and accurate information guarantee for the prevention and control of mine slope disasters.

[0025] With the rapid development of modern surveying and mapping science and technology, various new monitoring means have emerged continuously, such as deformation monitoring by satellite navigation and positioning system (GNSS), differential interferometric synthetic aperture radar (D-InSAR), close-range and unmanned aerial vehicle (UAV) photogrammetry, long-range terrestrial laser scanning (TLS), etc., which have all been applied to different open-pit mines. The monitoring of slopes and landslides is gradually developing from traditional point-type monitoring to surface-type and even volume-type monitoring. However, different monitoring methods have different applicability and limitations due to their respective inherent defects. For example, although GNSS monitoring has high accuracy and fast response, and can achieve online and continuous monitoring, the monitoring points are sparse, and the satellite signals are poor and multi-path effects are easy to occur in deep pit environments, so it cannot be monitored; although D-InSAR has high measurement accuracy and is surface-type monitoring, and can obtain large-scale displacement field information, phase unwrapping is difficult or phase decorrelation occurs during large deformations; although terrestrial TLS is fast and has relatively high accuracy, there are scanning dead angles, and the software modules supporting it are relatively complex in processing large-scale point cloud data. Due to the high slopes, steep gradients, large drops, and numerous influencing factors of large open-pit mines, they have characteristics such as complexity, concealment, multi-scale, multi-stage, and large deformation, and there is an urgent need to construct a sky-air-ground collaborative intelligent monitoring method and technology system that combines multiple platforms and multiple means.

[0026] The following further describes the present disclosure in detail with reference to the accompanying drawings and specific embodiments.

[0027] Figure 1 The flowchart of a slope monitoring method provided by an embodiment of the present disclosure is as follows Figure 1 shown, including steps 101-105.

[0028] Step 101, based on the radar image, determine the first deformation parameter of the slope monitoring area.

[0029] In some embodiments, the image of the slope detection prefetch can be obtained by the acquired Synthetic Aperture Radar (SAR) to determine the first deformation parameter.

[0030] In some embodiments, the first deformation parameter may include at least one of the following: slope deformation area, slope deformation rate, slope deformation size, etc., but is not limited thereto.

[0031] In some embodiments, the radar images of the same area at different time points can be obtained, and then by comparing the differences between the above radar images, the first deformation parameter of the slope detection area can be determined.

[0032] In an alternative embodiment, the first deformation parameter can be determined by the following method:

[0033] Obtain the radar image of the slope monitoring area at a preset time point; based on the horizontal baseline and vertical baseline in the radar image, use a preset phase algorithm to determine the phase map of the radar image; based on the baseline interferometry pairs of the phase map, the time interval of the baseline interferometry pairs, and the number of measurement pairs of the baseline interferometry pairs, determine the slope deformation rate of the slope monitoring area; based on the slope deformation rate, determine the first deformation parameter.

[0034] Step 102, based on the laser scanner, perform multi-period data collection on the slope monitoring area to determine the second deformation parameter of the slope monitoring area.

[0035] In some embodiments, a ground long-range three-dimensional laser scanner such as Riegl VZ-4000 can be used to perform laser scanning on the slope monitoring area in a way of fixing single-station coordinate points to achieve multi-period data collection of the slope monitoring area, but not limited to this. The present disclosure does not limit the data collection method.

[0036] Among them, multi-period data is the data collected at different time points.

[0037] In some embodiments, the second deformation parameter may include at least one of the following: slope deformation area, slope deformation rate, slope deformation magnitude, etc., but not limited to this.

[0038] In some embodiments, the second deformation parameter can be determined by comparing the data differences between multi-period data.

[0039] In an alternative embodiment, the second deformation parameter can be determined by the following method:

[0040] Based on the laser scanner, use the scanning method of fixing single-station coordinate points to scan the slope monitoring area to obtain a laser point cloud image; based on the laser point cloud image, use a preset filtering algorithm to determine the filtered point cloud image; based on the filtered point cloud image, determine the second deformation parameter.

[0041] Step 103, based on the high-frame rate camera, perform multi-period data collection on the slope monitoring area to determine the third deformation parameter of the slope monitoring area.

[0042] In some embodiments, a high-frame rate camera such as ZENMUSE X5s carried by a drone can be used to perform multi-period drone image data collection on the slope monitoring area to achieve multi-period data collection of the slope monitoring area, but not limited to this. The present disclosure does not limit the data collection method.

[0043] Among them, multi-period data is the data collected at different time points.

[0044] In some embodiments, the third deformation parameter may include at least one of the following: slope deformation area, slope deformation rate, slope deformation magnitude, etc., but is not limited thereto.

[0045] In some embodiments, the third deformation parameter can be determined by comparing the data differences between multiple periods of data.

[0046] In an alternative embodiment, the third deformation parameter can be determined by the following method:

[0047] Based on a high-frame-rate camera, collect multi-period data of the slope monitoring area to obtain slope acquisition images; based on the slope acquisition images, use digital photogrammetry technology to generate a three-dimensional color point cloud map; based on the three-dimensional color point cloud map, use a difference analysis algorithm to determine the third deformation parameter.

[0048] Step 104, based on a binocular video camera, monitor a preset checkerboard marker in the slope monitoring area to determine the fourth deformation parameter of the slope monitoring area.

[0049] In some embodiments, a checkerboard marker can be arranged in the slope monitoring area, and then the preset checkerboard marker can be monitored to determine the fourth deformation parameter of the slope monitoring area.

[0050] In some embodiments, the fourth deformation parameter may include at least one of the following: slope deformation area, slope deformation rate, slope deformation magnitude, etc., but is not limited thereto.

[0051] In an alternative embodiment, the fourth deformation parameter can be determined by the following method:

[0052] Based on the preset checkerboard marker, construct a reference coordinate system; based on the binocular video camera, obtain the two-dimensional coordinates of the preset checkerboard marker in the reference coordinate system; based on the two-dimensional coordinates, use a triangulation algorithm to determine the three-dimensional coordinates of the preset checkerboard marker; based on the three-dimensional coordinates, determine the fourth deformation parameter.

[0053] Step 105, based on the first deformation parameter, the second deformation parameter, the third deformation parameter, and the fourth deformation parameter, determine the slope deformation result of the slope monitoring area.

[0054] In some embodiments, the slope deformation result of the slope monitoring area can be determined by fusing the first deformation parameter, the second deformation parameter, the third deformation parameter, and the fourth deformation parameter.

[0055] Exemplarily, the comprehensive slope deformation magnitude of the slope monitoring area can be determined by weighted summing the slope deformation magnitudes among the first deformation parameter, the second deformation parameter, the third deformation parameter, and the fourth deformation parameter.

[0056] Exemplarily, by performing a union operation on the slope deformation regions of the first deformation parameter, the second deformation parameter, the third deformation parameter, and the fourth deformation parameter, the result of the union operation can be determined as the comprehensive deformation region of the slope monitoring region, thereby improving the accuracy of the slope deformation result.

[0057] In summary, the slope monitoring method proposed according to the present disclosure includes: determining the first deformation parameter of the slope monitoring region based on the radar image; performing multi-period data acquisition on the slope monitoring region using a laser scanner to determine the second deformation parameter of the slope monitoring region; performing multi-period data acquisition on the slope monitoring region using a high-bitrate camera to determine the third deformation parameter of the slope monitoring region; monitoring a preset checkerboard marker in the slope monitoring region using a binocular video camera to determine the fourth deformation parameter of the slope monitoring region; and determining the slope deformation result of the slope monitoring region based on the first deformation parameter, the second deformation parameter, the third deformation parameter, and the fourth deformation parameter. The method of the present disclosure improves the scientificity of slope monitoring and the accuracy of monitoring results by using multi-platform collaboration of satellite, airborne, and ground platforms to detect slopes.

[0058] Figure 2 Further, a flowchart of a slope monitoring method proposed by the present disclosure is shown. Based on Figure 1 the embodiments shown, Figure 2 it includes the following steps.

[0059] Step 201, obtain a radar image of the slope monitoring region at a preset time point.

[0060] In some embodiments, the radar image stored in the data providing platform of SAR can be obtained through an Application Programming Interface (API), but it is not limited thereto. The present disclosure does not limit the method of obtaining the radar image.

[0061] Step 202, based on the horizontal baseline and vertical baseline in the radar image, use a preset phase algorithm to determine the phase map of the radar image.

[0062] In some embodiments, by performing interferometric pair analysis on two radar images with different spatial positions, the baselines between the two radar images can be determined respectively.

[0063] Furthermore, the horizontal baseline and vertical baseline can be determined from the determined baselines through a baseline decomposition algorithm.

[0064] Furthermore, the phase map of the radar image can be determined by the following formula:

[0065]

[0066] Among them, is the horizontal baseline, B⊥ is the vertical baseline, B is the distance between the synthetic aperture radar and the slope to be monitored, and θ ∥ is the angle between the horizontal baseline and the radar signal of the synthetic aperture radar, and θ ⊥ is the angle between the vertical baseline and the radar signal of the synthetic aperture radar, λ is the wavelength of the radar signal, and φ is the phase diagram.

[0067] Step 203: Determine the slope deformation rate of the slope monitoring area based on the baseline interferometry pair of the phase diagram, the time interval of the baseline interferometry pair, and the number of measurement pairs of the baseline interferometry pair.

[0068] In some embodiments, the cumulative deformation amount of the slope can be determined by the following formula:

[0069]

[0070] Among them, ΔL is the cumulative deformation amount, v(t) is the deformation rate at time t, T is the time interval of the baseline interferometry pair of the phase diagram after rejection, and N is the number of baseline interferometry pairs of the phase diagram after rejection

[0071] Furthermore, the deformation rate of the slope is determined by the following formula:

[0072]

[0073] Among them, v(t) is the deformation rate at time t, N is the number of baseline interferometry pairs of the phase diagram after rejection, and T is the time interval of the baseline interferometry pair of the phase diagram after rejection.

[0074] Step 204: Determine the first deformation parameter based on the slope deformation rate.

[0075] In some embodiments, the slope deformation rate can be directly determined as the first deformation parameter; alternatively, the deformation area in the monitoring area can be determined according to the slope deformation rate, and the deformation area can be determined as the first deformation parameter.

[0076] Optionally, the cumulative deformation amount determined in step 203 can also be determined as the first deformation parameter, which is not limited in this disclosure.

[0077] Step 205: Based on the laser scanner, scan the slope monitoring area by using the scanning method of fixed single-station coordinate points to obtain a laser point cloud image.

[0078] Step 206: Based on the laser point cloud image, use a preset filtering algorithm to determine a filtered point cloud image.

[0079] In some embodiments, based on the laser point cloud image, using a preset point cloud threshold, abnormal point clouds in the laser point cloud image are removed to obtain a preprocessed point cloud image; based on the preprocessed point cloud image, using a point cloud segmentation algorithm, a segmented point cloud image is determined; the segmented point cloud image is meshed to obtain a slope grid image; the slope grid image is sequentially subjected to plane fitting processing and plane rotation processing to obtain a processed grid image; the processed grid image is filtered using a progressive densification triangular network filtering algorithm to obtain a filtered point cloud image.

[0080] Optionally, a threshold can be set using an elevation histogram to remove abnormal points.

[0081] Optionally, a region growing method can also be used for point cloud segmentation to obtain slope inclined plane point clouds and slope horizontal plane point clouds.

[0082] Optionally, the bottom and top vertex point clouds of the slope inclined plane in the laser point cloud image can be respectively subjected to least squares curve fitting; by setting a curvature threshold, when the curvature is greater than the curvature threshold, connection is made at the points with the maximum curvature at the corresponding bottom and top of the slope to obtain a segmentation line, and then a segmented point cloud is obtained; and the segmented point cloud is further fitted until the curvature of the fitted curve is less than the threshold, and finally the segmentation process can be completed to obtain a relatively gentle slope point cloud.

[0083] Optionally, a progressive densification triangular network can be used to filter the rotated slope point clouds and slope horizontal plane point clouds to obtain a filtered point cloud image.

[0084] Step 207, based on the filtered point cloud image, determine the second deformation parameter.

[0085] In some embodiments, by comparing the differences between different filtered point cloud images, parameters such as the deformation region, deformation rate, and cumulative deformation amount in the monitoring area can be determined, and the above parameters can be determined as the second deformation parameter.

[0086] Step 208, based on a high-frame rate camera, multi-phase data acquisition is performed on the slope monitoring area to obtain slope acquisition images.

[0087] In some embodiments, a high-frame rate camera such as ZENMUSE X5s can be carried by a drone to perform multi-phase drone image data acquisition on the slope monitoring area to achieve multi-phase data acquisition of the slope monitoring area, but it is not limited thereto, and the present disclosure does not limit the data acquisition method.

[0088] Among them, multi-phase data is data collected at different time points.

[0089] Step 209, based on the slope acquisition images, using digital photogrammetry technology, generate a three-dimensional color point cloud map.

[0090] In some embodiments, the slope acquisition image is a two-dimensional image. A depth map corresponding to the slope acquisition image can be generated according to the data obtained by the depth sensor. The depth map represents the depth information of each pixel point in the slope acquisition image.

[0091] Furthermore, in the depth image, the depth information of the pixel points in the slope acquisition image is determined, and then the depth information is combined with the two-dimensional coordinates to generate a three-dimensional color point cloud map.

[0092] Step 210: Based on the three-dimensional color point cloud map, use the differential analysis algorithm to determine the third deformation parameter.

[0093] In some embodiments, the cumulative deformation amount of the target can be determined according to the pixel coordinate offset value of the same pixel point in different three-dimensional color point cloud maps. Then, according to the shooting time corresponding to different three-dimensional color point cloud maps, the third deformation parameters such as the deformation rate and the deformation area can be determined.

[0094] Step 211: Based on the preset checkerboard marker, construct a reference coordinate system.

[0095] In some embodiments, checkerboard markers with the same side length can be posted on a plane with better flatness to form a calibration board, thereby constructing a two-dimensional reference coordinate system.

[0096] Step 212: Based on the binocular video camera, obtain the two-dimensional coordinates of the preset checkerboard marker in the reference coordinate system.

[0097] In some embodiments, by fixing the position of the binocular vision measurement system and adjusting the zoom lens to make the image clear at a certain shooting distance, and then according to the positions of different checkerboard markers in the obtained image, the two-dimensional coordinates of the preset checkerboard marker in the reference coordinate system are determined.

[0098] Step 213: Based on the two-dimensional coordinates, use the triangulation algorithm to determine the three-dimensional coordinates of the preset checkerboard marker.

[0099] In some embodiments, since a single image cannot obtain the depth information of the pixels, the method of triangulation needs to be used to estimate the depth of the pixel points. Since the triangulation algorithm is a relatively mature algorithm, it will not be elaborated here.

[0100] In some embodiments, the depth information of the preset checkerboard marker is determined through the triangulation algorithm, and then the three-dimensional coordinates of the preset checkerboard marker are determined according to the depth information and the two-dimensional coordinates.

[0101] Step 214: Based on the three-dimensional coordinates, determine the fourth deformation parameter.

[0102] In some embodiments, the coordinate offset value can be determined according to the three-dimensional coordinates of the same pixel point in different images to determine the cumulative deformation amount of the slope. Furthermore, according to the shooting time of the binocular video camera, the fourth deformation parameters such as the deformation rate and deformation area of the slope can be determined.

[0103] Step 215: Determine the slope deformation result of the slope monitoring area based on the first deformation parameter, the second deformation parameter, the third deformation parameter, and the fourth deformation parameter.

[0104] In some embodiments, the principle of step 215 is the same as that of step 105. For the description of the relevant embodiments of step 105, reference can be made, and details are not repeated here.

[0105] In summary, the slope monitoring method proposed by the present disclosure includes: obtaining a radar image of a slope monitoring area at a preset time point; based on the horizontal baseline and vertical baseline in the radar image, using a preset phase algorithm to determine the phase map of the radar image; based on the baseline interferometry pair, the time interval of the baseline interferometry pair, and the number of measurement pairs of the baseline interferometry pair in the phase map, determining the slope deformation rate of the slope monitoring area; based on the slope deformation rate, determining the first deformation parameter; based on a laser scanner, scanning the slope monitoring area in a scanning manner of fixed single-station coordinate points to obtain a laser point cloud image; based on the laser point cloud image, using a preset filtering algorithm to determine a filtered point cloud image; based on the filtered point cloud image, determining the second deformation parameter; based on a high-frame-rate camera, performing multi-period data acquisition on the slope monitoring area to obtain slope acquisition images; based on the slope acquisition images, using digital photogrammetry technology to generate a three-dimensional color point cloud map; based on the three-dimensional color point cloud map, using a difference analysis algorithm to determine the third deformation parameter; based on a preset checkerboard marker, constructing a reference coordinate system; based on a binocular video camera, obtaining the two-dimensional coordinates of the preset checkerboard marker in the reference coordinate system; based on the two-dimensional coordinates, using a triangulation algorithm to determine the three-dimensional coordinates of the preset checkerboard marker; based on the three-dimensional coordinates, determining the fourth deformation parameter; based on the first deformation parameter, the second deformation parameter, the third deformation parameter, and the fourth deformation parameter, determining the slope deformation result of the slope monitoring area. The method of the present disclosure improves the scientificity of slope monitoring and the accuracy of monitoring results by using multi-platform cooperation of satellite, air, and ground to detect slopes.

[0106] Therefore, the present solution has the following beneficial effects:

[0107] The method of the present disclosure improves the scientificity of slope monitoring and the accuracy of monitoring results by using multi-platform cooperation of satellite, air, and ground to detect slopes.

[0108] Figure 3 It is a schematic structural diagram of a slope monitoring device 300 provided by an embodiment of the present disclosure. As Figure 3As shown, the slope monitoring device includes:

[0109] A first monitoring unit 310, configured to determine a first deformation parameter of a slope detection area based on a radar image;

[0110] A second monitoring unit 320, configured to perform multi-phase data acquisition on a slope detection area based on a laser scanner, and determine a second deformation parameter of the slope monitoring area;

[0111] A third monitoring unit 330, configured to perform multi-phase data acquisition on a slope detection area based on a high-bitrate camera, and determine a third deformation parameter of the slope monitoring area;

[0112] A fourth monitoring unit 340, configured to monitor a preset checkerboard marker in a slope detection area based on a binocular video camera, and determine a fourth deformation parameter of the slope monitoring area;

[0113] A fusion unit 350, configured to determine a slope deformation result of a slope detection area based on the first deformation parameter, the second deformation parameter, the third deformation parameter, and the fourth deformation parameter.

[0114] In some embodiments of the present disclosure, the first monitoring unit 310 is further configured to obtain a radar image of a slope monitoring area at a preset time point; determine a phase diagram of the radar image based on a horizontal baseline and a vertical baseline in the radar image by using a preset phase algorithm; determine a slope deformation rate of the slope monitoring area based on a baseline interferometric pair of the phase diagram, a time interval of the baseline interferometric pair, and a measurement pair number of the baseline interferometric pair; and determine the first deformation parameter based on the slope deformation rate.

[0115] In some embodiments of the present disclosure, the second monitoring unit 320 is further configured to scan a slope monitoring area based on a laser scanner by using a scanning method of fixed single-station coordinate points to obtain a laser point cloud image; determine a filtered point cloud image based on the laser point cloud image by using a preset filtering algorithm; and determine the second deformation parameter based on the filtered point cloud image.

[0116] In some embodiments of the present disclosure, the second monitoring unit 320 is further configured to remove abnormal point clouds in the laser point cloud image based on the laser point cloud image by using a preset point cloud threshold to obtain a preprocessed point cloud image; determine a segmented point cloud image based on the preprocessed point cloud image by using a point cloud segmentation algorithm; grid the segmented point cloud image to obtain a slope grid image; perform plane fitting processing and plane rotation processing on the slope grid image in sequence to obtain a processed grid image; and filter the processed grid image by using a progressive densification triangular mesh filtering algorithm to obtain a filtered point cloud image.

[0117] In some embodiments of the present disclosure, the third monitoring unit 330 is further configured to perform multi-period data acquisition on the slope monitoring area based on a high-bitrate camera to obtain slope acquisition images; generate a three-dimensional color point cloud map based on the slope acquisition images by using digital photogrammetry technology; and determine a third deformation parameter based on the three-dimensional color point cloud map by using a differential analysis algorithm.

[0118] In some embodiments of the present disclosure, the fourth monitoring unit 340 is further configured to construct a reference coordinate system based on a preset checkerboard marker; obtain the two-dimensional coordinates of the preset checkerboard marker in the reference coordinate system based on a binocular video camera; determine the three-dimensional coordinates of the preset checkerboard marker by using a triangulation algorithm based on the two-dimensional coordinates; and determine a fourth deformation parameter based on the three-dimensional coordinates.

[0119] In summary, the slope monitoring device proposed according to the present disclosure includes: a first monitoring unit configured to determine a first deformation parameter of a slope detection area based on a radar image; a second monitoring unit configured to perform multi-period data acquisition on the slope detection area based on a laser scanner to determine a second deformation parameter of the slope monitoring area; a third monitoring unit configured to perform multi-period data acquisition on the slope detection area based on a high-bitrate camera to determine a third deformation parameter of the slope monitoring area; a fourth monitoring unit configured to monitor a preset checkerboard marker in the slope detection area based on a binocular video camera to determine a fourth deformation parameter of the slope monitoring area; and a fusion unit configured to determine a slope deformation result of the slope detection area based on the first deformation parameter, the second deformation parameter, the third deformation parameter, and the fourth deformation parameter. The device of the present disclosure improves the scientificity of slope monitoring and the accuracy of monitoring results by adopting multi-platform cooperation of satellite, aerial, and ground to detect slopes.

[0120] It should be noted that: when the slope monitoring device provided in the above embodiment performs slope monitoring, only the above division of each program module is used for illustration. In actual application, the above processing can be allocated to different program modules according to needs, that is, the internal structure of the slope monitoring device is divided into different program modules to complete all or part of the above-described processing.

[0121] Since the device provided in the embodiment of the present disclosure corresponds to the methods provided in the above several embodiments, the implementation manners of the methods are also applicable to the device provided in this embodiment and will not be described in detail in this embodiment.

[0122] In the embodiments provided by the present application described above, the methods and apparatuses provided by the embodiments of the present application are introduced. To implement each function in the methods provided by the embodiments of the present application, an electronic device may include a hardware structure, software modules, and implement the above functions in the form of a hardware structure, software modules, or a combination of a hardware structure and software modules. A certain function among the above functions may be executed in the form of a hardware structure, software modules, or a combination of a hardware structure and software modules.

[0123] Figure 4 Schematic diagram of the hardware composition structure of the electronic device provided by the embodiments of the present disclosure, as Figure 4 shown, the electronic device 400 includes at least one processor 402; and a memory 401 communicatively connected to the at least one processor 402; wherein, the memory 401 stores instructions executable by the at least one processor 402, and the instructions are executed by the at least one processor 402 to implement the steps of the slope monitoring method described in the embodiments of the present disclosure; or, the instructions are executed by the at least one processor 402 to implement the steps of the slope monitoring method described in the embodiments of the present disclosure.

[0124] It can be understood that the electronic device also includes a communication interface. Each component in the electronic device is coupled together through a bus system. It can be understood that the bus system is used to realize the connection and communication between these components. In addition to the data bus, the bus system also includes a power bus, a control bus, and a status signal bus.

[0125] It can be understood that the memory 401 can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory (ROM, Read Only Memory), a programmable read-only memory (PROM, Programmable Read-Only Memory), an erasable programmable read-only memory (EPROM, Erasable Programmable Read-Only Memory), an electrically erasable programmable read-only memory (EEPROM, Electrically Erasable Programmable Read-Only Memory), a ferromagnetic random access memory (FRAM, ferromagnetic random access memory), a flash memory (Flash Memory), a magnetic surface memory, an optical disc, or a compact disc read-only memory (CD-ROM, Compact Disc Read-Only Memory); the magnetic surface memory can be a disk memory or a tape memory. The volatile memory can be a random access memory (RAM, Random Access Memory), which is used as an external cache. By way of example but not limitation, many forms of RAM are available, such as a static random access memory (SRAM, Static Random Access Memory), a synchronous static random access memory (SSRAM, Synchronous Static Random Access Memory), a dynamic random access memory (DRAM, Dynamic Random Access Memory), a synchronous dynamic random access memory (SDRAM, Synchronous Dynamic Random Access Memory), a double data rate synchronous dynamic random access memory (DDRSDRAM, Double Data Rate Synchronous Dynamic Random Access Memory), an enhanced synchronous dynamic random access memory (ESDRAM, Enhanced Synchronous Dynamic Random Access Memory), a sync link dynamic random access memory (SLDRAM, SyncLink Dynamic Random Access Memory), a direct rambus random access memory (DRRAM, Direct Rambus Random Access Memory).The memory 401 described in the embodiments of this solution is intended to include but is not limited to these and any other suitable types of memory.

[0126] The method disclosed in the above embodiments of the present disclosure can be applied to or implemented by the processor 402. The processor 402 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the integrated logic circuit in hardware or instructions in software form in the processor 402.

[0127] The above-mentioned processor 402 may be a general-purpose processor, DSP, or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The processor 402 can implement or execute the various methods, steps, and logic block diagrams disclosed in the embodiments of this solution. The general-purpose processor may be a microprocessor or any conventional processor, etc. Combining the steps of the method disclosed in the embodiments of this solution, it can be directly embodied as being executed by a hardware decoding processor, or completed by a combination of hardware and software modules in the decoding processor. The software module may be located in a storage medium, and this storage medium is located in the memory 401. The processor 402 reads the information in the memory 401 and combines its hardware to complete the steps of the foregoing method.

[0128] In an exemplary embodiment, the electronic device can be implemented by one or more application-specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), FPGAs, general-purpose processors, controllers, MCUs, microprocessors, or other electronic components for executing the foregoing method.

[0129] The embodiments of the present disclosure also provide a non-transitory computer-readable storage medium storing computer instructions, and the computer instructions are used to implement the steps of the slope monitoring method described in the embodiments of this solution when the computer instructions are executed.

[0130] It should be noted that the terms "first", "second", etc. in the description of the present disclosure, the claims and the above-mentioned drawings are used to distinguish similar objects, and do not necessarily have to be used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged under appropriate circumstances, so that the embodiments of the present disclosure described here can be implemented in an order other than those illustrated or described here. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. On the contrary, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0131] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "schematic embodiments", "examples", "specific examples" or "some examples", etc. means that the specific features, structures, materials or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present solution. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0132] Any process or method description shown in the flowchart or described in other ways herein can be understood as representing a module, segment or portion of code including one or more executable instructions for implementing a specific logical function or process, and the scope of the preferred embodiments of the present solution includes additional implementations, where the functions can be executed in a manner that is not shown or discussed in sequence, including in a substantially simultaneous manner or in the reverse order according to the functions involved, which should be understood by those skilled in the technical field to which the embodiments of the present solution belong.

[0133] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a definite sequence list of executable instructions for implementing logical functions, and can be specifically implemented in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processing module, or other systems that can fetch and execute instructions from the instruction execution system, apparatus, or device), or used in conjunction with these instruction execution systems, apparatus, or devices. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by or in conjunction with an instruction execution system, apparatus, or device. More specific examples (non-exhaustive list) of computer-readable media include the following: an electrical connection portion with one or more wirings (control method), a portable computer diskette (magnetic device), a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber device, and a portable compact disc read-only memory (CDROM). Additionally, the computer-readable medium can even be paper or other suitable media on which a program can be printed, because the program can be obtained electronically, for example, by optically scanning the paper or other media, followed by editing, interpretation, or other suitable processing as necessary, and then stored in a computer memory.

[0134] It should be understood that each part of the implementation manner of the present solution can be implemented by hardware, software, firmware, or a combination thereof. In the above implementation manner, multiple steps or methods can be implemented by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented by hardware, as in another implementation manner, any one or a combination of the following techniques well known in the art can be used: discrete logic circuits with logic gate circuits for implementing logical functions on data signals, application-specific integrated circuits with suitable combinational logic gate circuits, programmable gate arrays (PGAs), field programmable gate arrays (FPGAs), etc.

[0135] Those of ordinary skill in the art of this technology can understand that all or part of the steps carried by the method of implementing the above embodiments can be completed by instructing relevant hardware through a program. The program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiments.

[0136] In addition, each functional unit in various embodiments of the present solution may be integrated into a processing module, may exist separately physically for each unit, or two or more units may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. When the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium. The above-mentioned storage medium may be a read-only memory, a magnetic disk, an optical disc, etc.

[0137] Although the embodiments of the present solution have been shown and described above, it can be understood that the above embodiments are exemplary and should not be construed as limitations on the present solution. Those of ordinary skill in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present solution.

Claims

1. A slope monitoring method, characterized in that: The method comprises: Based on the radar image, determining a first deformation parameter of the slope monitoring area; Based on a laser scanner, multiple data collection is performed on the slope monitoring area to determine a second deformation parameter of the slope monitoring area; Based on a high bit rate camera, multiple periods of data collection are performed on the slope monitoring area to determine a third deformation parameter of the slope monitoring area; Based on a binocular video camera, the preset chessboard markers in the slope monitoring area are monitored to determine a fourth deformation parameter of the slope monitoring area; Based on the first deformation parameter, the second deformation parameter, the third deformation parameter and the fourth deformation parameter, a slope deformation result of the slope monitoring area is determined.

2. The method according to claim 1, characterized in that The determining of the first deformation parameter of the slope monitoring area based on the radar image includes: Obtaining a radar image of the slope monitoring area at a preset time point; Based on the horizontal baseline and the vertical baseline in the radar image, a phase map of the radar image is determined using a preset phase algorithm; Determining a slope deformation rate of the slope monitoring area based on the baseline interferometric measurement pairs of the phase diagram, the time interval of the baseline interferometric measurement pairs, and the number of measurement pairs of the baseline interferometric measurement pairs; Based on the slope deformation rate, the first deformation parameter is determined.

3. The method according to claim 1, characterized in that The method of performing multi-period data collection on the slope monitoring area based on a laser scanner to determine the second deformation parameter of the slope monitoring area includes: Based on the laser scanner, the slope monitoring area is scanned by using a scanning method of a fixed single-station coordinate point to obtain a laser point cloud image; Based on the laser point cloud image, a filtered point cloud image is determined using a preset filtering algorithm; Based on the filtered point cloud image, the second deformation parameter is determined.

4. The method according to claim 3, characterized in that: Determining the filtered point cloud image based on the laser point cloud image by using a preset filtering algorithm includes: Based on the laser point cloud image, using a preset point cloud threshold, removing abnormal point clouds in the laser point cloud image to obtain a preprocessed point cloud image; Based on the preprocessed point cloud image, using a point cloud segmentation algorithm, determining a segmented point cloud image; Meshing the segmented point cloud image to obtain a slope mesh image; performing plane fitting processing and plane rotation processing on the slope grid image in sequence to obtain a processed grid image; The processed grid image is filtered using a progressively encrypted triangulated network filtering algorithm to obtain a filtered point cloud image.

5. The method according to claim 1, characterized in that The method of collecting multiple periods of data on the slope monitoring area based on a high bit rate camera to determine the third deformation parameter of the slope monitoring area includes: Based on a high bit rate camera, multiple phases of data collection are performed on the slope monitoring area to obtain a slope collection image; Based on the slope acquisition image, a three-dimensional color point cloud image is generated using digital photogrammetry technology; Based on the three-dimensional color point cloud image, the third deformation parameter is determined using a difference analysis algorithm.

6. The method according to claim 1, characterized in that The monitoring of the preset checkerboard markers in the slope monitoring area based on the binocular video camera to determine the fourth deformation parameter of the slope monitoring area includes: Based on the preset checkerboard markers, construct a reference coordinate system; Based on a binocular video camera, obtaining the two-dimensional coordinates of the preset checkerboard marker in the reference coordinate system; Based on the two-dimensional coordinates, using a triangulation algorithm, determining the three-dimensional coordinates of the preset checkerboard marker; Based on the three-dimensional coordinates, the fourth deformation parameter is determined.

7. A slope monitoring device, characterized in that: include: A first monitoring unit is used to determine a first deformation parameter of a slope detection area based on the radar image; A second monitoring unit is used to perform multi-period data collection on the slope detection area based on a laser scanner to determine a second deformation parameter of the slope monitoring area; A third monitoring unit is used to collect multi-period data of the slope detection area based on a high bit rate camera to determine a third deformation parameter of the slope monitoring area; a fourth monitoring unit, configured to monitor the preset checkerboard markers in the slope monitoring area based on a binocular video camera, and determine a fourth deformation parameter of the slope monitoring area; A fusion unit is used to determine the slope deformation result of the slope detection area based on the first deformation parameter, the second deformation parameter, the third deformation parameter and the fourth deformation parameter.

8. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method according to any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium storing computer instructions, characterized in that: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-6.

10. A computer program product, characterized in that The invention comprises a computer program which, when executed by a processor, implements the method according to any one of claims 1 to 6.

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