A kind of open-pit mine slope deformation monitoring method based on timing topographic parameters

Abstract

The present application provides a kind of open-pit mine slope deformation monitoring method based on timing topographic parameters, belong to slope deformation monitoring technical field.This method is by efficient collection mine slope area radar satellite image and unmanned aerial vehicle high frequency DEM data, after data processing and feature calculation, respectively obtain ascending track, descending track radar LOS one-dimensional deformation result and timing topographic parameters, including slope, slope direction, topographic curvature;Based on mining activity cycle dynamic update timing topographic parameters, construct radar line-of-sight direction deformation and surface self-adapting deformation projection model, solve mine slope three-dimensional deformation result, realize dynamic monitoring.The present application solves the problem of insufficient precision of slope deformation monitoring caused by dynamic change of topographic parameters, forms a set of from data acquisition, parameter updating to model solving precision slope deformation monitoring system, breaks through the limitation of traditional method in precision and dynamic adaptability, provides technical support for open-pit mine slope safe operation.

Description

Technical Field

[0001] This specification relates to the field of slope deformation monitoring technology, and in particular to a method for monitoring slope deformation in open-pit mines based on time-series topographic parameters. Background Technology

[0002] Open-pit mining is an important part of my country's mining industry. Compared with underground mining, it has advantages such as lower cost, higher efficiency, and shorter cycle, and is a significant driving force for resource supply and improved economic benefits. With the continuous development of open-pit mines, the height and angle of slopes gradually increase. Slopes are susceptible to cumulative deformation and structural damage due to various factors such as geological structure, soil properties, rainfall, and blasting vibrations, thus affecting slope stability. Once an open-pit mine slope becomes unstable, it can cause a series of serious consequences, including casualties, equipment damage, production stoppages, and property losses, resulting in huge economic losses for the mine. Therefore, researching open-pit mine slope deformation monitoring methods, timely detection of slope anomalies, and the implementation of scientific prevention and control measures are of great significance to ensuring safe production in mines.

[0003] Existing technologies for monitoring slope deformation in open-pit mines mainly include InSAR time-series analysis based on single ascending or descending orbit SAR imagery, joint calculation of three-dimensional deformation using ascending and descending orbit data, and analysis aided by static topographic parameters. While these methods have some applications, they have significant drawbacks. Single-orbit SAR imagery can only obtain one-dimensional deformation results along the radar line of sight (LOS) direction. The method of jointly calculating three-dimensional deformation using ascending and descending orbit data relies on the one-dimensional deformation results from both radar line of sight (LOS) directions. Solving for deformation in the vertical, east-west, and north-south directions involves inherent uncertainty. Typically, simplified assumptions (such as ignoring north-south deformation) are used to constrain the model, which is often unsuitable for the complex slope movements in open-pit mines, leading to misjudgments of deformation direction and distortion of magnitude. Static topographic parameter-assisted analysis methods use a single-period digital elevation model (DEM) to calculate slope, aspect, and projection vector. However, continuous mining activities in open-pit mines (blasting, benching, spoil heap filling, etc.) cause drastic changes in surface topography on a monthly or even perimeter scale. If single-period DEM parameters are still used, they cannot reflect the true topographic changes, resulting in the inability to quickly capture potential landslide trends induced by changes in topographic parameters. Secondly, the stability of mine slopes is directly affected by changes in slope, aspect, and topographic curvature. Existing methods ignore the inherent coupling mechanism between these topographic parameters and deformation, relying only on the cumulative deformation threshold to judge risk, without coupling dynamic topographic parameters.

[0004] In summary, the shortcomings of existing open-pit mine slope deformation monitoring methods are mainly reflected in the mismatch between the dynamic mining environment and the static monitoring model, the lack of kinematic constraints in the three-dimensional deformation inversion method, the lag of terrain parameter updates behind engineering activities, and the failure to couple the synergistic effect of terrain deformation in risk assessment. These shortcomings make it difficult to meet the needs of refined management of open-pit mine slope stability, and have a significant impact on monitoring, early warning, and safe production. Summary of the Invention

[0005] To address the aforementioned shortcomings in existing technologies, this invention provides a method for monitoring open-pit mine slope deformation based on time-series topographic parameters, which solves the problem of inaccurate monitoring of open-pit mine slope deformation.

[0006] To achieve the aforementioned objectives, the technical solution adopted by this invention is: a method for monitoring slope deformation in open-pit mines based on time-series topographic parameters, comprising:

[0007] S1: Process the rising-orbit synthetic aperture radar satellite imagery and the falling-orbit synthetic aperture radar satellite imagery covering the same slope area of ​​the open-pit mine to obtain the one-dimensional deformation result of the slope along the radar line of sight.

[0008] S2: Based on high-frequency digital elevation model data covering the same slope area of ​​an open-pit mine, a set of time-series terrain parameters is obtained through calculation;

[0009] S3: Based on the mining activity cycle, update the time-series terrain parameter set to obtain the dynamic update result of the time-series terrain parameters;

[0010] S4: Using the one-dimensional deformation results of the slope along the radar line of sight and the dynamic update results of the time-series terrain parameters, a projection model of the deformation along the radar line of sight and the adaptive deformation of the ground surface is established to obtain the three-dimensional deformation field under the constraint of the actual geometric shape of the slope.

[0011] S5: Based on the one-dimensional deformation results of the slope along the radar line of sight and the dynamic update results of the time-series terrain parameters, the overdetermined equations of the three-dimensional deformation field are solved to obtain the deformation monitoring results of the open-pit mine slope, thus completing the monitoring of the deformation of the open-pit mine slope.

[0012] Further, S1 includes:

[0013] S110: Acquire rising-orbit synthetic aperture radar satellite imagery, falling-orbit synthetic aperture radar satellite imagery, and digital elevation model data of the study area covering the same slope area of ​​an open-pit mine.

[0014] S120: Select one image from N ascending-orbit synthetic aperture radar satellite images as the master image. The images other than the master image are registered with the master image as a reference. According to the set time and space baseline thresholds, the N ascending-orbit synthetic aperture radar satellite images are combined in pairs to generate a total of M differential interferometric pairs. The phase formed after unwrapping the M differential interferometric pairs is calculated to obtain the overall ascending-orbit deformation information.

[0015] S130: Select one image from N de-orbiting synthetic aperture radar (SAR) satellite images as the master image. Register the other images with reference to the master image. Based on the set time and space baseline thresholds, combine the N ascending SAR satellite images in pairs to generate a total of M differential interferometric pairs. Calculate the phase formed after unwrapping the M differential interferometric pairs using the least squares method and singular value decomposition method to obtain the overall de-orbiting deformation information.

[0016] S140: Combining satellite orbit data, imaging geometric model, and digital elevation model data, the flat-ground phase and terrain phase in the interferograms of ascending and descending orbit deformation information are removed. Based on the coherence coefficient diagram, phase unwrapping is performed on all interferograms to obtain unwrapped differential interferometric phases without digital elevation model errors. After two model inversions and geocoding using small baseline ensemble aperture radar interferometry, the cumulative deformation results on the complete time series of ascending and descending orbit synthetic aperture radar satellite images are obtained as one-dimensional deformation results.

[0017] Further, S2 includes:

[0018] S210: Collect UAV images of the slope area of ​​the open-pit mine at a fixed cycle to obtain UAV image data, ground control point data and UAV position and attitude information data.

[0019] S220: Preprocess UAV imagery data, ground control point data, and UAV position and attitude information data to obtain high-frequency digital elevation model data;

[0020] S230: Perform parameter calculations on high-frequency digital elevation model data at fixed intervals to obtain a time-series terrain parameter set.

[0021] Further, S3 includes:

[0022] S310: Based on engineering data, mining activities are divided into multiple cycles with major disturbance events as nodes, resulting in a set of cycle time nodes;

[0023] S320: Based on the set of periodic time nodes, calculate the digital elevation model data of adjacent periods to obtain the pixel-level slope change;

[0024] S330: Normalize the pixel-level slope change to obtain the perturbation weighting factor;

[0025] S340: Based on the perturbation weight factor, the time-series terrain parameter set is updated to obtain the dynamic update result of the time-series terrain parameters.

[0026] Furthermore, the expression for the perturbation weighting factor is:

[0027] ;

[0028] ;

[0029] in, Indicates the perturbation weighting factor. This represents the change in slope at the pixel level. This indicates taking the absolute value. This represents the function that takes the maximum value. ( () represents the slope calculated from the DEM data acquired at time point t. ( The slope is calculated from the DEM data obtained at time point t-1.

[0030] Further, S4 includes:

[0031] S410: Analyze the relationship between the observed values ​​of deformation in the line-of-sight direction of the ascending radar, the observed values ​​of deformation in the line-of-sight direction of the descending radar, and the three-dimensional deformation to obtain the ascending relationship representation and the descending relationship representation;

[0032] S420: Based on the dynamic update results of time-series terrain parameters, and using terrain parameter constraints, construct a priori constraints on deformation direction;

[0033] S430: Substitute the a priori constraints of deformation direction into the ascending orbit relation and descending orbit relation respectively, construct an overdetermined set of equations, establish a projection model of radar line-of-sight deformation and surface adaptive deformation, and obtain the three-dimensional deformation field under the constraints of the actual geometric shape of the slope.

[0034] Furthermore, the expressions for the ascending orbit relationship and the descending orbit relationship are as follows:

[0035] ;

[0036] in, This indicates the deformation result of the LOS-axis of the ascending orbit data. This indicates the deformation result of the LOS-axis in the down-orbit data. Indicates the vertical deformation value. The radar incident angle indicating the orbital ascent. The radar incident angle indicating the descent orbit. Indicates the east-west deformation value. Indicates the azimuth angle of the satellite as it ascends to orbit. Indicates the azimuth angle of the satellite in its descending orbit. Indicates the north-south deformation value. This represents the noise term for the ascending track. This represents the noise term for the descending orbit.

[0037] Furthermore, the a priori constraints on deformation direction include vertical deformation constraints, horizontal deformation constraints, and terrain curvature, wherein the expression for the vertical deformation constraint is:

[0038] ;

[0039] The expression for the horizontal deformation constraint is:

[0040] ;

[0041] ;

[0042] ;

[0043] in, This indicates a vertical deformation constraint. This represents the proportionality coefficient. Indicates changes in slope. Indicates horizontal deformation constraint. Indicates east-west deformation constraints. Indicates north-south deformation constraint. Indicates the slope angle. Indicates the radar incident angle.

[0044] Furthermore, the objective function of the projection model is expressed as follows:

[0045] ;

[0046] ;

[0047] ;

[0048] ;

[0049] in, Minimization represents an optimization process that minimizes the value of an expression. This represents the terrain geometry weight matrix, used to define the covariance structure of the vertical and horizontal deformation components in the weighted least squares objective function. Represents the design matrix. This represents the three-dimensional deformation to be determined. Represents the observation vector. This represents the horizontal deformation weighting factor. Indicates the current pixel in time The curvature of the terrain, This indicates that all pixels within the study area are in time. The minimum absolute value of curvature, This indicates that all pixels within the study area are in time. The maximum value of the absolute value of curvature, This represents the vertical deformation weighting factor.

[0050] Further, S5 includes:

[0051] Based on the one-dimensional deformation results of the slope along the radar line of sight and the dynamic update results of the time-series topographic parameters, the overdetermined equations of the three-dimensional deformation field are solved to obtain the three-dimensional deformation variables U, E, N of each pixel point of the open-pit mine slope; among them, the vertical deformation U reflects the slope settlement or uplift, and the horizontal deformation E and N are decomposed into slope-direction and transverse deformation in combination with the slope aspect.

[0052] Based on the three-dimensional deformation of each pixel, the slip trend is analyzed to obtain the monitoring results of open-pit mine slope deformation, thus completing the monitoring of open-pit mine slope deformation.

[0053] The beneficial effects of this invention are as follows: This invention provides a method for monitoring slope deformation in open-pit mines based on time-series topographic parameters. By integrating high-frequency UAV topographic monitoring with multi-track InSAR technology, a three-dimensional deformation field constrained by the actual geometric shape of the slope is established, solving the problem of insufficient accuracy in LOS-direction deformation monitoring caused by dynamic changes in slope and aspect. First, monthly-scale UAV oblique photogrammetry is used to dynamically acquire topographic parameters such as slope and aspect, ensuring that the topographic model is updated synchronously with mining activities. Second, based on the slope change, aspect angle, and topographic curvature, a priori constraints on the deformation direction are constructed, establishing an adaptive projection model of InSAR radar LOS-direction deformation and the three-dimensional deformation field of the surface. Finally, by integrating the three-dimensional deformation field and dynamic topographic parameters, the three-dimensional deformation of the mine is calculated, effectively improving the reliability, accuracy, and early warning timeliness of open-pit mine slope deformation monitoring, providing precise decision support for safe mining. Attached Figure Description

[0054] This specification will be further described by way of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not limiting; in these embodiments, the same reference numerals denote the same structures, wherein:

[0055] Figure 1 This is an exemplary flowchart illustrating a method for monitoring the deformation of open-pit mine slopes based on time-series topographic parameters, according to some embodiments of this specification. Detailed Implementation

[0056] The specific embodiments of the present invention are described below to enable those skilled in the art to understand the present invention. However, it should be understood that the present invention is not limited to the scope of the specific embodiments. For those skilled in the art, various changes are obvious as long as they are within the spirit and scope of the present invention as defined and determined by the appended claims. All inventions utilizing the concept of the present invention are protected.

[0057] Example

[0058] Figure 1 This is an exemplary flowchart illustrating a method for monitoring slope deformation in open-pit mines based on time-series topographic parameters, according to some embodiments of this specification. Figure 1 As shown, the process includes the following steps. In some embodiments, the process may be executed by a processor.

[0059] S1: Process the rising-orbit synthetic aperture radar (SAR) satellite images and falling-orbit SAR satellite images covering the same slope area of ​​the open-pit mine to obtain the one-dimensional deformation results of the slope along the radar line of sight.

[0060] Up-orbit synthetic aperture radar (SAR) satellite imagery is imagery data covering the same slope area of ​​an open-pit mine, monitored during the up-orbit process of SAR satellite imagery.

[0061] Down-orbit synthetic aperture radar (SAR) satellite imagery is imagery data covering the same slope area of ​​an open-pit mine, monitored during the down-orbit process of SAR satellite imagery.

[0062] In some embodiments, to ensure the effectiveness of SBAS-InSAR timing processing, the number of ascending-orbit synthetic aperture radar satellite images and descending-orbit synthetic aperture radar satellite images shall not be less than N (N≥20) images.

[0063] The one-dimensional deformation results of the slope along the radar line of sight are the SBAS-InSAR time-series deformation results of ascending-orbit synthetic aperture radar (SAR) satellite imagery and descending-orbit SAR satellite imagery.

[0064] In some embodiments, the processor may implement S1 based on the following steps.

[0065] S110: Acquire rising-orbit synthetic aperture radar (SAR) satellite imagery, falling-orbit SAR satellite imagery, and digital elevation model data of the study area covering the same slope area of ​​an open-pit mine.

[0066] The digital elevation model data has a resolution of 30 meters and is used to perform geolocation correction on SAR satellite data.

[0067] S120: Select one image from N ascending-orbit synthetic aperture radar (SAR) satellite images as the master image. Register the other images with reference to the master image. Based on the set time and space baseline thresholds, combine the N ascending-orbit SAR satellite images in pairs to generate a total of M differential interferometric pairs. Calculate the phase formed after unwrapping the M differential interferometric pairs using the least squares method and singular value decomposition method to obtain the overall ascending-orbit deformation information.

[0068] The up-track deformation information is the cumulative deformation result over the complete time series of up-track image data.

[0069] S130: Select one image from N de-orbiting synthetic aperture radar (SAR) satellite images as the master image. Register the other images with reference to the master image. Based on the set time and space baseline thresholds, combine the N ascending SAR satellite images in pairs to generate a total of M differential interferometric pairs. Calculate the phase formed after unwrapping the M differential interferometric pairs using the least squares method and singular value decomposition method to obtain the overall de-orbiting deformation information.

[0070] The deformation information of the de-orbiting image data is the cumulative deformation result over the complete time series of the de-orbiting image data.

[0071] S140: Combining satellite orbit data, imaging geometric model, and digital elevation model data, the flat-ground phase and terrain phase in the interferograms of ascending and descending orbit deformation information are removed. Based on the coherence coefficient diagram, phase unwrapping is performed on all interferograms to obtain unwrapped differential interferometric phases without digital elevation model errors. After two model inversions and geocodings using Small Baseline Assembled Aperture Radar Interferometry (SBAS-InSAR) technology, the cumulative deformation results on the complete time series of ascending and descending orbit synthetic aperture radar satellite images are obtained as one-dimensional deformation results.

[0072] S2: Based on high-frequency digital elevation model data covering the same slope area of ​​an open-pit mine, a time-series terrain parameter set is obtained through calculation.

[0073] Digital elevation model data is digital elevation model (DEM) data that covers the same slope area of ​​an open-pit mine.

[0074] The temporal terrain parameter set is a dataset of temporal terrain parameters that covers the same slope area of ​​an open-pit mine and has high temporal resolution (monthly scale).

[0075] In some embodiments, the processor may implement S2 based on the following steps.

[0076] S210: Collect UAV images of the open-pit mine slope area at fixed intervals to obtain UAV image data, ground control point data (GCP), and UAV position and attitude information (POS).

[0077] Drone image data consists of raw image files (a series of high-resolution digital photos) and image metadata (each photo embeds information automatically recorded by the drone system, usually associated with POS data) acquired by the camera on the drone.

[0078] Ground control point data consists of markers with known precise coordinates set up within the survey area. It is crucial for converting the UAV model to the real-world coordinate system and controlling its absolute accuracy. This includes GCP targets, GCP measurement coordinates, and deployment schemes.

[0079] The position and attitude information data of a UAV is the trajectory and attitude data recorded in real time by the UAV's positioning and attitude determination system during flight, including information such as time, longitude, latitude, ellipsoidal altitude, pitch angle, heading angle, and speed.

[0080] In some embodiments, the processor can perform UAV imagery acquisition on a monthly basis for the slope area of ​​an open-pit mine. Each flight ensures that the coverage area remains consistent with the same slope area of ​​the open-pit mine, while acquiring high-precision ground control point (GCP) data and UAV POS data.

[0081] S220: Preprocesses UAV imagery data, ground control point data, and UAV position and attitude information data to obtain high-frequency digital elevation model data.

[0082] High-frequency digital elevation model data is high-resolution and timely data used to calculate time-series terrain parameters.

[0083] In some embodiments, the processor can perform aerial triangulation, point cloud matching, and other processing on UAV image data, ground control point data, and UAV position and attitude information data, and generate digital elevation model (DEM) data based on the point cloud data using the Kriging interpolation algorithm.

[0084] S230: Perform parameter calculations on high-frequency digital elevation model data at fixed intervals to obtain a time-series terrain parameter set.

[0085] In some embodiments, the processor can repeatedly calculate parameters such as slope (α), aspect (β), and topographic curvature (K) for each pixel point in the study area on a monthly basis to obtain a set of temporal topographic parameters covering the same slope area of ​​the open-pit mine with high temporal resolution (monthly scale).

[0086] S3: Based on the mining activity cycle, update the time-series terrain parameter set to obtain the dynamic update results of the time-series terrain parameters.

[0087] The dynamic update results of temporal terrain parameters are based on periodically updated temporal terrain parameters.

[0088] In some embodiments, the processor may implement S3 based on the following steps.

[0089] S310: Based on engineering data, mining activities are divided into multiple cycles with major disturbance events as nodes, resulting in a set of cycle time nodes.

[0090] Engineering data includes mining plans, blasting records, and spoil disposal schedules.

[0091] The set of periodic time nodes is the set of periods into which mining activities are divided. For example, the set of periodic time nodes can be represented as follows: , The initial time, For the current period.

[0092] In some embodiments, the processor can divide mining activities into several cycles based on engineering data such as mining plans, blasting records, and spoil disposal progress, using major disturbance events (such as blasting or large-scale excavation) as nodes, to obtain a set of cycle time nodes.

[0093] S320: Based on the set of periodic time nodes, calculate the pixel-level slope change from the digital elevation model data of adjacent periods.

[0094] S330: Normalize the pixel-level slope change to obtain the perturbation weight factor.

[0095] Perturbation weighting factor It is a normalization factor characterizing the degree to which a region is affected by mining activities. For example, The closer it is to 1, the more severely the cell is affected by mining activities (such as blasting zones). The closer it is to 0, the more stable the terrain.

[0096] In some embodiments, the expression for the perturbation weighting factor can be:

[0097] ;

[0098] ;

[0099] in, Indicates the perturbation weighting factor. This represents the change in slope at the pixel level. This indicates taking the absolute value. This represents the function that takes the maximum value. ( () represents the slope calculated from the DEM data acquired at time point t. ( The slope is calculated from the DEM data obtained at time point t-1.

[0100] S340: Based on the perturbation weight factor, the time-series terrain parameter set is updated to obtain the dynamic update result of the time-series terrain parameters.

[0101] In some embodiments, slope slope direction Topographic curvature .in , The changes in slope and aspect caused by mining activities are calculated by the difference between two adjacent DEM periods. The curvature change is calculated using the elevation matrix of the DEM.

[0102] S4: Using the one-dimensional deformation results of the slope along the radar line of sight and the dynamic update results of the time-series terrain parameters, a projection model of the deformation along the radar line of sight and the adaptive deformation of the ground surface is established to obtain the three-dimensional deformation field under the constraint of the actual geometric shape of the slope.

[0103] The projection model of radar line-of-sight deformation and adaptive surface deformation is a mathematical model used to analyze the projection of radar line-of-sight deformation and adaptive surface deformation.

[0104] In some embodiments, the processor may implement S4 based on the following steps.

[0105] S410: Perform relationship analysis on the observation values ​​of line-of-sight (LOS) deformation of the rising orbit radar, the observation values ​​of LOS deformation of the falling orbit radar, and the three-dimensional deformation to obtain the relationship representation of rising orbit and falling orbit.

[0106] The ascending orbit relationship represents the relationship between the LOS deformation observations of ascending orbit data and the three-dimensional deformations (vertical U, east-west E, and north-south N).

[0107] The LOS-direction deformation observation of the LOS-direction data represents the relationship between the three-dimensional deformation (vertical U, east-west E, and north-south N).

[0108] In some embodiments, the expressions for ascending and descending orbit relationships can be:

[0109] ;

[0110] in, This indicates the deformation result of the LOS-axis of the ascending orbit data. This indicates the deformation result of the LOS-axis in the down-orbit data. Indicates the vertical deformation value. The radar incident angle indicating the orbital ascent. The radar incident angle indicating the descent orbit. Indicates the east-west deformation value. Indicates the azimuth angle of the satellite as it ascends to orbit. Indicates the azimuth angle of the satellite in its descending orbit. Indicates the north-south deformation value. This represents the noise term for the ascending track. This represents the noise term for the descending orbit.

[0111] S420: Based on the dynamic update results of time-series terrain parameters, a priori constraints on deformation direction are constructed using terrain parameter constraints.

[0112] Terrain parameter constraints are mathematical rules that use dynamically updated terrain parameters (slope, aspect, curvature) with clear physical meaning to limit and guide the three-dimensional deformation field inversion process. They mainly include constraints on deformation direction, deformation level, and deformation contribution weight.

[0113] Deformation direction prior constraints are used to predefine the possible directions of deformation based on terrain parameter constraints (i.e., dynamically updated terrain parameters) before solving for 3D deformation. These mainly include vertical deformation constraints, horizontal deformation constraints, and terrain curvature constraints.

[0114] In some embodiments, dynamically updated terrain curvature The main adjustment involves the relative weights of vertical and horizontal deformations in the model. The larger the stress concentration area (such as the shoulder or toe of a slope), the greater the contribution of horizontal deformation to the radar line-of-sight (LOS) deformation, and the smaller the contribution of vertical deformation.

[0115] In some embodiments, the expression for the vertical deformation constraint can be:

[0116] ;

[0117] in, This indicates a vertical deformation constraint. This represents the proportionality coefficient. Indicates changes in slope.

[0118] In some embodiments, the expression for the horizontal deformation constraint is:

[0119] ;

[0120] ;

[0121] ;

[0122] in, Indicates horizontal deformation constraint. Indicates east-west deformation constraints. Indicates north-south deformation constraint. Indicates the slope angle. Indicates the radar incident angle.

[0123] S430: Substitute the a priori constraints of deformation direction into the ascending orbit relation and descending orbit relation respectively, construct an overdetermined set of equations, establish a projection model of radar line-of-sight deformation and surface adaptive deformation, and obtain the three-dimensional deformation field under the constraints of the actual geometric shape of the slope.

[0124] The overdetermined equations are a set of equations that reflect the deformation of the radar line of sight and the adaptive deformation projection of the ground surface.

[0125] In some embodiments, the processor can construct a weighted least squares objective function, substitute the constraints into the ascending and descending orbit equations, and construct an overdetermined system of equations. .

[0126] In some embodiments, the objective function of the projection model is expressed as:

[0127] ;

[0128] ;

[0129] ;

[0130] ;

[0131] in, Minimization represents an optimization process that minimizes the value of an expression. This represents the terrain geometry weight matrix, used to define the covariance structure of the vertical and horizontal deformation components in the weighted least squares objective function. Represents the design matrix. This represents the three-dimensional deformation to be determined. Represents the observation vector. This represents the horizontal deformation weighting factor. Indicates the current pixel in time The curvature of the terrain, This indicates that all pixels within the study area are in time. The minimum absolute value of curvature, This indicates that all pixels within the study area are in time. The maximum value of the absolute value of curvature, This represents the vertical deformation weighting factor.

[0132] S5: Based on the one-dimensional deformation results of the slope along the radar line of sight and the dynamic update results of the time-series terrain parameters, the overdetermined equations of the three-dimensional deformation field are solved to obtain the deformation monitoring results of the open-pit mine slope, thus completing the monitoring of the deformation of the open-pit mine slope.

[0133] The results of open-pit mine slope deformation monitoring are calculated by using dynamic terrain parameters acquired by UAVs as constraints. This allows for the accurate calculation of the vertical (U), east-west (E), and north-south (N) deformation of each pixel, rather than just the fuzzy deformation of the single radar line-of-sight direction provided by traditional InSAR.

[0134] The results of open-pit mine slope deformation monitoring are correlated with changes in topographic parameters such as slope, aspect, and curvature at the same time scale. For example, based on the results, it can be inferred that due to blasting excavation this month, the slope of the area increased from 35° to 45°, and at the same time, the slip rate along the slope aspect (calculated based on the new slope aspect) of the area accelerated from 10 mm per month to 40 mm per month.

[0135] By utilizing open-pit mine slope deformation monitoring results, potential failure surfaces or stress concentration zones on the slope, such as the slope shoulder and toe, can be accurately located. For example, a three-dimensional deformation field clearly shows that the slope toe area mainly exhibits horizontal tensile cracking, while the slope crest area mainly exhibits vertical settlement. This differentiated deformation pattern provides direct evidence for analyzing landslide mechanisms and designing precise reinforcement measures.

[0136] In some embodiments, the processor can solve the overdetermined equations of the three-dimensional deformation field based on the one-dimensional deformation results along the radar line of sight and the dynamic update results of the time-series terrain parameters, to obtain the three-dimensional deformation variables U, E, N of each pixel point of the open-pit mine slope; based on the three-dimensional deformation variables of each pixel point, the slip trend is analyzed to obtain the open-pit mine slope deformation monitoring results, thus completing the monitoring of open-pit mine slope deformation.

[0137] The three-dimensional deformation of each pixel point on the open-pit mine slope includes U, E, and N; among them, the vertical deformation U reflects the slope settlement or uplift, and the horizontal deformation E and N are decomposed into slope-direction and transverse deformations in combination with the slope aspect.

[0138] In some embodiments of this specification, a method for monitoring slope deformation in open-pit mines based on time-series topographic parameters is provided. By integrating high-frequency UAV topographic monitoring with multi-track InSAR technology, a three-dimensional deformation field constrained by the actual geometric shape of the slope is established, solving the problem of insufficient accuracy in LOS-direction deformation monitoring caused by dynamic changes in slope and aspect. First, monthly-scale UAV oblique photogrammetry is used to dynamically acquire topographic parameters such as slope and aspect, ensuring that the topographic model is updated synchronously with mining activities. Second, based on the slope change, aspect angle, and topographic curvature, a priori constraints on the deformation direction are constructed, and an adaptive projection model of InSAR radar LOS-direction deformation and the three-dimensional deformation field of the surface is established. Finally, by fusing the three-dimensional deformation field and dynamic topographic parameters, the three-dimensional deformation of the mine is calculated, effectively improving the reliability, accuracy, and early warning timeliness of open-pit mine slope deformation monitoring, providing precise decision support for safe mining.

Claims

1. A method for monitoring slope deformation in open-pit mines based on time-series topographic parameters, characterized in that, include: S1: Process the rising-orbit synthetic aperture radar satellite imagery and the falling-orbit synthetic aperture radar satellite imagery covering the same slope area of ​​the open-pit mine to obtain the one-dimensional deformation result of the slope along the radar line of sight. S2: Based on high-frequency digital elevation model data covering the same slope area of ​​an open-pit mine, a set of time-series terrain parameters is obtained through calculation; S3: Based on the mining activity cycle, update the time-series terrain parameter set to obtain the dynamic update result of the time-series terrain parameters; S3 includes: S310: Based on engineering data, mining activities are divided into multiple cycles with major disturbance events as nodes, resulting in a set of cycle time nodes; S320: Based on the set of periodic time nodes, calculate the digital elevation model data of adjacent periods to obtain the pixel-level slope change; S330: Normalize the pixel-level slope change to obtain the perturbation weighting factor; S340: Based on the perturbation weighting factor, the time-series terrain parameter set is updated to obtain the dynamic update result of the time-series terrain parameters; S4: Using the one-dimensional deformation results of the slope along the radar line of sight and the dynamic update results of time-series terrain parameters, a projection model of the deformation along the radar line of sight and the adaptive deformation of the ground surface is established to obtain the three-dimensional deformation field under the constraint of the actual geometric shape of the slope; S4 includes: S410: Analyze the relationship between the observed values ​​of deformation in the line-of-sight direction of the ascending radar, the observed values ​​of deformation in the line-of-sight direction of the descending radar, and the three-dimensional deformation to obtain the ascending relationship representation and the descending relationship representation; S420: Based on the dynamic update results of time-series terrain parameters, and using terrain parameter constraints, construct a priori constraints on deformation direction; S430: Substitute the a priori constraints of deformation direction into the ascending orbit relationship and descending orbit relationship respectively, construct an overdetermined set of equations, establish a projection model of radar line-of-sight deformation and surface adaptive deformation, and obtain the three-dimensional deformation field under the constraints of the actual geometric shape of the slope. S5: Based on the one-dimensional deformation results of the slope along the radar line of sight and the dynamic update results of the time-series terrain parameters, the overdetermined equations of the three-dimensional deformation field are solved to obtain the deformation monitoring results of the open-pit mine slope, thus completing the monitoring of the deformation of the open-pit mine slope.

2. The method for monitoring open-pit mine slope deformation based on time-series topographic parameters according to claim 1, characterized in that, S1 includes: S110: Acquire rising-orbit synthetic aperture radar satellite imagery, falling-orbit synthetic aperture radar satellite imagery, and digital elevation model data of the study area covering the same slope area of ​​an open-pit mine. S120: Select one image from N ascending-orbit synthetic aperture radar satellite images as the master image. The images other than the master image are registered with the master image as a reference. According to the set time and space baseline thresholds, the N ascending-orbit synthetic aperture radar satellite images are combined in pairs to generate a total of M differential interferometric pairs. The phase formed after unwrapping the M differential interferometric pairs is calculated to obtain the overall ascending-orbit deformation information. S130: Select one image from N de-orbiting synthetic aperture radar (SAR) satellite images as the master image. Register the other images with reference to the master image. Based on the set time and space baseline thresholds, combine the N ascending SAR satellite images in pairs to generate a total of M differential interferometric pairs. Calculate the phase formed after unwrapping the M differential interferometric pairs using the least squares method and singular value decomposition method to obtain the overall de-orbiting deformation information. S140: Combining satellite orbit data, imaging geometric model, and digital elevation model data, the flat-ground phase and terrain phase in the interferograms of ascending and descending orbit deformation information are removed. Based on the coherence coefficient diagram, phase unwrapping is performed on all interferograms to obtain unwrapped differential interferometric phases without digital elevation model errors. After two model inversions and geocoding using small baseline ensemble aperture radar interferometry, the cumulative deformation results on the complete time series of ascending and descending orbit synthetic aperture radar satellite images are obtained as one-dimensional deformation results.

3. The method for monitoring open-pit mine slope deformation based on time-series topographic parameters according to claim 1, characterized in that, S2 includes: S210: Collect UAV images of the slope area of ​​the open-pit mine at a fixed cycle to obtain UAV image data, ground control point data and UAV position and attitude information data. S220: Preprocess UAV imagery data, ground control point data, and UAV position and attitude information data to obtain high-frequency digital elevation model data; S230: Perform parameter calculations on high-frequency digital elevation model data at fixed intervals to obtain a time-series terrain parameter set.

4. The method for monitoring open-pit mine slope deformation based on time-series topographic parameters according to claim 1, characterized in that, The expression for the perturbation weighting factor is: ； ； in, Indicates the perturbation weighting factor. This represents the change in slope at the pixel level. This indicates taking the absolute value. This represents the function that takes the maximum value. ( () represents the slope calculated from the DEM data acquired at time point t. ( The slope is calculated from the DEM data obtained at time point t-1.

5. The method for monitoring open-pit mine slope deformation based on time-series topographic parameters according to claim 1, characterized in that, The expressions for the ascending and descending orbit relationships are as follows: ； in, This indicates the deformation result of the LOS-axis of the ascending orbit data. This indicates the deformation result of the LOS-axis in the down-orbit data. Indicates the vertical deformation value. The radar incident angle indicating the orbital ascent. The radar incident angle indicating the descent orbit. Indicates the east-west deformation value. Indicates the azimuth angle of the satellite as it ascends to orbit. Indicates the azimuth angle of the satellite in its descending orbit. Indicates the north-south deformation value. This represents the noise term for the ascending track. This represents the noise term for the descending orbit.

6. The method for monitoring open-pit mine slope deformation based on time-series topographic parameters according to claim 1, characterized in that, The a priori constraints on deformation direction include vertical deformation constraints, horizontal deformation constraints, and terrain curvature, wherein the expression for the vertical deformation constraint is: ； The expression for the horizontal deformation constraint is: ； ； ； in, This indicates a vertical deformation constraint. This represents the proportionality coefficient. Indicates changes in slope. Indicates horizontal deformation constraint. Indicates east-west deformation constraints. Indicates north-south deformation constraint. Indicates the slope angle. Indicates the radar incident angle.

7. The method for monitoring open-pit mine slope deformation based on time-series topographic parameters according to claim 1, characterized in that, The objective function of the projection model is expressed as follows: ； ； ； ； in, Minimization represents an optimization process that minimizes the value of an expression. This represents the terrain geometry weight matrix, used to define the covariance structure of the vertical and horizontal deformation components in the weighted least squares objective function. Represents the design matrix. This represents the three-dimensional deformation to be determined. Represents the observation vector. This represents the horizontal deformation weighting factor. Indicates the current pixel in time The curvature of the terrain, This indicates that all pixels within the study area are in time. The minimum absolute value of curvature, This indicates that all pixels within the study area are in time. The maximum value of the absolute value of curvature, This represents the vertical deformation weighting factor.

8. The method for monitoring open-pit mine slope deformation based on time-series topographic parameters according to claim 1, characterized in that, S5 includes: Based on the one-dimensional deformation results of the slope along the radar line of sight and the dynamic update results of the time-series topographic parameters, the overdetermined equations of the three-dimensional deformation field are solved to obtain the three-dimensional deformation variables U, E, N of each pixel point of the open-pit mine slope; among them, the vertical deformation U reflects the slope settlement or uplift, and the horizontal deformation E and N are decomposed into slope-direction and transverse deformation in combination with the slope aspect. Based on the three-dimensional deformation of each pixel, the slip trend is analyzed to obtain the monitoring results of open-pit mine slope deformation, thus completing the monitoring of open-pit mine slope deformation.

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