An intelligent control method and system for ecological restoration of a strip mining damaged area

Abstract

The application relates to the technical field of mining damage area repair, in particular to an open-pit mining damage area ecological repair intelligent regulation and control method and system. The method comprises the following steps: establishing an ecological planning model and a damage area monitoring network; collecting environmental characteristic parameters of the damage area based on the monitoring network, and setting a plurality of to-be-repaired sub-areas according to the environmental characteristic parameters; the ecological planning model sets a repair execution sequence according to all the to-be-repaired sub-areas, and sets an expected repair strategy of each to-be-repaired sub-area according to the repair execution sequence; a plurality of monitoring time nodes are set according to the repair execution sequence, environmental feedback data of each monitoring time node is acquired, and it is judged whether to generate an execution instruction of each repair sub-area according to the environmental feedback data. Through the monitoring network, multi-source data collection of the damage area is realized, and through the ecological planning model, the best repair parameters are matched for each sub-area segmented, so that the repair cost and the material input are accurately matched.

Description

Technical Field

[0001] This application relates to the field of restoration technology for mining-damaged areas, and in particular to an intelligent control method and system for ecological restoration of open-pit mining-damaged areas. Background Technology

[0002] Open-pit mining is an important method of mineral resource development in my country, and its share of output continues to rise. However, large-scale stripping and excavation activities have led to land damage, vegetation degradation, soil deterioration, and water loss, especially in ecologically fragile areas where the damage is particularly severe, with long vegetation restoration cycles and low self-sustaining capacity.

[0003] Currently, open-pit mine ecological restoration commonly employs traditional engineering methods such as topography reshaping, topsoil reconstruction, slope reinforcement, and vegetation revegetation, which have restored land productivity and landscape effects to some extent. However, existing monitoring relies mainly on manual patrols and fixed stations, making it difficult to achieve large-scale, high-frequency, and multi-element simultaneous observation. Current schemes largely depend on engineering experience or local surveys, lacking in-depth understanding of the quantitative relationship between mining disturbance intensity and ecological degradation. They also lack systematic evaluation of restoration suitability under different climatic and geomorphological conditions, plant species selection, and soil improvement strategies, leading to significant deviations between design parameters and actual site conditions, and unstable restoration results. The traditional model adopts a linear process of "one design, one construction, one acceptance," ignoring the temporal nature of ecological succession and the randomness of environmental fluctuations. When climate anomalies, water and soil conditions change, or restoration results fall short of expectations, deviations cannot be identified and measures adjusted in a timely manner, resulting in repeated construction and resource waste, significantly increasing restoration costs. Summary of the Invention

[0004] The purpose of this application is to provide an intelligent control method and system for ecological restoration of open-pit mining damaged areas in order to solve the above-mentioned technical problems, thereby improving the efficiency of ecological restoration of open-pit mining damaged areas and reducing the overall restoration cost.

[0005] In some embodiments of this application, a monitoring network is added to collect multi-source data on the damaged area, thereby accurately assessing and segmenting the damaged area. An ecological planning model is added to match the best restoration parameters for each segmented sub-area, achieving a precise match between restoration costs and material inputs, maximizing resource utilization efficiency while ensuring restoration quality.

[0006] In some embodiments of this application, the order of execution for repair is set based on an overall assessment of all sub-regions to be repaired, thereby constructing a spatiotemporal collaborative architecture. The repair of the regions first can indirectly reduce the repair cost of the regions to be repaired later, while avoiding the risk of secondary damage caused by improper governance.

[0007] In some embodiments of this application, an intelligent regulation method for ecological restoration of open-pit mining-damaged areas is provided, including: Establish ecological planning models and monitoring networks for damaged areas; Based on the monitoring network, environmental characteristic parameters of the damaged area are collected, and multiple sub-areas to be repaired are set according to the environmental characteristic parameters; The ecological planning model sets the restoration execution order based on all sub-regions to be restored, and sets the expected restoration strategy for each sub-region to be restored based on the restoration execution order. Multiple monitoring time nodes are set according to the repair execution order, environmental feedback data of each monitoring time node is obtained, and the execution instructions of each repair sub-region are determined based on the environmental feedback data.

[0008] In some embodiments of this application, the establishment of the ecological planning model includes: Establish a damage assessment model; Multiple damage scenarios are set according to the damage assessment model; Within all mining areas, select target damage scenarios sequentially and set up a basic strategy library for each target damage scenario; Establish a preliminary perturbation model for the target damage scenario; Generate a repair sub-model for the target damaged scenario, wherein the repair sub-model includes: a basic strategy library and a pre-disturbance model; Repair sub-models for each damage scenario are established sequentially; An ecological planning model is established based on the damage assessment model and all modified sub-models.

[0009] In some embodiments of this application, the basic strategy library for setting the target damage scenario includes: Establish a baseline damaged area for the target damaged scenario, and set basic repair parameters for the target damaged scenario based on the baseline damaged area; The basic remediation parameters include: soil remediation parameters, vegetation remediation parameters, and hydrological regulation parameters; Multiple deviated damage areas are defined for the target damage scenario; Set up compensation sub-strategies for each deviation from the damaged area in sequence; A basic strategy library for the target damage scenario is generated based on the basic repair parameters and all compensation sub-strategies.

[0010] In some embodiments of this application, the establishment of the pre-disturbance model of the target damage scenario includes: Select the scenes to be associated sequentially from all the damaged scenes, and generate the repair perturbation value of the scenes to be associated for the target damaged scene; If the repair disturbance value is greater than the preset disturbance threshold, the scene to be associated is set as the preceding associated scene of the target damaged scene; Sequentially determine whether each damaged scene is a preceding related scene of the target damaged scene; The preceding perturbation model of the target damage scenario is set based on all preceding related scenarios; The pre-disturbance model includes: a pre-mapping table and a startup evaluation model for the target damage scenario.

[0011] In some embodiments of this application, the step of setting multiple sub-regions to be repaired based on the environmental characteristic parameters includes: Multiple basic data collection points are set according to the monitoring network, and the mapping range of each basic data collection point is set. Obtain the environment sub-packages for each basic data collection point; Aggregate all basic collection points based on all environment sub-packages, and generate multiple collection point subsets based on the aggregation results; Multiple sub-regions to be repaired are set based on a subset of all collected points, and environmental feature parameter packages corresponding to each sub-region to be repaired are generated.

[0012] In some embodiments of this application, the step of setting the expected repair strategy for each sub-region to be repaired includes: The environmental characteristic parameter package of each sub-region to be repaired is input into the damage assessment model, and the mapped damage scene of each sub-region to be repaired is output. Set the execution value for each sub-region to be repaired based on its location parameters and the mapped damage scenario. The execution repair order is set according to all execution values, and the target repair areas are selected sequentially according to the execution repair order; Generate the expected repair volume for the target repair area; Based on the expected repair volume and the basic strategy library of the target repair area, the expected repair strategy for the target repair area is set.

[0013] In some embodiments of this application, the expected repair strategy for setting the target repair area includes: The target repair area is divided into multiple primary sub-regions; Select the target first-level region sequentially within all first-level sub-regions, and generate the matching value of the baseline damaged region in the mapped damaged scenario of the target first-level region and the target repair region; If the fit value is greater than the preset fit threshold; The basic repair parameters of the mapped damage scenario of the target repair area are set as the mapping repair parameters of the target primary area; If the fit value is less than the preset fit value, a first-level compensation instruction is generated; The mapping and repair parameters of the target primary region are set according to the primary compensation instruction; The mapping repair parameters for each first-level sub-region are set sequentially, and the expected repair strategy for the target repair region is set based on all the mapping repair parameters.

[0014] In some embodiments of this application, determining whether to generate execution instructions for each repair sub-region includes: The sub-region to be started is selected based on the execution repair order at the current monitoring time node; Obtain the environment feedback packet for the sub-region to be started; The startup value of the sub-region to be started is set according to the startup evaluation model of the environmental feedback package and the mapped damage scenario of the sub-region to be started; If the startup value is greater than the preset startup value threshold, a repair deviation value is generated based on the environmental feedback package and the expected repair amount of the sub-region to be started. If the deviation value exceeds the preset deviation threshold, a level 1 execution instruction will be generated. If the repair deviation value is less than the preset deviation threshold, a secondary execution instruction is generated.

[0015] In some embodiments of this application, an intelligent control system for ecological restoration of open-pit mining-damaged areas is provided, comprising: Monitoring units are used to construct a monitoring network for damaged areas; Planning units are used to establish ecological planning models; The planning unit includes: The first processing module is used to collect environmental characteristic parameters of the damaged area through the monitoring network, and set multiple sub-areas to be repaired based on the environmental characteristic parameters; The second processing module is used to set the repair execution order according to all sub-regions to be repaired based on the ecological planning model, and to set the expected repair strategy for each sub-region to be repaired based on the repair execution order. The decision module is used to set multiple monitoring time nodes according to the repair execution order, obtain environmental feedback data for each monitoring time node, and determine whether to generate execution instructions for each repair sub-region based on the environmental feedback data. The third processing module is used to establish a damage assessment model; Multiple damage scenarios are set according to the damage assessment model; Within all mining areas, select target damage scenarios sequentially and set up a basic strategy library for each target damage scenario; Establish a preliminary perturbation model for the target damage scenario; Generate a repair sub-model for the target damaged scenario, wherein the repair sub-model includes: a basic strategy library and a pre-disturbance model; Repair sub-models for each damage scenario are established sequentially; An ecological planning model is established based on the damage assessment model and all modified sub-models; The basic strategy library for setting the target damage scenario includes: Establish a baseline damaged area for the target damaged scenario, and set basic repair parameters for the target damaged scenario based on the baseline damaged area; The basic remediation parameters include: soil remediation parameters, vegetation remediation parameters, and hydrological regulation parameters; Multiple deviated damage areas are defined for the target damage scenario; Set up compensation sub-strategies for each deviation from the damaged area in sequence; A basic strategy library for the target damage scenario is generated based on the basic repair parameters and all compensation sub-strategies.

[0016] In some embodiments of this application, the third processing module is further configured to: Select the scenes to be associated sequentially from all the damaged scenes, and generate the repair perturbation value of the scenes to be associated for the target damaged scene; If the repair disturbance value is greater than the preset disturbance threshold, the scene to be associated is set as the preceding associated scene of the target damaged scene; Sequentially determine whether each damaged scene is a preceding related scene of the target damaged scene; The preceding perturbation model of the target damage scenario is set based on all preceding related scenarios; The pre-disturbance model includes: a pre-mapping table and a startup evaluation model for the target damage scenario.

[0017] Compared with existing technologies, the intelligent control method and system for ecological restoration of open-pit mining-damaged areas disclosed in this application have the following advantages: By adding a monitoring network to collect multi-source data on the damaged area, the damaged area can be accurately assessed and segmented. By adding an ecological planning model, the best restoration parameters can be matched to each segmented sub-area, so as to achieve a precise match between restoration costs and material input, and maximize resource utilization efficiency while ensuring restoration quality.

[0018] By setting the order of repairs based on a holistic assessment of all sub-regions to be repaired, a spatiotemporal collaborative architecture is constructed. Repairing regions first can indirectly reduce the repair costs of subsequent regions, while avoiding the risk of secondary damage due to improper governance. Attached Figure Description

[0019] Figure 1 This is a flowchart illustrating a preferred embodiment of an intelligent control method for ecological restoration of open-pit mining-damaged areas. Detailed Implementation

[0020] The specific embodiments of this application will be described in further detail below with reference to the accompanying drawings and examples. The following examples are used to illustrate this application, but are not intended to limit the scope of this application.

[0021] In the description of this application, it should be understood that the terms "center", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0022] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0023] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "linking" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection between two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0024] like Figure 1 As shown in the preferred embodiment of this application, a method for intelligent regulation and control of ecological restoration of open-pit mining-damaged areas includes: S101: Establish an ecological planning model and a monitoring network for damaged areas; S102: Collect environmental characteristic parameters of the damaged area based on the monitoring network, and set multiple sub-areas to be repaired according to the environmental characteristic parameters; S103: The ecological planning model sets the restoration execution order based on all sub-regions to be restored, and sets the expected restoration strategy for each sub-region to be restored based on the restoration execution order; S104: Set multiple monitoring time nodes according to the repair execution order, obtain environmental feedback data of each monitoring time node, and determine whether to generate execution instructions for each repair sub-region based on the environmental feedback data.

[0025] Specifically, the monitoring network consists of a satellite remote sensing monitoring subsystem, UAV remote sensing monitoring equipment, ground-based IoT monitoring equipment, and underground detection equipment. It is used to collect various environmental data in the damaged area (multi-dimensional spatiotemporal data such as topography, vegetation cover, soil quality, hydrological conditions, and meteorological environment, including parameters such as soil moisture, pH, nutrient content, slope displacement, groundwater level, and meteorological conditions).

[0026] Specifically, by preprocessing the collected data, environmental characteristic parameters of the damaged area are generated (including: surface slope, relative elevation difference, surface roughness, available topsoil thickness, organic matter content, pH value and salinity, catchment area, groundwater depth, slope stability, vegetation coverage and other environmental parameters that reflect the difficulty of restoration).

[0027] It is understandable that in the above embodiments, by adding a monitoring network, multi-source data collection of the damaged area is achieved, and a comprehensive quantitative structure of four dimensions—topography, soil degradation, vegetation damage, and hydrological disturbance—is established to achieve accurate assessment and segmentation of the damaged area.

[0028] In a preferred embodiment of this application, establishing an ecological planning model includes: Establish a damage assessment model; Multiple damage scenarios are set based on the damage assessment model; Within all mining areas, select target damage scenarios sequentially and set up a basic strategy library for each target damage scenario; Establish a preliminary perturbation model for the target damage scenario; Generate a repair sub-model for the target damage scenario. The repair sub-model includes: a basic policy library and a pre-disturbance model. Repair sub-models for each damage scenario are established sequentially; An ecological planning model is established based on the damage assessment model and all modified sub-models.

[0029] Specifically, based on historical damage records (i.e., initial environmental data and corresponding restoration execution parameters of mining-damaged areas that have undergone ecological restoration), a screening and analysis is conducted to select multiple environmental characteristic indicators (including but not limited to: surface slope, relative elevation difference, surface roughness, available topsoil thickness, organic matter content, pH value and salinity, catchment area, groundwater depth, slope stability, and vegetation coverage). A damage assessment model is then constructed based on all environmental characteristic indicators.

[0030] Specifically, the damage assessment model can quantify all environmental characteristic indicators, thereby generating multiple mapping intervals for each environmental characteristic indicator (for example, the mapping intervals for surface slope include less than 15 degrees, 15 to 30 degrees, and more than 30 degrees; the mapping intervals for relative height difference are less than 10 meters, more than 50 meters, and between 10 and 50 meters, etc.). These mapping intervals can be set by analyzing historical damage record data.

[0031] Specifically, multiple damage scenarios are generated based on a random combination of all mapping intervals of various environmental characteristic indicators.

[0032] Specifically, the basic strategy library for setting target damage scenarios includes: Establish a baseline damaged area for the target damaged scenario, and set basic repair parameters for the target damaged scenario based on the baseline damaged area; Basic remediation parameters include: soil remediation parameters, vegetation remediation parameters, and hydrological regulation parameters; Set multiple deviated damaged areas in the target damaged scene; Set up compensation sub-strategies for each deviation from the damaged area in sequence; A basic strategy library for the target damage scenario is generated based on the basic repair parameters and all compensation sub-strategies.

[0033] Specifically, the unit repair area is set (i.e., the optimal collection range of ground IoT monitoring equipment and underground detection equipment in the monitoring network).

[0034] Specifically, the relevant data of the target damage scene are filtered from the historical damage record data, and the corresponding historical damage area in the relevant data is divided using the unit repair area, with the size of each segmented area being the same as the unit repair area.

[0035] Specifically, by analyzing the associated data, the mapping intervals of various environmental feature indicators corresponding to the target damaged area are further refined, thereby generating multiple sub-intervals corresponding to each environmental feature indicator. Multiple initial damaged areas in the target damaged scenario are generated based on a random combination of all sub-intervals. By comparing and analyzing all environmental feature indicators corresponding to each segmented area, a benchmark damaged area is selected (if the difference between the environmental feature parameters corresponding to the current initial damaged area and the current segmented area is less than a preset difference threshold, then the current segmented area is a similar segmented area to the current initial damaged area, and the initial segmented area with the most similar segmented areas is selected as the benchmark damaged area). The remaining initial damaged areas are set as deviating damaged areas. Specifically, by performing optimization analysis on the associated data, the baseline damaged area is selected to set the basic repair parameters for the target damaged scenario (i.e., the soil repair parameters, vegetation repair parameters, and hydrological control parameters that need to be executed when the environmental characteristic indicators of the sub-area to be repaired are in the target damaged scenario. For example, when the surface slope of the target damaged area is high, the available topsoil thickness is small, the salinity is high, and the catchment area is low, large-scale mechanical intervention is required to reconstruct the terrain, soil, and vegetation community, and the specific execution order and the initial repair degree of the corresponding terrain, soil, and vegetation community are set, i.e., soil repair parameters and vegetation repair parameters need to be executed, but hydrological repair parameters do not need to be executed). The basic repair parameters have the best repair effect on the baseline damaged area within the target damaged area.

[0036] Specifically, by analyzing the associated data, compensation sub-strategies are generated for each deviated area in the target damage scenario (i.e., based on the degree of difference between the deviated damage area and the baseline damage area, the initial repair degree of the terrain, soil, vegetation community and hydrology in the baseline repair parameters is adjusted without changing the overall repair framework, thereby achieving accurate matching of repair resources for each different sub-area in the target damage scenario and reducing the overall repair cost).

[0037] Specifically, a preliminary perturbation model for the target damage scenario is established, including: Select the scenes to be associated sequentially from all the damaged scenes, and generate the repair perturbation value of the scenes to be associated for the target damaged scene; If the disturbance value to be repaired is greater than the preset disturbance threshold, the scene to be associated is set as the preceding associated scene of the target damaged scene; Determine in turn whether each damaged scene is a preceding related scene of the target damaged scene; Based on all the preceding related scenarios, set the preceding perturbation model for the target damage scenario; The pre-disturbance model includes: a pre-map table and a startup evaluation model for the target damage scenario.

[0038] Specifically, by analyzing historical damage records and combining them with simulations, repair perturbation values ​​are generated for the scenario to be associated and the target damaged scenario. That is, when the damaged area corresponding to the scenario to be associated and the area corresponding to the target damaged scenario are adjacent, a primary repair assessment value for the target damaged scenario is generated after repairing the damaged area of ​​the scenario to be associated first, and a secondary repair assessment value is generated after directly repairing the target damaged scenario. The difference between the primary and secondary repair assessment values ​​is set as the repair perturbation value of the scenario to be associated for the target damaged scenario (the larger the repair perturbation value, the higher the repair benefit for the damaged area corresponding to the target damaged scenario after repairing the damaged area corresponding to the scenario to be associated first). Specifically, the first-level repair cost of the target damaged scene is generated after the damaged areas of the related scenes are repaired first (i.e., the amount of repair resources required for the indirect repair of the damaged areas of the target damaged scene after the damaged areas of the related scenes are repaired, and then the target damaged scene is repaired). The lower the repair cost, the larger the corresponding first repair evaluation value.

[0039] Specifically, the secondary repair cost (i.e., the expected amount of repair resources and the amount of backup repair resources needed for secondary damage caused by the lack of repair in the surrounding area) is generated to directly repair the target damaged scene. The lower the secondary repair cost, the higher the corresponding secondary repair assessment value. Furthermore, the first and second repair assessment values ​​have the same range.

[0040] Specifically, the disturbance threshold can be set based on historical parameters. When the real-time repair disturbance value is greater than the preset disturbance threshold, it means that when the damaged area corresponding to the scene to be associated and the area corresponding to the target damaged scene are adjacent, repairing the damaged area corresponding to the scene to be associated first will have a substantial impact and benefit on the damaged area corresponding to the target damaged scene. At this time, the scene to be associated is set as the preceding associated scene of the target damaged scene (i.e., the scene that needs to be repaired first).

[0041] Specifically, the preceding mapping table includes all preceding related scenarios of the target damage scenario.

[0042] Specifically, the startup evaluation model includes a first-level time interval (i.e., when there are preceding related scenarios, the time interval between the start time of the repair of the preceding related scenario and the latest start time of the repair of the target damaged scenario) and the indirect repair level of the target damaged scenario (i.e., after the preceding related scenario starts repair, to what extent the damaged area corresponding to the target damaged scenario needs to reach before its own repair parameters can be executed). By starting the evaluation model, the startup timing of the target damaged scenario can be accurately controlled, thereby improving the overall repair efficiency.

[0043] In a preferred embodiment of this application, multiple sub-regions to be repaired are defined based on environmental characteristic parameters, including: Multiple basic data collection points are set up according to the monitoring network, and the mapping range of each basic data collection point is set. Obtain the environment sub-packages for each basic data collection point; Aggregate all basic collection points based on all environment sub-packages, and generate multiple collection point subsets based on the aggregation results; Multiple sub-regions to be repaired are set based on a subset of all collected points, and environmental feature parameter packages corresponding to each sub-region to be repaired are generated.

[0044] Specifically, multiple basic collection points are set up within the current damaged area based on the unit repair area, and each basic collection point is equipped with a data collection device (ground IoT monitoring equipment and underground detection equipment). The data collection range corresponding to each basic collection point is set as the mapping range, which is the same as the unit repair area.

[0045] Specifically, soil data within the corresponding mapping area is collected by data acquisition devices at each basic acquisition point, and environmental sub-packages (i.e., multi-dimensional spatiotemporal data such as topography, vegetation cover, soil quality, hydrological conditions, and meteorological environment within the mapping range corresponding to the current basic acquisition point) are generated by filtering and analyzing the data collected by the satellite remote sensing monitoring subsystem and UAV remote sensing monitoring devices.

[0046] Specifically, by performing similarity analysis on the environmental sub-packages corresponding to all basic collection points, all basic collection points are aggregated. Within a single collection point subset, the environmental sub-packages corresponding to each basic collection point represent the same damaged scenario. Furthermore, each basic collection point is adjacent to at least one other basic collection point within its subset. The mapping ranges corresponding to all basic collection points within the subset are then merged to generate the repair area corresponding to that subset.

[0047] Specifically, the environmental sub-packages corresponding to each basic collection point in the current collection point subset are fused and analyzed to generate an environmental parameter feature package (i.e., the parameter values ​​of each environmental feature index corresponding to the sub-region to be repaired) for the current collection point subset.

[0048] It is understandable that in the above embodiments, the order of execution for repair is set based on an overall assessment of all sub-regions to be repaired, thereby constructing a spatiotemporal collaborative architecture. The repair of the regions first can indirectly reduce the repair cost of the regions to be repaired later, while avoiding the risk of secondary damage caused by improper governance.

[0049] In a preferred embodiment of this application, the expected repair strategy for each sub-region to be repaired is set, including: Input the environmental characteristic parameter package of each sub-region to be repaired into the damage assessment model, and output the mapped damage scene of each sub-region to be repaired; Set the execution value for each sub-region to be repaired based on its location parameters and the mapped damage scenario. The execution repair order is set based on all executed values, and the target repair areas are selected sequentially according to the execution repair order; Generate the expected repair volume for the target repair area; Based on the expected repair volume and the base strategy library of the target repair area, set the expected repair strategy for the target repair area.

[0050] Specifically, the difference between the environmental feature parameter package corresponding to the current sub-region to be repaired and each damaged scene (i.e., the degree of difference between the corresponding environmental feature indicators) is generated. The greater the difference, the smaller the corresponding fit value. The damaged scene corresponding to the maximum value among all fit values ​​is selected as the mapped damaged scene of the current sub-region to be repaired.

[0051] Specifically, by analyzing the whole system, sub-regions to be repaired that do not have any preceding associated scenarios (i.e., the mapping damage scenarios corresponding to each adjacent region of the current sub-region to be repaired are not preceding associated scenarios of the mapping damage scenarios corresponding to the current sub-region to be repaired) are selected, and the execution value of these sub-regions is set to 1. Then, sub-regions to be repaired that can be used as preceding associated scenarios are selected, and the execution value of these sub-regions to be repaired is set to 2. This process is repeated to generate the execution value of each sub-region to be repaired.

[0052] The execution repair order is set according to the order of execution values ​​from smallest to largest. If the execution values ​​of two sub-regions to be repaired are the same, then the two sub-regions to be repaired are in the same position in the execution repair order, that is, they can be repaired in parallel.

[0053] Specifically, the expected repair volume refers to the extent to which the target repair area can be indirectly reached after repair begins, based on the adjacent preceding areas (i.e., the sub-areas to be repaired in the preceding related scenarios corresponding to the target repair area's mapping scenario). Furthermore, the expected repair volume includes the expected fluctuations of various environmental characteristic indicators (i.e., the degree of indirect repair in the preceding assessment model of the mapped damage scenario corresponding to the target repair area).

[0054] Specifically, the expected repair strategy for the target repair area includes: The target repair area is divided into multiple primary sub-regions; Select the target first-level region sequentially within all first-level sub-regions, and generate the matching value of the baseline damaged region in the mapped damaged scene of the target first-level region and the target repair region; If the fit value is greater than the preset fit threshold; Set the basic repair parameters of the mapped damaged scene of the target repair area as the mapping repair parameters of the target first-level area; If the matching value is less than the preset matching value, a level 1 compensation instruction is generated; Set the mapping and repair parameters for the target primary region according to the primary compensation instruction; Set the mapping repair parameters for each first-level sub-region in sequence, and set the expected repair strategy for the target repair region based on all mapping repair parameters.

[0055] Specifically, the target repair area is divided into multiple first-level sub-regions based on the basic collection points, where each first-level sub-region corresponds to the mapping range of a basic collection point.

[0056] Specifically, based on the environmental sub-package of the target primary region and the expected repair amount of the target repair scenario, an expected environmental sub-package of the target primary region is generated (that is, the parameter values ​​of each corresponding environmental feature index in the environmental sub-package are adjusted by the expected repair amount, and the adjusted parameter values ​​are set as the expected environmental sub-package).

[0057] Specifically, the degree of difference in the baseline damaged area is generated based on the expected environmental sub-package of the target primary area. The greater the degree of difference, the smaller the corresponding fit value.

[0058] Specifically, when the matching value is greater than the preset matching threshold, it indicates that the damage state of the target primary area is the same as that of the baseline damaged area. In this case, calling the basic repair parameters in the mapped damage scenario can achieve optimal repair for the target primary area.

[0059] Specifically, when the matching value is less than a preset matching value threshold, it indicates a difference between the damage state corresponding to the target primary area and the damage state corresponding to the baseline damage area. In this case, matching values ​​are generated for each deviating damage area in the target primary area and the mapped damage scene according to the primary compensation instruction. The compensation sub-strategy for the deviating damage scene corresponding to the maximum matching value is then called to adjust the basic repair parameters of the mapped damage scene. The adjustment result is set as the mapping repair parameters for the target primary area.

[0060] It is understandable that in the above embodiments, by adding an ecological planning model to match the best restoration parameters for each segmented sub-region, the restoration cost and material input are accurately matched, thereby maximizing resource utilization efficiency while ensuring restoration quality.

[0061] In a preferred embodiment of this application, determining whether to generate execution instructions for each repair sub-region includes: Select the sub-region to be started based on the order of execution and repair; Obtain the environment feedback packet for the sub-region to be started; The activation value of the sub-region to be activated is set according to the activation evaluation model of the environmental feedback package and the mapped damage scenario of the sub-region to be activated; If the startup value is greater than the preset startup value threshold, a repair deviation value is generated based on the environmental feedback package and the expected repair amount of the sub-region to be started. If the deviation value exceeds the preset deviation threshold, a level 1 execution instruction will be generated. If the repair deviation value is less than the preset deviation threshold, a secondary execution instruction is generated.

[0062] Specifically, the environmental feedback package contains the real-time environmental characteristic parameters of the sub-region to be started and the start-up duration of the adjacent preceding regions of the sub-region to be started. The environmental feedback package is input into the start-up evaluation model of the sub-region to be started, and it is determined whether the start-up duration is greater than the first-level time interval within the start-up evaluation model. If it is greater, the start-up value is set to 1; if it is not greater, the similarity between the real-time environmental characteristic parameters and the degree of indirect repair in the start-up evaluation model is analyzed. If the similarity value is greater than a preset similarity threshold, the start-up value is set to 1; if the similarity value is less than the similarity threshold, the start-up value is set to 0.

[0063] Specifically, the startup threshold is set to 0.5.

[0064] Specifically, the actual repair amount is generated based on the environmental feedback package. When the actual repair amount exceeds the expected repair amount (i.e., the actual interference effect exceeds the expectation), the repair deviation value is set to 0.

[0065] When the actual repair amount is less than the expected repair amount (i.e. the actual interference effect does not reach the expected level), the repair deviation amount is set according to the degree of difference between the actual repair amount and the expected repair amount. The higher the degree of difference, the larger the corresponding repair deviation value.

[0066] Specifically, the deviation threshold can be set based on historical parameters. The first-level execution instruction means that the expected interference in the corresponding sub-region to be started has not reached the expected level. At this time, the initially set expected repair strategy needs to be adjusted before ecological repair can be carried out in the sub-region to be started.

[0067] The Level 2 execution instruction refers to directly executing the expected restoration strategy to carry out ecological restoration of the sub-region to be initiated.

[0068] In another preferred embodiment of the intelligent control method for ecological restoration of open-pit mining-damaged areas based on any of the above preferred embodiments, this preferred embodiment provides an intelligent control system for ecological restoration of open-pit mining-damaged areas, including: Monitoring units are used to construct a monitoring network for damaged areas; Planning units are used to establish ecological planning models; The planning unit includes: The first processing module is used to collect environmental characteristic parameters of the damaged area through the monitoring network, and set multiple sub-areas to be repaired based on the environmental characteristic parameters; The second processing module is used to set the restoration execution order based on all sub-regions to be restored using an ecological planning model, and to set the expected restoration strategy for each sub-region to be restored based on the restoration execution order. The decision module is used to set multiple monitoring time nodes according to the repair execution order, obtain environmental feedback data at each monitoring time node, and determine whether to generate execution instructions for each repair sub-region based on the environmental feedback data. The third processing module is used to establish a damage assessment model; Multiple damage scenarios are set based on the damage assessment model; Within all mining areas, select target damage scenarios sequentially and set up a basic strategy library for each target damage scenario; Establish a preliminary perturbation model for the target damage scenario; Generate a repair sub-model for the target damage scenario. The repair sub-model includes: a basic policy library and a pre-disturbance model. Repair sub-models for each damage scenario are established sequentially; An ecological planning model is established based on the damage assessment model and all modified sub-models; The basic strategy library for setting target damage scenarios includes: Establish a baseline damaged area for the target damaged scenario, and set basic repair parameters for the target damaged scenario based on the baseline damaged area; Basic remediation parameters include: soil remediation parameters, vegetation remediation parameters, and hydrological regulation parameters; Set multiple deviated damaged areas in the target damaged scene; Set up compensation sub-strategies for each deviation from the damaged area in sequence; A basic strategy library for the target damage scenario is generated based on the basic repair parameters and all compensation sub-strategies.

[0069] Specifically, the third processing module is also used for: Select the scenes to be associated sequentially from all the damaged scenes, and generate the repair perturbation value of the scenes to be associated for the target damaged scene; If the disturbance value to be repaired is greater than the preset disturbance threshold, the scene to be associated is set as the preceding associated scene of the target damaged scene; Determine in turn whether each damaged scene is a preceding related scene of the target damaged scene; Based on all the preceding related scenarios, set the preceding perturbation model for the target damage scenario; The pre-disturbance model includes: a pre-map table and a startup evaluation model for the target damage scenario.

[0070] According to the first concept of this application, a monitoring network is added to collect multi-source data on the damaged area, thereby accurately assessing and segmenting the damaged area. An ecological planning model is added to match the best restoration parameters for each segmented sub-area, achieving a precise match between restoration costs and material inputs, maximizing resource utilization efficiency while ensuring restoration quality.

[0071] According to the second concept of this application, a spatiotemporal collaborative architecture is constructed by setting the order of repair based on an overall assessment of all sub-regions to be repaired. The repair of the regions first can indirectly reduce the repair cost of the regions to be repaired later, while avoiding the risk of secondary damage caused by improper governance.

[0072] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and substitutions can be made without departing from the technical principles of this application, and these improvements and substitutions should also be considered within the scope of protection of this application.

Claims

1. An intelligent control method for ecological restoration of a surface mining damage area, characterized in that, include: Establish ecological planning models and monitoring networks for damaged areas; Based on the monitoring network, environmental characteristic parameters of the damaged area are collected, and multiple sub-areas to be repaired are set according to the environmental characteristic parameters; The ecological planning model sets the restoration execution order based on all sub-regions to be restored, and sets the expected restoration strategy for each sub-region to be restored based on the restoration execution order. Multiple monitoring time nodes are set according to the repair execution order, environmental feedback data of each monitoring time node is obtained, and the execution instructions of each repair sub-region are determined based on the environmental feedback data.

2. The intelligent regulation method for ecological restoration of open-pit mining-damaged areas as described in claim 1, characterized in that, The establishment of the ecological planning model includes: Establish a damage assessment model; Multiple damage scenarios are set according to the damage assessment model; Within all mining areas, select target damage scenarios sequentially and set up a basic strategy library for each target damage scenario; Establish a preliminary perturbation model for the target damage scenario; Generate a repair sub-model for the target damaged scenario, wherein the repair sub-model includes: a basic strategy library and a pre-disturbance model; Repair sub-models for each damage scenario are established sequentially; An ecological planning model is established based on the damage assessment model and all modified sub-models.

3. The intelligent regulation method for ecological restoration of open-pit mining-damaged areas as described in claim 2, characterized in that, The basic strategy library for setting target damage scenarios includes: Establish a baseline damaged area for the target damaged scenario, and set basic repair parameters for the target damaged scenario based on the baseline damaged area; The basic remediation parameters include: soil remediation parameters, vegetation remediation parameters, and hydrological regulation parameters; Multiple deviated damage areas are defined for the target damage scenario; Set up compensation sub-strategies for each deviation from the damaged area in sequence; A basic strategy library for the target damage scenario is generated based on the basic repair parameters and all compensation sub-strategies.

4. The intelligent regulation method for ecological restoration of open-pit mining-damaged areas as described in claim 3, characterized in that, The establishment of the pre-disturbance model for the target damage scenario includes: Select the scenes to be associated sequentially from all the damaged scenes, and generate the repair perturbation value of the scenes to be associated for the target damaged scene; If the repair disturbance value is greater than the preset disturbance threshold, the scene to be associated is set as the preceding associated scene of the target damaged scene; Sequentially determine whether each damaged scene is a preceding related scene of the target damaged scene; The preceding perturbation model of the target damage scenario is set based on all preceding related scenarios; The pre-disturbance model includes: a pre-mapping table and a startup evaluation model for the target damage scenario.

5. The intelligent regulation method for ecological restoration of open-pit mining-damaged areas as described in claim 4, characterized in that, The step of setting multiple sub-regions to be repaired based on the environmental characteristic parameters includes: Multiple basic data collection points are set according to the monitoring network, and the mapping range of each basic data collection point is set. Obtain the environment sub-packages for each basic data collection point; Aggregate all basic collection points based on all environment sub-packages, and generate multiple collection point subsets based on the aggregation results; Multiple sub-regions to be repaired are set based on a subset of all collected points, and environmental feature parameter packages corresponding to each sub-region to be repaired are generated.

6. The intelligent regulation method for ecological restoration of open-pit mining-damaged areas as described in claim 5, characterized in that, The setting of the expected repair strategy for each sub-region to be repaired includes: The environmental characteristic parameter package of each sub-region to be repaired is input into the damage assessment model, and the mapped damage scene of each sub-region to be repaired is output. Set the execution value for each sub-region to be repaired based on its location parameters and the mapped damage scenario. The execution repair order is set according to all execution values, and the target repair areas are selected sequentially according to the execution repair order; Generate the expected repair volume for the target repair area; Based on the expected repair volume and the basic strategy library of the target repair area, the expected repair strategy for the target repair area is set.

7. The intelligent regulation method for ecological restoration of open-pit mining-damaged areas as described in claim 6, characterized in that, The expected repair strategy for the defined target repair area includes: The target repair area is divided into multiple primary sub-regions; Select the target first-level region sequentially within all first-level sub-regions, and generate the matching value of the baseline damaged region in the mapped damaged scenario of the target first-level region and the target repair region; If the fit value is greater than the preset fit threshold; The basic repair parameters of the mapped damage scenario of the target repair area are set as the mapping repair parameters of the target primary area; If the fit value is less than the preset fit value, a first-level compensation instruction is generated; The mapping and repair parameters of the target primary region are set according to the primary compensation instruction; The mapping repair parameters for each first-level sub-region are set sequentially, and the expected repair strategy for the target repair region is set based on all the mapping repair parameters.

8. The intelligent regulation method for ecological restoration of open-pit mining-damaged areas as described in claim 7, characterized in that, The determination of whether to generate execution instructions for each repair sub-region includes: The sub-region to be started is selected based on the execution repair order at the current monitoring time node; Obtain the environment feedback packet for the sub-region to be started; The startup value of the sub-region to be started is set according to the startup evaluation model of the environmental feedback package and the mapped damage scenario of the sub-region to be started; If the startup value is greater than the preset startup value threshold, a repair deviation value is generated based on the environmental feedback package and the expected repair amount of the sub-region to be started. If the deviation value exceeds the preset deviation threshold, a level 1 execution instruction will be generated. If the repair deviation value is less than the preset deviation threshold, a secondary execution instruction is generated.

9. An intelligent control system for ecological restoration of open-pit mining damaged areas, employing the intelligent control method for ecological restoration of open-pit mining damaged areas as described in any one of claims 1-8, characterized in that, include: Monitoring units are used to construct a monitoring network for damaged areas; Planning units are used to establish ecological planning models; The planning unit includes: The first processing module is used to collect environmental characteristic parameters of the damaged area through the monitoring network, and set multiple sub-areas to be repaired based on the environmental characteristic parameters; The second processing module is used to set the repair execution order according to all sub-regions to be repaired based on the ecological planning model, and to set the expected repair strategy for each sub-region to be repaired based on the repair execution order. The decision module is used to set multiple monitoring time nodes according to the repair execution order, obtain environmental feedback data for each monitoring time node, and determine whether to generate execution instructions for each repair sub-region based on the environmental feedback data. The third processing module is used to establish a damage assessment model; Multiple damage scenarios are set according to the damage assessment model; Within all mining areas, select target damage scenarios sequentially and set up a basic strategy library for each target damage scenario; Establish a preliminary perturbation model for the target damage scenario; Generate a repair sub-model for the target damaged scenario, wherein the repair sub-model includes: a basic strategy library and a pre-disturbance model; Repair sub-models for each damage scenario are established sequentially; An ecological planning model is established based on the damage assessment model and all modified sub-models; The basic strategy library for setting the target damage scenario includes: Establish a baseline damaged area for the target damaged scenario, and set basic repair parameters for the target damaged scenario based on the baseline damaged area; The basic remediation parameters include: soil remediation parameters, vegetation remediation parameters, and hydrological regulation parameters; Multiple deviated damage areas are defined for the target damage scenario; Set up compensation sub-strategies for each deviation from the damaged area in sequence; A basic strategy library for the target damage scenario is generated based on the basic repair parameters and all compensation sub-strategies.

10. The intelligent control system for ecological restoration of open-pit mining damaged areas as described in claim 9, characterized in that, The third processing module is also used for: Select the scenes to be associated sequentially from all the damaged scenes, and generate the repair perturbation value of the scenes to be associated for the target damaged scene; If the repair disturbance value is greater than the preset disturbance threshold, the scene to be associated is set as the preceding associated scene of the target damaged scene; Sequentially determine whether each damaged scene is a preceding related scene of the target damaged scene; The preceding perturbation model of the target damage scenario is set based on all preceding related scenarios; The pre-disturbance model includes: a pre-mapping table and a startup evaluation model for the target damage scenario.

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