CN-122024100-A - Strip mine slope characteristic analysis method and system based on three-dimensional point cloud and unmanned aerial vehicle

CN122024100ACN 122024100 ACN122024100 ACN 122024100ACN-122024100-A

Abstract

The invention relates to the technical field of strip mine safety monitoring, and discloses a strip mine slope characteristic analysis method and system based on three-dimensional point cloud and unmanned aerial vehicle. According to the method, original three-dimensional point cloud data are acquired through an unmanned aerial vehicle and subjected to standardization processing, boundary lines of slope surface pieces are determined and segmented based on space geometric features, geometric feature parameters are extracted, deformation areas and displacement vectors are determined through registration and differential calculation of multi-time phase point cloud data, and stability assessment results are generated by combining side slope mechanics constraint conditions. The invention can realize accurate monitoring and stability assessment of slope deformation and improve the accuracy of slope safety early warning of the strip mine.

Inventors

Ge Shanfeng
LI SHENGLONG
LU PENG
ZHANG TIANCHENG
LIU GANG
LI JINGTAO
LI QINGYAO
CHAI SHUGANG
YANG XIAOWEI
WANG YANTAO
LI JIE
WANG HAIDONG

Assignees

北京捷翔天地信息技术有限公司
中煤平朔集团有限公司

Dates

Publication Date: 20260512
Application Date: 20260203

Claims (10)

1. The strip mine slope characteristic analysis method based on the three-dimensional point cloud and the unmanned aerial vehicle is characterized by comprising the following steps of: Acquiring original three-dimensional point cloud data of a strip mine slope area through a ranging sensor carried by an unmanned aerial vehicle, and carrying out standardization processing on the original three-dimensional point cloud data to obtain standardized three-dimensional point cloud data; determining a geometric boundary between slope surface pieces based on the space geometric features of the normalized three-dimensional point cloud data, and dividing the normalized three-dimensional point cloud data into a plurality of slope surface pieces according to the geometric boundary; Extracting geometric characteristic parameters representing the slope morphology aiming at each slope sheet, determining a deformation area in the slope sheet, which is deformed, through space registration and difference calculation of multi-time phase point cloud data based on the geometric characteristic parameters, and calculating a displacement vector of the deformation area; And according to the geometric characteristic parameters and the displacement vector, and by combining with the slope mechanics constraint condition, generating a slope stability evaluation result comprising a stability grade and a potential slip direction.
2. The method of claim 1, wherein obtaining raw three-dimensional point cloud data of a strip mine slope region by a ranging sensor carried by an unmanned aerial vehicle, normalizing the raw three-dimensional point cloud data to obtain normalized three-dimensional point cloud data, comprises: Acquiring original three-dimensional point cloud data of a strip mine slope area through a ranging sensor carried by an unmanned aerial vehicle, establishing a local neighborhood for each point in the original three-dimensional point cloud data, and determining noise points through calculating point cloud density distribution characteristics in the local neighborhood; Carrying out high Cheng Fenceng on the original three-dimensional point cloud data from which the noise points are removed, dividing the point cloud data into a plurality of elevation intervals according to the elevation direction, extracting local minimum points in each elevation interval, and taking a local minimum point set of the elevation intervals as a bottom boundary point; based on the spatial distribution characteristics of the bottom boundary points, the screened bottom boundary points are obtained after isolated points and abrupt points are removed by calculating the distance relation and elevation change characteristics between adjacent bottom boundary points; and performing surface fitting on the screened bottom boundary points to obtain a terrain reference surface of the slope region, and performing coordinate transformation on the original three-dimensional point cloud data with the noise points removed by taking the terrain reference surface as a reference standard to obtain the normalized three-dimensional point cloud data.
3. The method of claim 1, wherein determining a geometric demarcation between slope panels based on the spatial geometry of the normalized three-dimensional point cloud data, dividing the normalized three-dimensional point cloud data into a plurality of slope panels according to the geometric demarcation, comprises: calculating a vector for each point in the normalized three-dimensional point cloud data, and determining a point cloud normal vector field, wherein the point cloud normal vector field is used for representing the space geometric characteristics of the normalized three-dimensional point cloud data; Calculating normal vector angles between adjacent points based on the point cloud normal vector field, determining point pairs with normal vector angles exceeding normal vector consistency constraint, and marking the point pairs as candidate demarcation points; based on Euclidean distance and topological adjacency relation between the candidate demarcation points, connecting the candidate demarcation points with the distance meeting continuity constraint and the topological adjacency relation to obtain a candidate demarcation point chain; Performing length evaluation and direction consistency check on each candidate boundary point chain, and screening out candidate boundary point chains with lengths meeting validity constraint and direction changes meeting smoothness constraint as valid boundary point chains; And performing curve fitting on the effective demarcation point chain to generate a geometric demarcation line between the edge slope surface pieces, and dividing the normalized three-dimensional point cloud data into a plurality of edge slope surface pieces according to the geometric demarcation line.
4. The method according to claim 1, wherein extracting geometric feature parameters characterizing a slope morphology for each edge-slope sheet, determining a deformed region in the edge-slope sheet where deformation occurs by spatial registration and differential calculation of multi-temporal point cloud data based on the geometric feature parameters, and calculating a displacement vector of the deformed region, comprises: Performing local surface fitting on point cloud data in each side slope sheet according to each side slope sheet, and calculating to obtain geometrical characteristic parameters representing the side slope morphology based on the fitted surfaces; acquiring multi-time phase point cloud data acquired at different moments, and respectively extracting point cloud data corresponding to the same side slope sheet in the multi-time phase point cloud data as a reference time phase point cloud and a target time phase point cloud; Taking the geometric characteristic parameters of the reference time phase point cloud as registration constraint, and carrying out spatial registration transformation on the target time phase point cloud by determining the spatial correspondence between the reference time phase point cloud and the target time phase point cloud to obtain a registered target time phase point cloud; Calculating the point-to-point distance between the registered target time phase point cloud and the reference time phase point cloud to generate a point cloud differential result, and determining a deformed region in the edge slope sheet based on the point cloud differential result; And calculating the spatial displacement between the position of the corresponding point in the reference time phase point cloud and the position in the registered target time phase point cloud of each point in the deformation region to obtain a displacement vector of the deformation region.
5. The method of claim 4, wherein calculating a point-to-point distance between the registered target time phase point cloud and the reference time phase point cloud generates a point cloud differential result, and determining a deformed region in the edge-slope sheet that is deformed based on the point cloud differential result comprises: Searching a corresponding point closest to the point in the reference time phase point cloud for each point in the registered target time phase point cloud, and calculating Euclidean distance between the point and the corresponding point as a point-to-point distance; obtaining a point cloud differential result based on the point-to-point distances of all points in the slope surface piece, wherein the point cloud differential result represents the spatial variation distribution of the slope surface piece on a time sequence; performing spatial clustering analysis on the point cloud difference result, and dividing the point cloud difference result into a plurality of clustering clusters by calculating the spatial distribution density of the point-to-point distances and the neighborhood similarity characteristics; Carrying out statistical analysis on each cluster, and screening out clusters, the statistical characteristic values of which meet deformation detection constraint, from the clusters based on the statistical characteristic values of the point-to-point distances in the clusters, and taking the clusters as candidate deformation areas; And carrying out boundary extraction and region connectivity verification on the candidate deformed regions, removing isolated regions with areas not meeting the validity constraint, and determining the reserved candidate deformed regions as deformed regions with deformation in the slope sheet.
6. The method of claim 1, wherein generating a slope stability assessment result comprising a stability class and a potential slip direction based on the geometric feature parameter and the displacement vector in combination with a slope mechanical constraint condition comprises: Calculating the critical slip angle of each edge slope sheet based on the gradient angle and the normal vector in the geometric characteristic parameters, and calculating the displacement rate and the displacement accumulation amount of the deformation area based on the direction and the amplitude of the displacement vector; comparing and analyzing the gradient angle in the geometric characteristic parameter with the critical slip angle, and determining a slope mechanical state evaluation index by combining the displacement rate and the displacement accumulation; Carrying out weighted fusion on the slope mechanical state evaluation index and the slope material strength constraint and the slope geometric form constraint in the slope mechanical constraint condition to obtain a slope comprehensive stability index; Comparing the comprehensive stability index of the side slope with a preset stability grading threshold value to determine the stability grade corresponding to the side slope surface piece; based on the space distribution characteristics of the displacement vectors and normal vectors in the geometric characteristic parameters, determining a dominant displacement direction of a deformation area as a potential slip direction by calculating a projection component and a tangential component of the displacement vectors in the direction of a normal vector of a side slope sheet; And combining the stability grade with the potential slip direction to obtain a slope stability evaluation result.
7. The method of claim 6, wherein comparing the slope angle in the geometric characteristic parameter with the critical slip angle, and determining the slope mechanical state evaluation index in combination with the displacement rate and the displacement accumulation amount, comprises: Calculating an angle difference value between the gradient angle and the critical slip angle, and carrying out geometric form correlation correction on the angle difference value based on the gradient height and the gradient length of the edge slope surface piece to obtain a geometric safety margin of the edge slope surface piece; Performing differential operation based on a displacement rate time sequence formed by displacement rates at a plurality of moments, calculating rate variation between displacement rates at adjacent moments, and determining a displacement acceleration sequence based on the rate variation; Extracting trend characteristics of the displacement acceleration sequence, and identifying phase characteristics of different phases to be quantized into change trend characteristics by analyzing monotonicity and fluctuation of the displacement acceleration sequence; Nonlinear mapping is carried out on the change trend characteristics and the displacement accumulation amount, and a deformation evolution index is obtained by applying a preset time sensitive weight to the change trend characteristics and carrying out coupling operation on the change trend characteristics and the displacement accumulation amount; And performing coupling calculation on the geometric safety margin and the deformation evolution index to obtain a slope mechanical state evaluation index.
8. Strip mine slope feature analysis system based on three-dimensional point cloud and unmanned aerial vehicle, for implementing the method according to any one of claims 1 to 7, characterized by comprising: The first unit is used for acquiring original three-dimensional point cloud data of a strip mine slope area through a ranging sensor carried by an unmanned aerial vehicle, and carrying out standardization processing on the original three-dimensional point cloud data to obtain standardized three-dimensional point cloud data; The second unit is used for determining a geometric boundary between the slope surface pieces based on the space geometric characteristics of the normalized three-dimensional point cloud data, and dividing the normalized three-dimensional point cloud data into a plurality of slope surface pieces according to the geometric boundary; the third unit is used for extracting geometric characteristic parameters representing the slope morphology for each slope surface piece, determining a deformation area in the slope surface piece through space registration and difference calculation of multi-time phase point cloud data based on the geometric characteristic parameters, and calculating a displacement vector of the deformation area; And the fourth unit is used for generating a slope stability evaluation result comprising a stability grade and a potential slip direction according to the geometric characteristic parameter and the displacement vector and by combining a slope mechanical constraint condition.
9. An electronic device, comprising: A processor; A memory for storing processor-executable instructions; Wherein the processor is configured to invoke the instructions stored in the memory to perform the method of any of claims 1 to 7.
10. A computer readable storage medium having stored thereon computer program instructions, which when executed by a processor, implement the method of any of claims 1 to 7.

Description

Strip mine slope characteristic analysis method and system based on three-dimensional point cloud and unmanned aerial vehicle Technical Field The invention relates to the technical field of strip mine safety monitoring, in particular to a strip mine side slope characteristic analysis method and system based on three-dimensional point cloud and unmanned aerial vehicle. Background Slope stability analysis in the process of mining of strip mines is a key link for guaranteeing production safety. Traditional slope monitoring methods mainly rely on manual field measurement or fixed monitoring equipment, and the methods are limited by factors such as measurement frequency, coverage range, working environment and the like. With the development of unmanned aerial vehicle technology and three-dimensional point cloud data acquisition technology, three-dimensional point cloud data of the strip mine slope are acquired by using unmanned aerial vehicle-mounted ranging sensors, and a new technical means is provided for slope characteristic analysis. At present, various technical schemes exist in the aspect of slope characteristic analysis of strip mines, and the technical schemes mainly comprise an analysis method based on optical images, a ground laser radar scanning method, a traditional manual measurement method and the like. These methods have achieved some success in slope feature extraction and stability assessment, but have some technical drawbacks and limitations. The traditional slope characteristic extraction method is difficult to realize automatic segmentation of the slope surface pieces, and the geometrical boundaries of the slope surface pieces are usually determined by manual intervention, so that the workload is increased, subjective judgment errors are easily introduced, and the consistency and the accuracy of analysis results cannot be ensured. The lack of an effective registration and differential calculation method in the aspect of multi-time phase point cloud data processing in the prior art leads to difficulty in accurately identifying and quantitatively analyzing a slope deformation area, and particularly has lower deformation detection precision and reliability under complex terrain conditions. The existing slope stability evaluation method is often focused on single geometric parameters or experience judgment, lacks a comprehensive analysis framework combining the slope geometric characteristics, deformation monitoring results and slope mechanical constraint conditions, and is difficult to provide comprehensive evaluation results containing key information such as stability grade, potential slip direction and the like. Disclosure of Invention The embodiment of the invention provides a strip mine slope characteristic analysis method and a strip mine slope characteristic analysis system based on three-dimensional point cloud and unmanned aerial vehicle, which at least can solve part of problems existing in the prior art. In a first aspect of the embodiment of the invention, a method for analyzing characteristics of a strip mine slope based on three-dimensional point cloud and unmanned aerial vehicle is provided, which comprises the following steps: Acquiring original three-dimensional point cloud data of a strip mine slope area through a ranging sensor carried by an unmanned aerial vehicle, and carrying out standardization processing on the original three-dimensional point cloud data to obtain standardized three-dimensional point cloud data; determining a geometric boundary between slope surface pieces based on the space geometric features of the normalized three-dimensional point cloud data, and dividing the normalized three-dimensional point cloud data into a plurality of slope surface pieces according to the geometric boundary; Extracting geometric characteristic parameters representing the slope morphology aiming at each slope sheet, determining a deformation area in the slope sheet, which is deformed, through space registration and difference calculation of multi-time phase point cloud data based on the geometric characteristic parameters, and calculating a displacement vector of the deformation area; And according to the geometric characteristic parameters and the displacement vector, and by combining with the slope mechanics constraint condition, generating a slope stability evaluation result comprising a stability grade and a potential slip direction. Acquiring original three-dimensional point cloud data of a strip mine slope area through a ranging sensor carried by an unmanned aerial vehicle, carrying out standardization processing on the original three-dimensional point cloud data to obtain standardized three-dimensional point cloud data, wherein the method comprises the following steps of: Acquiring original three-dimensional point cloud data of a strip mine slope area through a ranging sensor carried by an unmanned aerial vehicle, establishing a local neighborhood for each point in the or