A method and system for monitoring and early warning of a slope of an open pit mine

Abstract

The present application belongs to the technical field of open-pit mine slope monitoring, and discloses an open-pit mine slope monitoring and early warning method and system. The three-dimensional measured data of the mine area slope are obtained by using the combination technology of vehicle-mounted laser radar and ground-based laser radar; the data of the vehicle-mounted laser radar and the ground-based laser radar are fused and mapped by using the fusion mapping technology, and high-precision three-dimensional radar data are obtained; the three-dimensional displacement of the slope is analyzed based on the multi-period three-dimensional radar data, and the slope crack is explored based on the ground-based radar data; the three-dimensional radar data and the open-pit mine slope data of the slope crack are used to establish an open-pit mine slope stability early warning model, and the whole slope is measured and monitored uninterruptedly for 24 hours. The present application greatly improves the work efficiency, saves manpower, material resources and financial resources, and shortens the unnecessary slope crack size. At the same time, the prevention and control measures proposed in the present application can reduce the probability of safety accidents.

Description

Technical Field

[0001] This invention belongs to the field of open-pit mine slope monitoring technology, and particularly relates to an open-pit mine slope monitoring and early warning method and system. Background Technology

[0002] During the development and mining of various open-pit mines, the mines are frequently affected by various mine disasters. Among these, slope rock mass safety is the most significant factor restricting both mine production efficiency and safety. Slopes, naturally or artificially excavated, are one of the most fundamental geological environments in human engineering activities and a common engineering form in construction. Slope instability and landslides, one of the three major global geological disasters (earthquakes, floods, and landslides / debris flows), are a major disaster frequently encountered in mining operations, posing a serious threat to national property and the lives of miners. Therefore, a correct understanding of slopes, rational design, timely monitoring, and appropriate management to minimize the disasters caused by slope instability are issues that engineering designers and construction personnel must consider. Humans have made many efforts in monitoring and managing slope problems, including understanding landslide mechanisms, improving slope stability analysis theories and methods, developing landslide management and monitoring technologies, and landslide forecasting. Among these, dynamic monitoring and forecasting technologies for slopes are the core content and key technologies in slope stability research, holding an important position in mining engineering and engineering geology.

[0003] Although numerous experts and scholars have analyzed the geological environment and soil properties of slopes, establishing a solid theoretical foundation for understanding the causes and trends of slope changes and instability, the practical application of this theory remains a challenge. Real-time and rapid acquisition of initial slope displacement changes is crucial for predicting slope instability and landslides. For monitoring displacement changes in open-pit mine slopes, traditional methods such as levels and total stations are not only inefficient in terms of real-time performance and manpower, but also pose significant safety risks for surveyors. While GPS monitoring can achieve real-time monitoring, the setup of GPS stations is difficult and costly, and these stations can be destroyed in the event of slope instability or landslides. Therefore, long-distance real-time monitoring is a more practical approach. Currently, photogrammetry is a simple method for non-contact real-time measurement of the object being measured.

[0004] To address the aforementioned requirements, existing technologies have proposed several machine vision-based target monitoring methods. These methods primarily utilize digital or analog cameras employing charge-coupled devices (CCDs) or complementary metal-oxide-semiconductors (CMOS) as photosensitive elements to acquire sequential or video images of the target to be monitored. The acquired images are then transmitted to a computer for computational processing to analyze target changes between images acquired at different times. However, video surveillance typically produces target images with low resolution, hindering accurate target monitoring. Furthermore, without a fast and effective image change monitoring algorithm, it is difficult to simultaneously achieve both real-time monitoring and accuracy.

[0005] Based on the above analysis, the problems and shortcomings of the existing technology are as follows: the existing technology has low work efficiency in slope monitoring, requires a lot of investment in manpower, material resources and financial resources, and cannot effectively reduce the probability of safety accidents.

[0006] Current slope monitoring technology cannot perform 24-hour uninterrupted measurement and monitoring of the entire slope, and cannot understand the dynamic changes of the slope in real time. Summary of the Invention

[0007] To overcome the problems existing in related technologies, the present invention discloses an embodiment of a method and system for monitoring and early warning of open-pit mine slopes.

[0008] The technical solution is as follows: A method for monitoring and early warning of open-pit mine slopes, comprising the following steps:

[0009] S1 uses a combination of vehicle-mounted lidar and ground-based lidar technology to acquire three-dimensional measured data of the slope in the mining area.

[0010] S2 employs fusion mapping technology to fuse and map data from vehicle-mounted and ground-based lidar to obtain high-precision 3D radar data; it analyzes the 3D displacement of the slope based on multi-period 3D radar data and detects slope cracks based on ground-based lidar data.

[0011] S3 utilizes the acquired 3D radar data and open-pit mine slope data with slope cracks to establish an early warning model for the stability of open-pit mine slopes. It conducts 24-hour uninterrupted measurement and monitoring of the entire slope, obtains real-time dynamic changes of the slope, and identifies potential unstable areas of open-pit mine slopes.

[0012] In step S3, the dynamic changes of the slope are acquired in real time, and potential unstable areas of the open-pit mine slope are identified, including:

[0013] S101, obtains the set of dynamic changes in slopes within the region and potential unstable areas of open-pit mine slopes;

[0014] S102, Optimized identification model for constructing an early warning model for slope stability in open-pit mines;

[0015] S103, Construct an optimized identification model for measurement and monitoring equipment;

[0016] S104, the probability of slope stability evolution for early warning at the measurement and monitoring station.

[0017] In step S101, the resulting set expression is:

[0018] O EV ={1,2…M EV} (1)

[0019] O A ={1,2…M A} (2)

[0020]

[0021] In the formula, O EV M represents the set of dynamic change states of slopes within a region that exhibit a tendency for slope cracks to extend. EV The threshold for the dynamic change state of the slope, O A M represents the set of potentially unstable open-pit mine slopes within the region. A This represents the threshold for potentially unstable slope areas in open-pit mines. Let n be the set of unstable region factors within the unstable region of potential open-pit mine slope n. The threshold value for the unstable region factor is the value within the unstable region of the potential open-pit mine slope of number n.

[0022] In step S102, the open-pit mine slope stability early warning model serves as the main body for outputting slope crack stability early warning. Within the same discrete time window, if the slope dynamic change state threshold for outputting slope crack stability early warning is... Less than the threshold of all unstable region factors The early warning model for slope stability in open-pit mines is fully mapped in one round of the algorithm; the expression is:

[0023]

[0024]

[0025] In the formula, u is the threshold value for the dynamic change state of the slope. ev This represents the dynamic changes in the slope. The threshold for all unstable region factors;

[0026] If the slope crack stability early warning threshold is output, the slope dynamic change state threshold is used. Greater than the threshold of all unstable region factors A multi-stage slope dynamic change state and potential open-pit mine slope instability zone mapping method is needed. Based on the preference ranking of instability zone factors for open-pit mine slope stability early warning models, the method first prioritizes models with thresholds equal to... The open-pit mine slope stability early warning model is mapped, the unstable area factors are virtually queued and their status is updated, and then the remaining open-pit mine slope stability early warning models are mapped to the next stage of slope dynamic change status and potential open-pit mine slope unstable area mapping method, until all open-pit mine slope stability early warning models have completed measurement, monitoring and mapping.

[0027] Furthermore, the optimized identification model for constructing the early warning model of open-pit mine slope stability includes:

[0028] (1) Monitoring the dynamic changes of slope and the size of slope cracks;

[0029] (2) Maximum safe crack distance constraint under dynamic slope change state;

[0030] (3) Matching target matrix of open-pit mine slope stability early warning model.

[0031] In step (1), the slope dynamic change state develops to 60% of the warning value, and then the slope cracks are rapidly developed. The target critical function for measuring and monitoring the slope dynamic change state reaching the unstable area of ​​the potential open-pit mine slope is set at 60%. The expression for measuring and monitoring the slope crack size is as follows:

[0032]

[0033]

[0034] In the formula, L ch (u ev ) represents the dynamic change state of the slope. ev unstable slope areas in potential open-pit mines a The required slope crack size for measurement and monitoring, L′ ch (u ev The current dynamic change state of the slope is shown in the condition that it has not developed to the warning value of 60%. ev unstable slope areas in potential open-pit mines a The required slope crack size for measurement and monitoring, E(u) ev ,u a ) represents the dynamic change state of the slope. ev to the unstable area of ​​potential open-pit mine slope ua Safety fracture scale, u ev For the dynamic changing state of the slope, u a For potential unstable slope areas in open-pit mines, ζ(u ev ) represents the dynamic change state of the slope. ev The evolution coefficient per unit distance, Q(u) ev ) represents the dynamic change state of the slope. ev Measure and monitor total distance, O ev O is the set of dynamic changing states of the slope. A For the set of potentially unstable open-pit mine slopes within the region, F0(u ev ) represents the dynamic change state of the slope. ev The critical function at the start, C(U) ev () represents the real-time crack distance of the slope under dynamic changes;

[0035] In step (2), the maximum safe crack distance under dynamic slope change is constrained by the real-time crack distance. When the remaining critical function is insufficient to support the dynamic slope change, the open-pit mine slope stability early warning model will not include potential open-pit mine slope instability regions in its preference sequence. The maximum safe crack distance is obtained by the following formula:

[0036]

[0037]

[0038] In the formula, The dynamic change state of the slope at a certain reference point, u ev Maximum safe distance for cracks, where i is the number of reference points on the open-pit mine slope. The dynamic change state of the slope u ev Maximum safe distance for cracks This represents the distance between the dynamic change state of the slope and the potential unstable area of ​​the open-pit mine slope.

[0039] In step (3), the matching performance of the open-pit mine slope stability early warning model is determined by the slope crack size and measurement and monitoring accuracy. The optimized slope crack size of the open-pit mine slope stability early warning model is quantified using the slope crack size model. The unit slope crack size ρ of the open-pit mine slope stability early warning model is set according to the standard specifications. Therefore, the matching performance target matrix of the open-pit mine slope stability early warning model is as follows:

[0040] min Y EV =(a(u ev )L sum (u ev u a )p+β(uev )X(u ev u a (10)

[0041] stα+β=1,0≤α≤1,0≤β≤1 (11)

[0042] L sum (u ev u a ) = L a (u ev u a )+L f (u ev u a )+L ch (u ev u a (12)

[0043] X(u ev u a )=X′(u ev u a )+E(u ev u a )ζ(u ev )p(u a (13)

[0044] X′(u ev u a ) = (60% - F0(u) ev ))C(u ev )p(u a (14)

[0045] In the formula, minY EV To measure the accuracy of monitoring, 'a' represents the preference weight for slope crack size in the open-pit mine slope stability early warning model, 'β' represents the preference weight for slope crack price in the open-pit mine slope stability early warning model, and 'u' represents the preference weight for slope crack price in the open-pit mine slope stability early warning model. ev For the dynamic changing state of the slope, u a For potentially unstable open-pit mine slopes, a(u ev The stability early warning model for open-pit mine slopes is used in the dynamic change state of the slope. ev Slope crack size preference weight, L sum (u ev u a ) represents the cost of slope crack size in the open-pit mine slope stability early warning model, ρ represents the unit slope crack size, and X(u) represents the cost of slope crack size. ev u a X′(u) represents the distance between the dynamic change state of the slope and the mapped potential unstable area of ​​the open-pit mine slope under the matching of the open-pit mine slope stability early warning model.ev u a L represents the distance between the dynamic change state of the slope and the mapped potential unstable area of ​​the open-pit mine slope under the current open-pit mine slope stability early warning model matching. a (u ev u a ) represents the dynamic change state of the slope. ev Drive towards the unstable area of ​​a potential open-pit mine slope a The size of the crack on the driving slope, L f (u ev u a L represents the size of the cracks in the queuing slope after reaching the measurement and monitoring station. ch (u ev u a X(u) is the measurement and monitoring function for slope crack size, which is filled to the target critical function. ev u a E(u) represents the measurement and monitoring accuracy of the open-pit mine slope stability early warning model under the matching of the open-pit mine slope stability early warning model. ev u a The dynamic change state of the slope is matched with the early warning model for the stability of open-pit mine slopes. ev Maximum safe distance for cracks, ζ(u) ev ) represents the dynamic change state of the slope. ev The evolution coefficient per unit distance, p(u) a ) represents a potentially unstable area on the slope of an open-pit mine. a The range of changes measured and monitored, (u ev F0(u) represents the dynamic change state of the slope. ev ) represents the dynamic change state of the slope. ev The critical function at the start.

[0046] Furthermore, after clarifying the target matrix for the matching of the open-pit mine slope stability early warning model, the cloud-based decision-making platform evaluates and ranks the preference values ​​of the open-pit mine slope stability early warning model for each unstable region factor, defining the preference sequence of the open-pit mine slope stability early warning model for unstable region factors as H. EV H EV The representation is as follows:

[0047]

[0048]

[0049] In the formula, H EV (u ev This is a model for early warning of slope stability in open-pit mines, used to monitor the dynamic changes in slope state. ev The preference sequence of factors in unstable regions. To monitor the dynamic changes in the slope state u ev The measurement and monitoring accuracy values ​​of different unstable area factors in the set of potentially unstable open-pit mine slopes within the region.

[0050] In step S102, the expression for optimizing the recognition model is as follows:

[0051] (1) Accuracy of calculation of unit slope crack size for unstable region factor: The accuracy of calculation of unit slope crack size for each unstable region factor is obtained by the following formula:

[0052]

[0053] In the formula, λ(u n X(u) represents the accuracy of the unstable region factor calculation per unit slope crack size. ev u n L represents the measurement and monitoring accuracy of the early warning model for slope stability in open-pit mines. sum (u ev u n ) represents the slope crack size in the open-pit mine slope stability early warning model, u ev For the dynamic changing state of the slope, u n As an unstable region factor, Let n be the set of unstable region factors within the unstable region of the potential open-pit mine slope;

[0054] (2) Target matrix for matching measurement and monitoring equipment:

[0055] The target matrix for the matching of measurement and monitoring equipment is defined as follows:

[0056] max Y N =λu n (18)

[0057]

[0058] In the formula, max Y N O represents the measurement and monitoring accuracy value under the matching of measurement and monitoring equipment. EV For the potential unstable area of ​​the open-pit mine slope in the dynamic change state of the slope, λ is the unstable area factor coefficient, u n As the unstable region factor, u ev For the dynamic change state of the slope, ψ(u) n u ev ) represents the unstable region factor u n Receive the dynamic change status of the slope u ev The identifier, received using ψ(u) n u ev ) = 1 indicates that ψ(u) is not accepted.n u ev ) = 0 means;

[0059] The cloud-based decision-making platform evaluates and ranks the preference values ​​of unstable region factors for each open-pit mine slope stability early warning model, defining the preference sequence of unstable region factors for open-pit mine slope stability early warning models as Z. n Z n The representation is as follows:

[0060]

[0061]

[0062] In the formula, H N (u N ( ) represents the preference sequence of unstable region factors among unstable region factors in the open-pit mine slope stability early warning model. This represents the slope crack size in the unstable region factor of the open-pit mine slope stability early warning model. For the early warning model matching of open-pit mine slope stability under dynamic slope change state u ev The average maximum safe crack distance constrained by the unstable region factor. u represents the average maximum safe crack distance under factor constraints in unstable regions under the matching of an open-pit mine slope stability early warning model. ev As the unstable region factor, u a For a certain unstable region factor, O EV O is a potential unstable area of ​​open-pit mine slope within the region of dynamic slope change. A This refers to the collection of potentially unstable open-pit mine slopes within the region.

[0063] After ranking the mutual preference values ​​between the open-pit mine slope stability early warning model and the unstable area factors, a one-to-one bilateral mapping between the open-pit mine slope stability early warning model and the unstable area factors is performed using a multi-stage slope dynamic change state and potential open-pit mine slope unstable area mapping method.

[0064] In step S104, the probability of slope stability early warning evolution at the monitoring station is measured by measuring the radiation amplitude of the monitoring station equipment. The expression for the radiation amplitude is:

[0065]

[0066] In the formula, η(i a (i) represents a potentially unstable area on the slope of an open-pit mine. a The radiation amplitude, u ev O represents the dynamic changing state of the slope. EVFor the region of potential unstable open-pit mine slopes in the dynamic change state of slope, ψ(u n u ev ) represents the unstable region factor u n Receive the dynamic change status of the slope u ev The identifier, u n For the unstable region factor, P(u) ev ) represents the dynamic change state of the slope. ev Radiation amplitude, The radiation amplitude coefficient, This represents a factor for a certain unstable region.

[0067] η(i a The closer the value is to 1, the more unstable the potential open-pit mine slope area is to i. a The crack scale has low safety strength; the η(i) between potentially unstable areas of open-pit mine slopes a The smaller the difference, the more balanced the probability of slope stability evolution among the unstable areas of potential open-pit mine slopes.

[0068] Another object of the present invention is to provide an open-pit mine slope monitoring and early warning system, which is used to implement the aforementioned open-pit mine slope monitoring and early warning method. The system includes:

[0069] The three-dimensional measured data acquisition device is used to acquire three-dimensional measured data of the slope of the mining area by combining vehicle-mounted lidar and ground-based lidar technology.

[0070] The 3D radar data and slope crack acquisition module is used to fuse and map data from vehicle-mounted lidar and ground-based lidar using fusion mapping technology to obtain high-precision 3D radar data; it analyzes the 3D displacement of the slope based on multi-period 3D radar data and detects slope cracks based on ground-based lidar data;

[0071] The copper mine slope early warning model establishment module uses acquired 3D radar data and open-pit mine slope crack data to establish an open-pit mine slope stability early warning model. It conducts 24-hour uninterrupted measurement and monitoring of the entire slope, obtains real-time dynamic changes of the slope, and identifies potential unstable areas of the open-pit mine slope.

[0072] Combining all the above technical solutions, the advantages and positive effects of this invention are as follows: This invention utilizes vehicle-mounted radar and ground-based radar fusion mapping technology to analyze the three-dimensional displacement of the slope using the fused data. Based on the three-dimensional displacement of the slope and the distribution of cracks, a monitoring and early warning model for open-pit mine slopes is established. This invention uses vehicle-mounted and ground-based radar equipment to acquire slope radar data from multiple periods, fuses and compares the data to obtain the three-dimensional displacement of the slope. Simultaneously, an early warning model for the stability of open-pit mine slopes is established through slope radar, enabling 24-hour continuous measurement and monitoring of the entire slope, real-time understanding of the dynamic changes of the slope, rapid identification of potentially unstable areas, and achieving the purpose of early warning.

[0073] Based on the geological characteristics of the mine and its surrounding area, and the actual conditions of the mine slopes, this invention analyzes the principles of monitoring open-pit mine slope stability. An early warning model is established using slope radar, providing a feasible basis for assessing slope stability in the mining area. Furthermore, this invention can significantly improve work efficiency in controlling mine slope stability, saving manpower, material resources, and financial resources, and reducing the size of unnecessary slope cracks. Simultaneously, the prevention and control measures proposed in this research can specifically reduce the probability of safety accidents. Through feasibility studies and comparative analysis, the proposed construction method, compared with current general construction methods, will save 20% of construction costs. This will further increase market competitiveness, expand the ability to undertake long-term open-pit copper mine slope stability monitoring, and is expected to increase related design tasks by 15%-25%, while bringing direct economic benefits of 1-2 million yuan to the unit. This invention also completed the collection of copper mine slope model data and related data; completed data analysis and organization; constructed a copper mine slope early warning model; and conducted 24-hour uninterrupted measurement and monitoring of the entire slope to understand its dynamic changes in real time. Attached Figure Description

[0074] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure;

[0075] Figure 1 This is a flowchart of the open-pit mine slope monitoring and early warning method provided in this embodiment of the invention;

[0076] Figure 2 This is a flowchart for identifying potentially unstable areas on open-pit mine slopes provided in an embodiment of the present invention;

[0077] Figure 3 This is a schematic diagram of the open-pit mine slope monitoring and early warning system provided in an embodiment of the present invention;

[0078] In the figure: 1. Three-dimensional measured data acquisition device; 2. Three-dimensional radar data and slope crack acquisition module; 3. Copper mine slope early warning model establishment module. Detailed Implementation

[0079] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Many specific details are set forth in the following description to provide a thorough understanding of the present invention. However, the present invention can be practiced in many other ways different from those described herein, and those skilled in the art can make similar modifications without departing from the spirit of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0080] Example 1, such as Figure 1 As shown, the open-pit mine slope monitoring and early warning method provided in this embodiment of the invention, through analysis of existing data and literature, proposes a method for monitoring the stability of copper mine slopes using radar technology and a method for acquiring slope data in the mining area; specifically, it includes the following steps:

[0081] S1 uses a combination of vehicle-mounted lidar and ground-based lidar technology to acquire three-dimensional measured data of the slope in the mining area.

[0082] S2 employs fusion mapping technology to fuse and map data from vehicle-mounted and ground-based lidar to obtain high-precision 3D radar data; it analyzes the 3D displacement of the slope based on multi-period 3D radar data and detects slope cracks based on ground-based lidar data.

[0083] S3 utilizes the acquired 3D radar data and open-pit mine slope data with slope cracks to establish an early warning model for the stability of open-pit mine slopes. It conducts 24-hour uninterrupted measurement and monitoring of the entire slope, obtains real-time dynamic changes of the slope, and identifies potential unstable areas of open-pit mine slopes.

[0084] In step S3, the entire slope is continuously monitored for 24 hours to obtain real-time dynamic changes and identify potential unstable areas of the open-pit mine slope, including:

[0085] S101, obtain the set of dynamic changes of slopes and potential unstable areas of open-pit mine slopes within the region, as shown in formulas (1)-(3).

[0086] O EV ={1,2…M EV} (1)

[0087] O A ={1,2…M A} (2)

[0088]

[0089] In the formula, O EVM represents the set of dynamic change states of slopes within a region that exhibit a tendency for slope cracks to extend. EV The threshold for the dynamic change state of the slope, O A M represents the set of potentially unstable open-pit mine slopes within the region. A This represents the threshold for potentially unstable slope areas in open-pit mines. Let n be the set of unstable region factors within the unstable region of potential open-pit mine slope n. The threshold value for the unstable region factor is the value within the unstable region of the potential open-pit mine slope of number n.

[0090] The open-pit mine slope stability early warning model, as the main body for outputting slope crack stability early warning, within the same discrete time window, if the slope dynamic change state threshold for outputting slope crack stability early warning... Less than the threshold of all unstable region factors The early warning model for slope stability in open-pit mines is fully mapped in one round of the algorithm; the expression is:

[0091]

[0092]

[0093] If the slope crack stability early warning threshold is output, the slope dynamic change state threshold is used. Greater than the threshold of all unstable region factors A multi-stage slope dynamic change state and potential open-pit mine slope instability zone mapping method is needed. Based on the preference ranking of instability zone factors for open-pit mine slope stability early warning models, the method first prioritizes models with thresholds equal to... The open-pit mine slope stability early warning model is mapped, the unstable area factors are virtually queued and their status is updated, and then the remaining open-pit mine slope stability early warning models are mapped to the next stage of slope dynamic change status and potential open-pit mine slope unstable area mapping method, until all open-pit mine slope stability early warning models have completed measurement, monitoring and mapping.

[0094] The mapping between the dynamic change state of slopes and unstable area factors requires comprehensive consideration of the compatibility between the open-pit mine slope stability early warning model and the measurement and monitoring equipment.

[0095] S102, Constructing an optimized identification model for early warning and identification of open-pit mine slope stability; including:

[0096] 1) Monitoring the dynamic changes in slope conditions and the size of slope cracks;

[0097] The dynamic changes in the slope initially develop at a relatively slow pace, reaching approximately 60% of the warning value, before rapidly developing into cracks. Therefore, the target critical function for measuring and monitoring the dynamic changes in the slope to reach the potential unstable zone of an open-pit mine slope is set at 60%. The size of the cracks in the slope is then calculated using the following formula:

[0098]

[0099]

[0100] In the formula, L ch (u ev ) represents the dynamic change state of the slope. ev unstable slope areas in potential open-pit mines a The required slope crack size for measurement and monitoring, L′ ch (u ev The current dynamic change state of the slope is shown in the condition that it has not developed to the warning value of 60%. ev unstable slope areas in potential open-pit mines a The required slope crack size for measurement and monitoring, E(u) ev u a ) represents the dynamic change state of the slope. ev to the unstable area of ​​potential open-pit mine slope u a Safety fracture scale, u ev For the dynamic changing state of the slope, u a For potentially unstable open-pit mine slopes, ζ(u ev ) represents the dynamic change state of the slope. ev The evolution coefficient per unit distance, Q(u) ev ) represents the dynamic change state of the slope. ev Measure and monitor total distance, O ev O is the set of dynamic changing states of the slope. A For the set of potentially unstable open-pit mine slopes within the region, F0(u ev ) represents the dynamic change state of the slope. ev The critical function at the start, C(u) ev () represents the real-time crack distance of the slope under dynamic changes;

[0101] 2) Maximum safe crack distance constraint under dynamic slope change state;

[0102] The maximum safe crack distance under dynamic slope changes is constrained by the real-time crack distance. When the remaining critical function is insufficient to support the slope's dynamic changes towards more distant potential unstable open-pit mine slopes, these potential unstable open-pit mine slopes will not appear in the preference sequence of the open-pit mine slope stability early warning model. The maximum safe crack distance is derived from the following formula:

[0103]

[0104]

[0105] In the formula, The dynamic change state of the slope at a certain reference point, u ev Maximum safe distance for cracks, where i is the number of reference points on the open-pit mine slope. The dynamic change state of the slope u ev Maximum safe distance for cracks The distance between the dynamic change state of the slope and the mapped potential unstable area of ​​the open-pit mine slope is required to be less than the maximum safe crack distance of the dynamic change state of the slope.

[0106] 3) Matching target matrix of open-pit mine slope stability early warning model;

[0107] The matching performance of the open-pit mine slope stability early warning model is determined by the slope crack size and measurement and monitoring accuracy. The optimal slope crack size for the open-pit mine slope stability early warning model is quantified using a slope crack size model, and the unit slope crack size ρ is set according to standard specifications. Therefore, the matching target matrix for the open-pit mine slope stability early warning model is as follows:

[0108] min Y EV =(a(u ev )L sum (u ev u a )ρ+β(u ev )X(u ev u a (10)

[0109] stα+β=1,0≤α≤1,0≤β≤1 (11)

[0110] L sum (u ev u a ) = L a (u ev u a )+L f(u ev u a )+L ch (u ev u a (12)

[0111] X(u ev u a )=X′(u ev u a )+E(u ev u a )ζ(u ev )p(u a (13)

[0112] X′(u ev u a ) = (60% - F0(u) ev ))C(u ev )p(u a (14)

[0113] In the formula, minY EV To measure the accuracy of monitoring, 'a' represents the preference weight for slope crack size in the open-pit mine slope stability early warning model, 'β' represents the preference weight for slope crack price in the open-pit mine slope stability early warning model, and 'u' represents the preference weight for slope crack price in the open-pit mine slope stability early warning model. ev For the dynamic changing state of the slope, u a For potentially unstable open-pit mine slopes, a(u ev The stability early warning model for open-pit mine slopes is used in the dynamic change state of the slope. ev Slope crack size preference weight, L sum (u ev u a ) represents the cost of slope crack size in the open-pit mine slope stability early warning model, ρ represents the unit slope crack size, and X(u) represents the cost of slope crack size. ev u a X′(u) represents the distance between the dynamic change state of the slope and the mapped potential unstable area of ​​the open-pit mine slope under the matching of the open-pit mine slope stability early warning model. ev u a L represents the distance between the dynamic change state of the slope and the mapped potential unstable area of ​​the open-pit mine slope under the current open-pit mine slope stability early warning model matching. a (u ev u a ) represents the dynamic change state of the slope. ev Drive towards the unstable area of ​​a potential open-pit mine slope a The size of the crack on the driving slope, L f (u ev u aL represents the size of the cracks in the queuing slope after reaching the measurement and monitoring station. ch (u ev u a X(u) is the measurement and monitoring function for slope crack size, which is filled to the target critical function. ev u a E(u) represents the measurement and monitoring accuracy of the open-pit mine slope stability early warning model under the matching of the open-pit mine slope stability early warning model. ev u a The dynamic change state of the slope is matched with the early warning model for the stability of open-pit mine slopes. ev Maximum safe distance for cracks, ζ(u) ev ) represents the dynamic change state of the slope. ev The evolution coefficient per unit distance, p(u) a ) represents a potentially unstable area on the slope of an open-pit mine. a The range of changes in measurement and monitoring, (u ev F0(u) represents the dynamic change state of the slope. ev ) represents the dynamic change state of the slope. ev The critical function at the start.

[0114] After clarifying the target matrix for the matching of the open-pit mine slope stability early warning model, the cloud-based decision-making platform evaluates and ranks the preference values ​​of the open-pit mine slope stability early warning model for each unstable region factor. The preference sequence of the open-pit mine slope stability early warning model for unstable region factors is defined as H. EV H EV The representation is as follows:

[0115]

[0116]

[0117] In the formula, H EV (u ev This is a model for early warning of slope stability in open-pit mines, used to monitor the dynamic changes in slope state. ev The preference sequence of factors in unstable regions. To monitor the dynamic changes in the slope state u ev The measurement and monitoring accuracy values ​​of different unstable area factors in the set of potentially unstable open-pit mine slopes within the region.

[0118] S103, Construct an optimized identification model for measurement and monitoring equipment;

[0119] When selecting an early warning model for open-pit mine slope stability, the measurement and monitoring equipment primarily considers both its own computational accuracy and the balance of slope stability evolution probabilities. To ensure that no severe computational fluctuations occur when large-scale data is collected on slope dynamic changes, it is set that each unstable region factor receives a maximum of one slope dynamic change state per mapping cycle. The model established for the measurement and monitoring equipment is as follows:

[0120] 1) Accuracy of calculating unit slope crack size for unstable region factor:

[0121] The accuracy of measurement and monitoring equipment primarily stems from the measurement and monitoring accuracy of the open-pit mine slope stability early warning model. Potentially unstable open-pit mine slopes tend to receive measurements of larger and faster-evolving slope cracks, thus improving the accuracy of calculations per unit slope crack size. The accuracy of calculations per unit slope crack size for each unstable region factor is derived from the following formula:

[0122]

[0123] In the formula, λ(u n X(u) represents the accuracy of the unstable region factor calculation per unit slope crack size. ev ,u n L represents the measurement and monitoring accuracy of the early warning model for slope stability in open-pit mines. sum (u ev ,u n ) represents the cost of slope crack size in an open-pit mine slope stability early warning model, u ev For the dynamic changing state of the slope, u n As an unstable region factor, Let n be the set of unstable region factors within the unstable region of the potential open-pit mine slope;

[0124] 2) Measurement and monitoring equipment matching target matrix: The measurement and monitoring equipment matching target matrix is ​​defined as follows:

[0125] max Y N =λu n (18

[0126]

[0127] In the formula, max Y N O represents the measurement and monitoring accuracy value under the matching of measurement and monitoring equipment. EV For the potential unstable area of ​​the open-pit mine slope in the dynamic change state of the slope, λ is the unstable area factor coefficient, u n As the unstable region factor, u ev For the dynamic change state of the slope, ψ(u) n ,uev ) represents the unstable region factor u n Receive the dynamic change status of the slope u ev The identifier, received by ψ(u) n ,u ev ) = 1 indicates that ψ(u) is not accepted. n ,u ev ) = 0 indicates that

[0128] The cloud-based decision-making platform evaluates and ranks the preference values ​​of unstable region factors for each open-pit mine slope stability early warning model, defining the preference sequence of unstable region factors for open-pit mine slope stability early warning models as Z. n Z n The representation is as follows:

[0129]

[0130]

[0131] In the formula, H N (u N ( ) represents the preference sequence of unstable region factors among unstable region factors in the open-pit mine slope stability early warning model. This represents the slope crack size in the unstable region factor of the open-pit mine slope stability early warning model. For the early warning model matching of open-pit mine slope stability under dynamic slope change state u ev The average maximum safe crack distance constrained by the unstable region factor. u represents the average maximum safe crack distance under factor constraints in unstable regions under the matching of an open-pit mine slope stability early warning model. ev As the unstable region factor, u a For a certain unstable region factor, O EV O is a potential unstable area of ​​open-pit mine slope within the region of dynamic slope change. A This refers to the collection of potentially unstable open-pit mine slopes within the region.

[0132] After ranking the mutual preference values ​​between the open-pit mine slope stability early warning model and the unstable area factors, a one-to-one bilateral mapping between the open-pit mine slope stability early warning model and the unstable area factors is performed using a multi-stage slope dynamic change state and potential open-pit mine slope unstable area mapping method.

[0133] S104, probability of slope stability evolution at the monitoring station;

[0134] The probability of slope stability early warning evolution at the monitoring station is measured by measuring the radiation amplitude of the monitoring station equipment. The radiation amplitude is shown in equation (22).

[0135]

[0136] In the formula, η(i a (i) represents a potentially unstable area on the slope of an open-pit mine. a The radiation amplitude, u ev O represents the dynamic changing state of the slope. EV For the region of potential unstable open-pit mine slopes in the dynamic change state of slope, ψ(u n u ev ) represents the unstable region factor u n Receive the dynamic change status of the slope u ev The identifier, u n For the unstable region factor, P(u) ev ) represents the dynamic change state of the slope. ev Radiation amplitude, The radiation amplitude coefficient, This represents a factor for a certain unstable region.

[0137] η(i a The closer the value is to 1, the more unstable the potential open-pit mine slope area is to i. a The crack scale has low safety strength; the η(i) between potentially unstable areas of open-pit mine slopes a The smaller the difference, the more balanced the probability of slope stability evolution among the unstable areas of potential open-pit mine slopes.

[0138] The strategy proposed in this invention simultaneously satisfies the compatibility between the early warning model for slope stability in open-pit mines and the measurement and monitoring equipment.

[0139] Example 2, as another embodiment of the present invention, in step S2, an exemplary commonly used fusion mapping technique is provided, including:

[0140] The first step involves using multiple complementary features, based on different extraction methods, to heterogeneously characterize open-pit mine slope detection images from different detection angles;

[0141] The second step is to delve into the cross-dimensional displacement semantics between different features based on the cross-dimensional semantic analysis model, and achieve initial feature fusion.

[0142] The third step is to dynamically calculate the three-dimensional displacement weights of the features, complete the feature fusion and optimize the feature combination to achieve feature fusion, and finally realize multi-stage and multi-feature deep fusion.

[0143] Preferably, in the first step, the following steps are required: Based on the complementarity between heterogeneous features, extract a set of excellent features of the image from multiple perspectives such as shape, texture, and deep learning, including Gist, SIFT, HOG, VGG16, LBP, DenseNet, and ResNet.

[0144] In the second step, the cross-dimensional semantics include: the cross-dimensional semantics are that different features all point to the same or similar displacement semantics, which are represented by SG, SV, SR, GH, GV, GR and SD respectively, for a total of 21 sets of cross-dimensional displacement semantics;

[0145] In the third step, the post-fusion implementation method specifically includes: using a hybrid soft and hard voting mechanism to vote on the feature combinations generated by the intermediate fusion, thereby achieving feature post-fusion;

[0146] The post-feature fusion implementation method specifically includes: performing SUM fusion, making decisions based on Max, designing two strategies, random or sorted, selecting the n' feature combinations from the top n groups of 3D displacement feature combinations with the best accuracy, n=11, n'=3,5,7,9,11, performing soft and hard voting decisions on the prediction results, and integrating and learning different feature discrimination results to achieve post-feature fusion.

[0147] The aforementioned feature fusion implementation method specifically includes: dynamically calculating feature weights based on an improved three-dimensional displacement model to achieve feature fusion;

[0148] The feature fusion implementation method specifically includes: calculating the estimated probability of single feature and cross-dimensional displacement semantics based on the Adaboost algorithm; improving the effective region gene selection algorithm, dynamically calculating the three-dimensional displacement weight of single feature and cross-dimensional displacement semantics, using the three-dimensional displacement weight to weight the estimated probability, constructing feature combination, and using the improved three-dimensional displacement model to achieve fusion of multiple features;

[0149] In the soft and hard voting decision-making process for the prediction results, the decision may adopt a stacked boosting fusion algorithm or a weighted fusion strategy.

[0150] After the third step, the following step is required: Step four, use the constructed DE-Ada* model that integrates initial fusion, intermediate fusion and post-fusion to identify open-pit mine slope detection images, and output predicted labels for open-pit mine slope detection images based on the identification results.

[0151] In another embodiment of the present invention, step S2, slope crack detection based on data, includes:

[0152] Step 1: Obtaining open-pit mine slope characteristic information. Based on the internal center information, geological analysis information, and slope detection curve information of the multi-stage layer of the open-pit mine slope to be analyzed, determine the open-pit mine slope characteristic information of the multi-stage layer of the open-pit mine slope to be analyzed.

[0153] Step 2, Determining the crack degree curve: Based on the characteristic information of the multi-stage layer of the open-pit mine slope to be analyzed, various crack degree curves of the multi-stage layer of the open-pit mine slope to be analyzed are calculated according to the preset crack degree curve model; the crack degree curve includes crack degree and correction curve calculated by radar wave time difference and compensation density.

[0154] Step 3: Determine the combination of crack degree curves. In the dry layer of the multi-stage layer of the open-pit mine slope to be analyzed, the various crack degree curves calculated in Step 2 are overlapped and placed in the same predicted crack degree curve channel as the combination of crack degree curves of the multi-stage layer of the open-pit mine slope to be analyzed.

[0155] Step 4: Crack type identification. In other sections of the multi-stage layer of the open-pit mine slope to be analyzed, compare the various crack degree curves in the crack degree curve combination, and determine the crack type of the corresponding section based on the comparison results and the preset crack model.

[0156] Step 5: Determine the crack type of the corresponding layer in Step 4 based on the preset crack model. Combine the collected images of different stages of the slope and the stress data of different stages of the slope, and calculate the coherence volume after superimposing and offset according to the azimuth range to obtain multiple central angle coherence data volumes.

[0157] Step 6: Reconstruct the coherent attribute data of each sampling point of each CDP point on each central corner coherent data volume to obtain the minimum coherent dataset of each sampling point, and then obtain the minimum coherent data volume.

[0158] Step 7: Calculate the crack azimuth using the minimum coherence data volume to obtain the crack azimuth data value of each sampling point, thereby obtaining the crack azimuth data volume; determine the crack development status based on the minimum coherence data volume and the crack azimuth data volume.

[0159] Step 8: In different stages of the slope, based on geological conditions and research objectives, select slopes that have representative significance in terms of crack azimuth data obtained in Step 7 and crack development status, and conduct coring operations and geostress tests on multi-stage sections of the open-pit mine slope.

[0160] Step 9: Conduct ground-based radar scanning observation of the center of the slope interior to identify the crack development section, and describe and record the crack development and orientation.

[0161] Step 10: Conduct triaxial stress strain tests at different stages of the slope's interior center to obtain stress-strain curves;

[0162] Step 11 involves conducting resistivity slope detection, radar wave slope detection, spontaneous potential slope detection, natural gamma slope detection, compensated neutron slope detection, density slope detection, and slope diameter slope detection. Combined with the stress-strain curve described in Step 10, the slope detection curve of the entire target slope segment is obtained. Using the cored segment curve that confirms crack development as a reference, the slope detection interpretation identifies more crack-developed slope segments.

[0163] Step 12: Perform micro-resistivity scanning imaging slope detection on the crack-developed slope sections identified in Step 11.

[0164] Step 13: Based on the slope detection data obtained in Step 12, establish a single slope profile model to comprehensively evaluate the development of multi-stage layer cracks in the open-pit mine slope.

[0165] Preferably, the method for determining the combination of crack intensity curves in step 3 includes:

[0166] Using the crack intensity correction curve of the multi-stage layer of the open-pit mine slope to be analyzed as a reference, with the depth coordinate remaining unchanged, the radar wave transit time crack intensity curve and density crack intensity curve of the multi-stage layer of the open-pit mine slope to be analyzed are translated in the crack intensity coordinate direction, so that the density crack intensity curve and radar wave transit time crack intensity curve of the multi-stage layer of the open-pit mine slope to be analyzed coincide with the crack intensity correction curve of the multi-stage layer of the open-pit mine slope to be analyzed within the same predicted crack intensity curve channel.

[0167] Preferably, step 4, crack type identification, also includes:

[0168] The depth of the internal center of the multi-stage layer of the open-pit mine slope to be analyzed is determined, and it is determined whether the crack type of each segment of the internal center of the slope after depth determination maps to the crack type of the corresponding segment identified in the crack identification step; and / or, the crack type of each segment of the multi-stage layer of the open-pit mine slope to be analyzed is identified using imaging slope detection, and it is determined whether the crack type of each segment identified by imaging slope detection maps to the crack type of the corresponding segment identified in the crack identification step.

[0169] In the preset crack degree curve model, based on the open-pit mine slope characteristic information of the multi-stage layer of the open-pit mine slope to be analyzed, the radar wave time difference and the skeleton density of the slope at different stages of the multi-stage layer of the open-pit mine slope to be analyzed are determined.

[0170] Based on the acquired images of different stages of the slope and the stress data of different stages of the slope, and based on the radar wave transit time and density of the skeleton of different stages of the slope, the radar wave transit time curve and the compensation density of the multi-stage layer of the open-pit mine slope to be analyzed are used to calculate the radar wave crack intensity curve and density crack intensity curve of the multi-stage layer of the open-pit mine slope to be analyzed according to the radar wave crack intensity response model and the density crack intensity response model, respectively.

[0171] The method for generating the central angle coherence data volume in step 5 includes:

[0172] The acquired gather data is divided into corresponding azimuth ranges using preset azimuth division parameters to obtain multiple corresponding central angle gather data.

[0173] The data from each central corner gather are stacked and offset separately to obtain the corresponding central corner stacked data volume; coherence volume calculation is performed on each central corner stacked data volume to obtain the corresponding central corner coherence data volume.

[0174] Step 6, the method for generating the minimum coherent data volume includes:

[0175] A coherent attribute dataset is established using the multiple central angle coherent data volumes and the sampling points corresponding to the slope data;

[0176] The minimum coherence value is selected from the coherence attribute dataset of each sampling point as the coherence attribute value of that sampling point, thus obtaining the minimum coherence dataset of each sampling point;

[0177] The minimum coherence datasets of each sampling point are integrated to obtain the minimum coherence data volume.

[0178] As another embodiment of the present invention, exemplary, the establishment of the copper mine slope early warning model in step S3 includes:

[0179] (1) Identification of displacement and crack system movement velocity: The grid data of displacement and crack identification are subjected to regional dilation processing, and individual displacement and cracks are identified by clustering. Finally, the movement velocity of each individual displacement and crack is calculated by weighted statistics.

[0180] (2) Identification of potential unstable areas of open-pit mine slopes: Based on the unstable information of ground open-pit mine slopes observed by automatic stations, establish a potential unstable area identification model for open-pit mine slopes and an inversion model of open-pit mine slope instability parameters; then apply the potential unstable area identification model for open-pit mine slopes to the real-time open-pit mine slope instability early warning service.

[0181] In an embodiment of the present invention, for example, step (1) of identifying the displacement and the movement speed of the crack system specifically includes:

[0182] The grid data for displacement and crack identification were subjected to 3×3 region dilation, and individual displacement and crack units were identified using clustering. For all grid locations within each displacement and crack unit region, the displacement or crack vector V was inverted using the corresponding CLTREC method. g The movement velocity V of each displacement and crack unit is finally calculated through weighted statistics. s :

[0183]

[0184] Where i represents the i-th grid point within the range of strong displacement and crack individual, and there are N grid points within the range of displacement and crack individual, with the weighting coefficient selected as the grid point echo intensity R;

[0185] Step (2), the identification of potential unstable areas on open-pit mine slopes, specifically includes:

[0186] 1) Based on the grid data of radial open-pit mine slopes with equal elevation angles (Vel) ppi Identify the maximum radial displacement or crack velocity in the vertical direction at each grid point location (X, Y):

[0187] Vel max (x, y) = MAX(Vel ppi (e, x, y)), e ≤ E max

[0188] Where e represents the total E max Based on the e-th elevation angle layer, the variation region V is identified. g ≥12m / s, mark grid points in all variation regions;

[0189] 2) After identifying potential variation areas, normal and abnormal areas are identified based on the polarization characteristics of dual-polarization radar;

[0190] 3) Combine historical cases, and construct a correlation model between the instability information and polarization of open-pit mine slopes observed by automatic stations, based on the default length of the past quarter or the length of the same quarter in history. This inversion model uses polarization as the characterization factor for the estimation of open-pit mine slope instability, and verifies the authenticity of the inversion results by using the instability of open-pit mine slopes observed by automatic stations.

[0191] 4) Synthesis of potential unstable areas on open-pit mine slopes through multi-element integration;

[0192] The discrimination method used in step (2) to identify normal and abnormal regions includes:

[0193] For grid points marked as displacement and crack regions, a grid point is determined to be affected by displacement or cracks if it satisfies the following formula, i.e., the echo top height (ETOP). 18dBZ That is, the maximum height of the echo >18dBZ is higher than the height H of the -20℃ location. -20° The correlation coefficient ρ is at least 1km, and the grid point location corresponds to a certain elevation angle layer. HV The value is less than 0.95 and the echo intensity Z is greater than 45 dBZ; at the same time, the height information of each displacement or crack appearing in the vertical direction of this grid point is recorded;

[0194] ETOP 18dBZ >(H -20° +1.0)∩ρ HV <0.95∩Z>45

[0195] Continue to utilize differential reflectivity Z dr and differential phase shift rate K dp To distinguish between abnormal and normal regions, the following formula condition must be met: Differential reflectance Z dr Approaching 0 and the differential phase shift rate K dp If the value is low, it is considered a normal zone; otherwise, it is considered an abnormal zone.

[0196] Z dr <0.5∩K dp <0.5

[0197] Step 3) defines the true observation standard for instability of open-pit mine slopes as follows:

[0198] (a) Construct a statistical model of the height distribution probability of the abnormal and normal areas of the open-pit mine slope instability: Based on the displacement or crack vector field inverted by 3km, according to the semi-Lagrange method, i.e. formula (5), backward particle tracking is performed at a step size of 1 minute to find the movement trajectory of the grid points in the large displacement or crack area in the past hour; Formula (6) is used to statistically analyze the reference height layer frequency of the abnormal and normal areas suitable for the instability of the open-pit mine slope in the past hour; Generate the height distribution probability statistical results of the instability of the open-pit mine slope corresponding to the abnormal and normal areas, and select the height corresponding to the height probability close to 50% probability as the filtering threshold based on the Gaussian probability model assumption;

[0199]

[0200] The above formula indicates that the tracking position in the past t minute is the position in the past t-1 minute minus the displacement or crack vector corresponding to the position in the past t-1 minute, in km / min. Using the above formula, the movement trajectory of the grid point that caused the instability of the open-pit mine slope was tracked for 60 minutes in the past hour.

[0201] Hstandar =LROUND((H hail -H 2km ) / (H -20° -H 2km )*10)

[0202] Calculate the reference height layer based on the above formula, and statistically analyze H. 2km To H -20° The height range, i.e., the number of times displacement or cracks occur at different heights within the temperature layer height of 2km to -20°C; LROUND represents the rounding function.

[0203] (b) Constructing an open-pit mine slope instability strength model by inverting the polarization quantity in the abnormal and normal zones: After obtaining the movement trajectory of the large displacement or crack grid points over the past hour, an open-pit mine slope instability strength model is constructed for the abnormal and normal zones. For the grid points in the abnormal zone, based on the statistical model of the height distribution probability of the abnormal and normal zones prone to open-pit mine slope instability, the differential phase shift rate K of all displacement or crack characteristics in the vertical direction corresponding to the displacement or crack grid points over the past hour is selected. dp The maximum value, combined with the instability strength values ​​of the open-pit mine slope from the automatic weather station, is used to construct a second-order fitting statistical model using partial least squares. For grid points in the normal area: similarly, based on the statistical model of the probability distribution of height in the abnormal and normal areas of the prone open-pit mine slope instability, the displacement or crack grid points in the past hour are selected, and the maximum value of the characteristic echo intensity Z of all displacements or cracks in the corresponding vertical direction is collected. This value, along with the instability strength values ​​of the open-pit mine slope from the automatic weather station, is used to construct a second-order fitting statistical model using partial least squares.

[0204] Example 3, as Figure 3 As shown, the open-pit mine slope monitoring and early warning system provided in this embodiment of the invention includes:

[0205] The three-dimensional measured data acquisition device 1 is used to acquire three-dimensional measured data of the slope of the mining area by combining vehicle-mounted lidar and ground-based lidar technology.

[0206] The 3D radar data and slope crack acquisition module 2 is used to fuse and map data from both vehicle-mounted and ground-based lidar using fusion mapping technology to obtain high-precision 3D radar data; it analyzes the 3D displacement of the slope based on multi-period 3D radar data, and simultaneously detects slope cracks based on ground-based lidar data.

[0207] The copper mine slope early warning model establishment module 3 is used to establish an open-pit mine slope stability early warning model based on the acquired three-dimensional radar data and open-pit mine slope crack data according to the site conditions. It can conduct 24-hour uninterrupted measurement and monitoring of the entire slope, understand the dynamic changes of the slope in real time, and identify potential unstable areas of the open-pit mine slope.

[0208] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0209] The information interaction and execution process between the above-mentioned devices / units are based on the same concept as the method embodiments of the present invention. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.

[0210] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this invention. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments.

[0211] This invention also provides a computer device comprising: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, wherein the processor executes the computer program to implement the steps in any of the above method embodiments.

[0212] This invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, can implement the steps described in the various method embodiments above.

[0213] This invention also provides an information data processing terminal, which, when executed on an electronic device, provides an input interface for an open-pit mine slope stability early warning model to implement the steps described in the above method embodiments. The information data processing terminal is not limited to mobile phones, computers, or switches.

[0214] This invention also provides a server, which, when executed on an electronic device, provides an input interface for an early warning model of open-pit mine slope stability to implement the steps described in the above method embodiments.

[0215] This invention provides a computer program product that, when run on an electronic device, enables the electronic device to implement the steps described in the various method embodiments above.

[0216] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying the computer program code to a photographic device / terminal device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0217] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications, equivalent substitutions, and improvements made by those skilled in the art within the scope of the technology disclosed in the present invention, and within the spirit and principles of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A method for monitoring and early warning of open-pit mine slopes, characterized in that, The method includes the following steps: S1 uses a combination of vehicle-mounted lidar and ground-based lidar technology to acquire three-dimensional measured data of the slope in the mining area. S2 employs fusion mapping technology to fuse and map data from vehicle-mounted and ground-based lidar to obtain high-precision 3D radar data; it analyzes the 3D displacement of the slope based on multi-period 3D radar data and detects slope cracks based on ground-based lidar data. S3. Using the acquired three-dimensional radar data and open-pit mine slope data with slope cracks, an early warning model for the stability of open-pit mine slopes is established. The entire slope is continuously measured and monitored 24 hours a day to obtain the dynamic changes of the slope in real time and identify potential unstable areas of open-pit mine slopes. In step S3, the dynamic changes of the slope are acquired in real time, and potential unstable areas of the open-pit mine slope are identified, including: S101, obtains the set of dynamic changes in slopes within the region and potential unstable areas of open-pit mine slopes; S102, Optimized identification model for constructing an early warning model for slope stability in open-pit mines; S103, Construct an optimized identification model for measurement and monitoring equipment; S104, Probability of slope stability evolution at the monitoring station; In step S101, the resulting set expression is: ； ； ； In the formula, This is a set of dynamic change states of slopes within a region that show a tendency for slope cracks to extend. This represents the threshold for the dynamic change state of the slope. This refers to a collection of potentially unstable open-pit mine slope areas within the region. This represents the threshold for potentially unstable slope areas in open-pit mines. for Set of unstable region factors within the unstable area of ​​a potential open-pit mine slope. for Threshold for unstable region factor within the unstable area of ​​potential open-pit mine slope; In step S102, the open-pit mine slope stability early warning model serves as the main body for outputting slope crack stability early warning. Within the same discrete time window, if the slope dynamic change state threshold for outputting slope crack stability early warning is... Less than the threshold of all unstable region factors The open-pit mine slope stability early warning model is fully mapped in one round of algorithm; the expression is: ； ； In the formula, This represents the threshold value for the dynamic change state of the slope. This represents the dynamic changes in the slope. The threshold for all unstable region factors; If the slope crack stability early warning threshold is output, the slope dynamic change state threshold is used. Greater than the threshold of all unstable region factors This requires a multi-stage slope dynamic change state and a mapping method for potential unstable areas of open-pit mine slopes. Based on the preference ranking of unstable area factors for open-pit mine slope stability early warning models, the first step is to prioritize models with a threshold equal to... The open-pit mine slope stability early warning model is mapped, the unstable area factors are virtually queued and their status is updated, and then the remaining open-pit mine slope stability early warning models are mapped to the next stage of slope dynamic change status and potential open-pit mine slope unstable area mapping method, until all open-pit mine slope stability early warning models have completed measurement, monitoring and mapping.

2. The open-pit mine slope monitoring and early warning method according to claim 1, characterized in that, The optimized identification model for constructing an early warning model for open-pit mine slope stability includes: (1) Monitoring the dynamic changes of slope and the size of slope cracks; (2) Maximum safe crack distance constraint under dynamic slope change state; (3) Matching target matrix of open-pit mine slope stability early warning model.

3. The open-pit mine slope monitoring and early warning method according to claim 2, characterized in that, In step (1), the slope dynamic change state develops to 60% of the warning value, and then the slope cracks are rapidly developed. The target critical function for measuring and monitoring the slope dynamic change state reaching the unstable area of ​​the potential open-pit mine slope is set at 60%. The expression for measuring and monitoring the slope crack size is: ； ； In the formula, The dynamic change state of the slope Unstable slope areas of potential open-pit mines Measuring and monitoring the required slope crack dimensions. The current dynamic change state of the slope under the condition that it has not developed to 60% of the warning value. Unstable slope areas of potential open-pit mines The required dimensions of slope cracks for measurement and monitoring. The dynamic change state of the slope To the unstable area of ​​potential open-pit mine slope Safe fracture scale. This represents the dynamic changes in the slope. This area is a potential site of unstable open-pit mine slopes. The dynamic change state of the slope The evolution coefficient per unit distance, The dynamic change state of the slope Measure and monitor the total distance. This is a set of dynamic changing states of the slope. This refers to a collection of potentially unstable open-pit mine slope areas within the region. The dynamic change state of the slope The critical function at the start, Real-time crack distance representing the dynamic changes in the slope; In step (2), the maximum safe crack distance under dynamic slope change is constrained by the real-time crack distance. When the remaining critical function is insufficient to support the dynamic slope change, the open-pit mine slope stability early warning model will not include potential open-pit mine slope instability regions in its preference sequence. The maximum safe crack distance is obtained by the following formula: ； ； In the formula, The dynamic change state of the slope at a certain reference point Maximum safe distance for cracks The number of reference points for open-pit mine slopes. The dynamic change state of the slope Maximum safe distance for cracks This represents the distance between the dynamic change state of the slope and the potential unstable area of ​​the open-pit mine slope. In step (3), the matching of the open-pit mine slope stability early warning model is composed of the slope crack size and the measurement and monitoring accuracy. The slope crack size model is used to quantify the optimized slope crack size of the open-pit mine slope stability early warning model, and the unit slope crack size of the open-pit mine slope stability early warning model is set according to the standard specifications. Therefore, the matching objective matrix of the open-pit mine slope stability early warning model is as follows: ； ； ； ； ； In the formula, To measure the accuracy of monitoring values, The preferred weights for slope crack size in the open-pit mine slope stability early warning model are used. The price preference weights for slope cracks in the open-pit mine slope stability early warning model are used. This represents the dynamic changes in the slope. This area is a potential site of unstable slopes in open-pit mines. For open-pit mine slope stability early warning model under dynamic slope change state Slope crack size preference weights Cost of slope crack size for open-pit mine slope stability early warning model. The unit slope crack size To match the dynamic change state of the slope with the distance between the mapped potential unstable area of ​​the open-pit mine slope in the early warning model for slope stability, the following method is used. To match the dynamic change state of the slope with the distance between the mapped potential unstable area of ​​the open-pit mine slope under the current open-pit mine slope stability early warning model. The dynamic change state of the slope Drive towards the unstable area of ​​a potential open-pit mine slope The size of the cracks on the driving slope. The dimensions of the slope cracks after reaching the measurement and monitoring station. To measure and monitor the slope crack size to reach the target critical function, To improve the measurement and monitoring accuracy of the open-pit mine slope stability early warning model under the matching of the open-pit mine slope stability early warning model. Matching the dynamic changes of the slope to the early warning model for slope stability in open-pit mines Maximum safe distance for cracks The dynamic state of the slope The evolution coefficient per unit distance, Unstable slopes in potential open-pit mines The range of changes measured and monitored. This represents the dynamic changes in the slope. The dynamic change state of the slope The critical function at the start.

4. The open-pit mine slope monitoring and early warning method according to claim 2, characterized in that, After defining the target matrix for the matching of the open-pit mine slope stability early warning model, the cloud-based decision-making platform evaluates and ranks the preference values ​​of the open-pit mine slope stability early warning model for each unstable region factor, defining the preference sequence of the open-pit mine slope stability early warning model for unstable region factors as follows: , The representation is as follows: ； ； In the formula, For the early warning model of slope stability in open-pit mines, the dynamic changes of slope status are monitored. The preference sequence of factors in unstable regions. To monitor the dynamic changes in the slope The measurement and monitoring accuracy values ​​of different unstable area factors in the set of potentially unstable open-pit mine slopes within the region.

5. The open-pit mine slope monitoring and early warning method according to claim 1, characterized in that, In step S102, the expression for optimizing the recognition model is as follows: (1) Accuracy of calculation of unit slope crack size for unstable region factor: The accuracy of calculation of unit slope crack size for each unstable region factor is obtained by the following formula: ； In the formula, To determine the accuracy of the unit slope crack size calculation for the unstable region factor. To improve the measurement and monitoring accuracy of the early warning model for slope stability in open-pit mines. This refers to the slope crack size in the open-pit mine slope stability early warning model. This represents the dynamic changes in the slope. As an unstable region factor, for Set of unstable region factors within the unstable area of ​​potential open-pit mine slope; (2) Target matrix for matching measurement and monitoring equipment: The target matrix for the matching of measurement and monitoring equipment is defined as follows: ； ； In the formula, This refers to the measurement and monitoring accuracy value under the matching of measurement and monitoring equipment. This refers to the potentially unstable open-pit mine slope area within the region of dynamic slope change. For unstable region factor coefficients, As an unstable region factor, This represents the dynamic changes in the slope. Unstable region factor Receive the dynamic changes of the slope The identifier, for receiving This indicates that we do not accept [the product / service]. express; The cloud-based decision-making platform evaluates and ranks the preference values ​​of unstable region factors for each open-pit mine slope stability early warning model, defining the preference sequence of unstable region factors for open-pit mine slope stability early warning models as follows: , The representation is as follows: ； ； In the formula, This is the preference sequence of unstable region factors among the unstable region factors in the open-pit mine slope stability early warning model. This represents the slope crack size in the unstable region factor of the open-pit mine slope stability early warning model. Matching the early warning model for slope stability in open-pit mines under dynamic slope change conditions The average maximum safe crack distance constrained by the unstable region factor. This represents the average maximum safe distance of cracks under factor constraints in unstable regions, provided the early warning model for slope stability in open-pit mines is matched. As an unstable region factor, For a certain unstable region factor, This refers to the potentially unstable open-pit mine slope area within the region of dynamic slope change. This refers to the collection of potentially unstable open-pit mine slopes within the region. After ranking the mutual preference values ​​between the open-pit mine slope stability early warning model and the unstable area factors, a one-to-one bilateral mapping between the open-pit mine slope stability early warning model and the unstable area factors is performed using a multi-stage slope dynamic change state and potential open-pit mine slope unstable area mapping method.

6. The open-pit mine slope monitoring and early warning method according to claim 1, characterized in that, In step S104, the probability of slope stability early warning evolution at the monitoring station is measured by measuring the radiation amplitude of the monitoring station equipment. The expression for the radiation amplitude is: ； In the formula, Unstable slopes in potential open-pit mines The radiation amplitude, This represents the dynamic changes in the slope. This refers to the potentially unstable open-pit mine slope area within the region of dynamic slope change. Unstable region factor Receive the dynamic changes of the slope The logo, As an unstable region factor, The dynamic state of the slope Radiation amplitude, The radiation amplitude coefficient, This represents a factor for a certain unstable region. The closer a value is to 1, the more likely it is to indicate an unstable area on the slope of a potential open-pit mine. The crack size has low safety strength; the potential unstable areas between open-pit mine slopes The smaller the difference, the more balanced the probability of slope stability early warning evolution among the unstable areas of potential open-pit mine slopes.

7. An open-pit mine slope monitoring and early warning system, characterized in that, This system is used to implement the open-pit mine slope monitoring and early warning method according to any one of claims 1-6, and the system includes: The three-dimensional measured data acquisition device (1) is used to acquire three-dimensional measured data of the slope of the mining area by combining vehicle-mounted lidar and ground-based lidar technology. The three-dimensional radar data and slope crack acquisition module (2) is used to perform fusion mapping on the data of vehicle-mounted lidar and ground-based lidar using fusion mapping technology to obtain high-precision three-dimensional radar data; analyze the three-dimensional displacement of the slope based on multi-period three-dimensional radar data, and conduct slope crack detection based on ground-based radar data; The copper mine slope early warning model establishment module (3) uses the acquired three-dimensional radar data and open-pit mine slope data with slope cracks to establish an open-pit mine slope stability early warning model, conduct 24-hour uninterrupted measurement and monitoring of the entire slope, obtain the dynamic changes of the slope in real time, and identify potential unstable areas of open-pit mine slopes.

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