A method and system for intelligent management of geological data

Abstract

This invention discloses an intelligent management method and system for geological data, relating to the field of slope geological data management technology. The invention locates the target work area and collects data from it to construct a location time series set. It then uses a simulation model and imports the location time series set into the model to construct a scenario simulation model of the target work area. The scenario simulation model is divided into local sub-regions, and based on the division results, slope geological stability assessment and analysis are performed on each sub-region to determine risk sub-regions. Based on these risk sub-regions, a risk integration area within the target work area is determined. The slope geological stability fluctuation data of the risk integration area is analyzed, and combined with historical slope geological data of the target work area, a comparative analysis is performed on the current target work area to determine the abnormal state of the slope geological data in the current target work area. This invention achieves in-depth mining and analysis of multi-volume slope geological data.

Description

Technical Field

[0001] This invention relates to the field of slope geological data management, specifically to an intelligent management method and system for geological data. Background Technology

[0002] In infrastructure construction, mining, and water conservancy projects, the stability of slope geological data is of paramount importance. Traditional slope geological data management often relies on manual inspections and single-point sensors for data collection. This approach has several drawbacks. First, the monitoring parameters are limited, making it difficult to capture and analyze signals when slope geological data becomes unstable. Second, manual inspections are time-consuming, leading to delayed data analysis and risk warnings. Furthermore, traditional methods lack intelligent analysis capabilities for massive amounts of monitoring data, making it difficult to conduct in-depth intelligent mining and analysis of large volumes of mixed-type slope geological data. Relying solely on human experience is insufficient to meet the safety management needs of modern engineering projects for slope geological data. Summary of the Invention

[0003] The purpose of this invention is to provide an intelligent management method and system for geological data to solve the problems raised in the prior art.

[0004] To achieve the above objectives, the present invention provides the following technical solution: An intelligent management method for geological data, comprising the following steps: By locating the target work area and building a real-time data perception system, slope geological data of the target work area is collected, the collected data is processed with location tags, and a location time series set is constructed. Using a simulation model and importing the location time series set corresponding to the target work area into the model, a real-time scene simulation of the target work area is performed to construct a scene simulation model of the target work area. By dividing the scene simulation model into local sub-regions, slope geological stability assessment and analysis are performed on each sub-region according to the division results. Based on the slope geological stability assessment results of each sub-region, risk sub-regions are determined, and risk integration areas within the target work area are determined based on the risk sub-regions. The slope geological stability fluctuation data of the risk integration area are analyzed, and combined with the historical slope geological data of the target work area, a comparative analysis is performed on the current target work area to determine the abnormal state of the slope geological data in the current target work area.

[0005] Furthermore, the positioning of the target work area is performed by combining the coordinate positioning method with the coordinate data of the target work area; wherein the coordinate positioning method is satellite positioning, which can be GPS positioning or Beidou positioning; the coordinate data of the target work area is stored in a database and can be obtained by retrieving the database; The data perception system includes a scene 3D data acquisition subsystem and a slope data acquisition subsystem. The 3D data acquisition subsystem is used to acquire 3D data of the target work area. The slope data acquisition subsystem is used to acquire slope geological data of the target work area. The acquisition of 3D data of the target work area involves using a remote sensing drone to identify environmental features of the target work area scene and generating 3D cloud points for each environmental feature based on the identification results. Environmental features include mountains, rock layers, soil layers, and water quality. Slope geological data includes topographic data, soil and rock condition data, and hydrological data. Topographic data includes slope height and slope angle. Soil and rock condition data includes unit weight, density, and water content. Hydrological data includes groundwater level and pore water pressure. After the data sensing system completes data acquisition, it labels the acquired data with corresponding positioning data to construct positioning time series data, and constructs a positioning time series set according to the time sequence; the positioning time series set includes a three-dimensional data positioning time series set and a slope geological data positioning time series set; wherein the positioning data includes the coordinate data and acquisition time data of a certain acquisition point in the corresponding scene.

[0006] Furthermore, the simulation model is constructed based on the three-dimensional data positioning time series collected within the target work area to simulate the corresponding scene space and output a virtual model of the target work area. In the virtual model of the target work area, the real-time collected slope geological data of each coordinate point in the positioning time series of the actual target work area scene is compared with the actual target work area scene and an update log is recorded. During the construction of the simulation model for the target work area, three-dimensional simulation is performed based on the environmental characteristics of each coordinate point in the positioning time series to recreate the actual target work area scene. Based on the output virtual model of the target operation area, the virtual model of the target operation area is divided into local sub-regions by gridding, and each sub-region is labeled and assigned a value according to the division result. The local sub-region division method is to divide the grid based on the smallest area monitored by the UAV in the target operation area within a unit period. Based on the local sub-region gridding of the virtual model of the target operation area, the slope geological data location time series collected in the target operation area is divided into corresponding sub-regions in a unified manner to construct a slope geological data location time series subset for each sub-region.

[0007] Furthermore, based on the local sub-region division results of the virtual model of the target operation area, slope geological data stability assessment and analysis are performed on each sub-region. The specific steps are as follows: S1. In the virtual model of the target work area, each sub-region is located and determined by sub-region labels, and the slope geological data location time series set at each coordinate point in the corresponding sub-region is retrieved according to the location results. S2. Based on the location time series set of slope geological data in the corresponding sub-region, classify and identify the environmental features at each coordinate point to determine the area proportion of different environmental features in the corresponding sub-region. S3. Stability assessment index analysis is performed on different environmental characteristics within each sub-region. Based on the area proportion of different environmental characteristics within the corresponding sub-region, the stability of the slope geological data of the sub-region is assessed and analyzed. The calculation is as follows: Among them, ST n S represents the slope geological data stability assessment value for the corresponding sub-region n; n S represents the area of ​​the subregion with the corresponding number n; m,n α represents the area of ​​the environmental feature numbered m in the corresponding subregion n; m,n This represents the average stability assessment value of environmental feature m in subregion n. The stability assessment values ​​of different environmental features are obtained by analyzing the collected geological data of the corresponding slope. n is the subregion number; m is the environmental feature number; i is the number of environmental features. The average stability assessment value of the corresponding environmental feature is obtained by calculating the average stability assessment values ​​of the environmental features at each coordinate point within the area of ​​the same environmental feature in the corresponding subregion. S4. Based on the assessment and analysis data of slope geological data stability for each sub-region, the reference data for slope geological data stability in the historical data of the sub-region is determined through the database, and a comparative analysis is performed to identify risk sub-regions. The reference data for slope geological data stability in the historical data of the sub-region is used as the comparison value to determine the comparison error and construct a comparison interval. If the current sub-region slope geological data stability assessment value is within the comparison interval, it is determined to be a normal sub-region; otherwise, it is determined to be a risk sub-region. In the virtual model of the target operation area, based on the risk judgment analysis results of each sub-region, the number of each risk sub-region is explicitly marked, and any risk sub-region is used as the starting point for judgment and integration with its adjacent sub-regions. The judgment and integration involves connecting the midpoints of the two risk sub-regions if an adjacent sub-region is also a risk sub-region, and continuing to the next adjacent sub-region for judgment. Conversely, if the adjacent sub-region of a risk sub-region is a normal sub-region, the judgment continues for the next adjacent sub-region. When all risk sub-region judgments and integrations are completed, the area formed by connecting the endpoints of each risk sub-region is recorded as the risk integration area. The risk integration area includes the area of ​​the risk sub-region and the area of ​​the sub-region enclosed by the connecting endpoints of the risk sub-regions. When risk sub-regions are not consecutively adjacent, the area formed by connecting their endpoints will include the normal sub-region, and the normal sub-region enclosed by the risk sub-region will be affected by the risk. Therefore, the risk sub-region and the surrounding normal sub-region are integrated into the risk integration area. Slope geological stability fluctuation data analysis is performed on the risk integration area in the virtual model of the target operation area. This analysis combines the stability assessment data of each risk sub-region and the stability assessment data of the normal sub-region within the risk integration area. The calculation formula is as follows: ; Where Dt is the fluctuation value of the geological stability of the slope in the risk integration area; S abn S represents the sum of the areas of risk sub-regions within the risk integration area; nor Sd represents the sum of the areas of normal sub-regions within the risk integration area; Sd represents the compensation unit area; ST represents the sum of the areas of normal sub-regions within the risk integration area. n∈N The slope geological data stability assessment value is the risk sub-region numbered n in the risk sub-region set N within the risk integration area; is the mean value of the slope geological data stability assessment value of the normal sub-region in the risk integration area; N is the set of numbers of the risk sub-regions in the risk integration area.

[0008] Furthermore, the average historical slope geological data stability assessment values ​​of each sub-region of the target operation area are retrieved from the database, and the absolute value of the difference between these values ​​and the average stability assessment values ​​of the current target operation area's slope geological data is analyzed. By analyzing the area proportion of the risk integration zone within the target operation area, combined with the slope geological stability fluctuation data of the risk integration zone in the current target operation area's virtual model, a comprehensive analysis of abnormal slope geological data fluctuations in the current target operation area is conducted. The calculation formula is as follows: ; Wherein, Yt is the abnormal fluctuation index of the comprehensive slope geological data of the target operation area; SY is the area of ​​the risk integration area; SA is the area of ​​the target operation area; The average stability assessment value of slope geological data for each sub-region within the target operation area; R represents the average stability assessment value of historical slope geological data for each sub-region of the target operation area; R is the compensation value. Based on the analysis of abnormal fluctuations in the comprehensive slope geological data of the current target work area, it is determined whether there are any abnormalities in the slope geological data of the current target work area. If it is determined to be abnormal, the risk integration area in the current target work area is fed back to the management terminal as an abnormal area; otherwise, it is determined to be normal, and a risk warning is issued for the risk integration area in the current target work area. Specifically, by setting an abnormal fluctuation threshold, when the abnormal fluctuation analysis data of the comprehensive slope geological data of the target work area exceeds the threshold, it is determined to be an abnormal state; otherwise, it is determined to be normal. An intelligent management system for geological data includes a positioning sensing module, a simulation construction module, a fluctuation data evaluation module, and an anomaly judgment module. The positioning and sensing module locates the target work area and constructs a real-time data sensing system to collect slope geological data of the target work area. It then processes the collected data with positioning tags and constructs a positioning time series set. The simulation construction module uses a simulation model and imports the positioning time series set corresponding to the target work area into the model to perform real-time scene simulation of the target work area, constructing a scene simulation model of the target work area and dividing the scene simulation model into local sub-regions. The fluctuation data assessment module performs slope geological stability assessment and analysis on each sub-region based on the division results. Based on the stability assessment results of each sub-region, it determines risk sub-regions and, based on the risk sub-regions, determines risk integration areas within the target work area. It analyzes the slope geological stability fluctuation data of the risk integration areas. The anomaly judgment module combines historical slope geological data of the target work area with comparative analysis of the current target work area to determine and report the abnormal state of the slope geological data in the current target work area.

[0009] Furthermore, the positioning sensing module includes a regional positioning unit and a data sensing and processing unit; The area positioning unit performs positioning operations based on the coordinate positioning method and the coordinate data of the target work area. The data perception processing unit constructs a real-time data perception system to collect slope geological data of the target work area. The data perception system includes a scene 3D data acquisition subsystem and a slope data acquisition subsystem. The 3D data acquisition subsystem is used to collect 3D data of the target work area, and the slope data acquisition subsystem is used to collect slope geological data of the target work area. After the data perception system completes data acquisition, it labels the collected data with corresponding positioning data to construct positioning time series data, and constructs a positioning time series set according to the time sequence. The positioning time series set includes a 3D data positioning time series set and a slope geological data positioning time series set.

[0010] Furthermore, the simulation construction module includes a simulation model building unit and a sub-region division unit; the simulation model building unit performs corresponding scene space simulation construction based on the three-dimensional data positioning time series set collected in the target operation area, and outputs a virtual model of the target operation area; based on the virtual model of the target operation area, the real-time collected slope geological data of each coordinate point in the slope geological data positioning time series set collected in the actual target operation area scene is updated and an update log is recorded. The sub-region division unit divides the virtual model of the target operation area into local sub-regions by gridding the virtual model of the target operation area, and assigns labels to each sub-region according to the division results. Based on the gridding of the local sub-regions of the virtual model of the target operation area, the slope geological data location time series collected in the target operation area is divided into corresponding sub-regions in a coordinated manner to construct a slope geological data location time series subset for each sub-region.

[0011] Furthermore, the volatility data assessment module includes a sub-regional data assessment unit and a risk area integrated analysis unit; The sub-region data evaluation unit performs slope geological data stability assessment and analysis on each sub-region based on the local sub-region division results of the virtual model of the target operation area. In the virtual model of the target operation area, each sub-region is located using sub-region labels, and the slope geological data location time series set at each coordinate point in the corresponding sub-region is retrieved based on the location results. Based on the slope geological data location time series set in the corresponding sub-region, environmental features at each coordinate point are classified and identified to determine the area proportion of different environmental features in the corresponding sub-region. Stability assessment index analysis is performed on different environmental features in each sub-region, and the slope geological data stability of the sub-region is assessed and analyzed in conjunction with the area proportion of different environmental features in the corresponding sub-region. Based on the assessment and analysis data of slope geological data stability for each sub-region, reference data for slope geological data stability in the sub-region is determined from historical data through the database, and comparative analysis is performed to identify risky sub-regions. The risk area integration and analysis unit, within the virtual model of the target work area, explicitly labels each risk sub-region number based on the risk judgment and analysis results of each sub-region, and integrates it with its adjacent sub-regions, using any risk sub-region as the starting point. The integration process involves connecting the midpoints of the two risk sub-regions if one is also a risk sub-region, and then proceeding to the next adjacent sub-region for further analysis; conversely, if the adjacent sub-region is a normal sub-region, the process continues with the next adjacent sub-region. After integrating all risk sub-regions, the area formed by connecting the midpoints of each risk sub-region is designated as the risk integration area. Slope geological stability fluctuation data analysis is performed on the risk integration area in the virtual model of the target work area, combining the stability assessment data of each risk sub-region with the stability assessment data of the normal sub-regions within the risk integration area for analysis and calculation. Furthermore, the anomaly assessment module includes a regional data anomaly judgment unit and a status feedback unit. The regional data anomaly judgment unit retrieves the average historical slope geological data stability assessment value of each sub-region of the target operation area from the database, and analyzes the absolute value of the difference between the average slope geological data stability assessment value of each sub-region of the current target operation area and the average value of the current slope geological data stability assessment value of each sub-region of the target operation area. By analyzing the area ratio of the risk integration area in the target operation area and combining the slope geological stability fluctuation data of the risk integration area in the virtual model of the current target operation area, a comprehensive slope geological data anomaly fluctuation analysis is performed on the current target operation area. The status feedback unit determines whether there is an abnormal state in the slope geological data of the current target operation area based on the abnormal fluctuation status analysis data of the comprehensive slope geological data of the current target operation area. If it is determined to be abnormal, the risk integration area in the current target operation area is fed back to the management terminal as an abnormal area; otherwise, it is determined to be normal, and a risk warning is issued for the risk integration area in the current target operation area.

[0012] Compared with the prior art, the beneficial effects of the present invention are: This invention combines a positioning system, a data sensing system, a simulation system, and an intelligent analysis system to achieve remote, intelligent, and safe monitoring and risk analysis and early warning of slope geological data in the work area. It classifies and identifies environmental characteristics in the work area and performs stability assessments based on the corresponding collected slope geological data. Risk levels are determined through stability assessments of sub-regional slope geological data, and fluctuations in slope geological data are analyzed by integrating risk sub-regions to identify abnormal fluctuations in the work area. This invention improves the automation and intelligence level of traditional manual inspections by refining and integrating progressive anomaly analysis of local areas within the work area, compensating for the early warning lag of traditional methods, and achieving in-depth mining and analysis of large volumes of slope geological data. To a certain extent, it meets the needs of modern engineering for slope geological data safety management. Attached Figure Description

[0013] Figure 1 This is a schematic diagram of the structure of an intelligent management system for geological data according to the present invention; Figure 2 This is a flowchart illustrating an intelligent management method for geological data according to the present invention. Detailed Implementation

[0014] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0015] Example 1:

[0016] like Figure 1 As shown, the present invention provides a technical solution: An intelligent management system for geological data, wherein the system includes a positioning and sensing module, a simulation construction module, a fluctuation data evaluation module, and an anomaly judgment module; The system comprises the following modules: a positioning and perception module, a real-time data perception system, and a simulation construction module. The positioning and perception module locates the target work area and collects slope geological data. It then processes the collected data with positioning tags and constructs a positioning time series set. The simulation construction module uses a simulation model and imports the positioning time series set corresponding to the target work area into the model. It performs real-time scene simulation of the target work area, constructs a scene simulation model, and divides the scene simulation model into local sub-regions. The fluctuation data assessment module performs slope geological stability assessment and analysis on each sub-region based on the division results. Based on the slope geological stability assessment results of each sub-region, it determines risk sub-regions and, based on these risk sub-regions, determines risk integration areas within the target work area. It analyzes the slope geological stability fluctuation data in the risk integration areas. Finally, the anomaly judgment module combines historical slope geological data of the target work area with comparative analysis of the current target work area to determine and report any abnormal states of the slope geological data in the current target work area.

[0017] Furthermore, the positioning and sensing module includes a regional positioning unit and a data sensing and processing unit; The area positioning unit performs positioning operations based on the coordinate positioning method and the coordinate data of the target work area; The data perception and processing unit constructs a real-time data perception system to collect slope geological data of the target work area. The data perception system includes a scene 3D data acquisition subsystem and a slope data acquisition subsystem. The 3D data acquisition subsystem is used to collect 3D data of the target work area, and the slope data acquisition subsystem is used to collect slope geological data of the target work area. After the data perception system completes data acquisition, it labels the acquired data with corresponding positioning data to construct positioning time series data, and constructs a positioning time series set according to the time sequence. The positioning time series set includes a 3D data positioning time series set and a slope geological data positioning time series set.

[0018] Furthermore, the simulation construction module includes a simulation model building unit and a sub-region division unit; The simulation model building unit performs corresponding scene space simulation building based on the three-dimensional data positioning time series collected in the target operation area, and outputs a virtual model of the target operation area; based on the virtual model of the target operation area, the real-time collected slope geological data of each coordinate point in the positioning time series of the actual target operation area scene is updated and the update log is recorded. The sub-region division unit divides the virtual model of the target operation area into local sub-regions by gridding the virtual model of the target operation area, and assigns labels to each sub-region according to the division results. Based on the gridding of the local sub-regions of the virtual model of the target operation area, the slope geological data location time series collected in the target operation area is divided into corresponding sub-regions in a coordinated manner to construct a slope geological data location time series subset for each sub-region.

[0019] Furthermore, the volatility data assessment module includes a sub-regional data assessment unit and a risk area integrated analysis unit; The sub-region data evaluation unit performs slope geological data stability assessment and analysis on each sub-region based on the local sub-region division results of the virtual model of the target operation area. Within the virtual model, each sub-region is located using sub-region labels, and the location time series of slope geological data at each coordinate point within the corresponding sub-region is retrieved based on the location results. Based on the location time series of slope geological data in the corresponding sub-region, environmental features at each coordinate point are classified and identified to determine the area proportion of different environmental features within the corresponding sub-region. Stability assessment index analysis is performed on different environmental features within each sub-region, and the slope geological data stability of the sub-region is assessed and analyzed in conjunction with the area proportion of different environmental features within the corresponding sub-region. Based on the assessment and analysis data of slope geological data stability for each sub-region, historical reference data for sub-region slope geological data stability is determined through a database and compared and analyzed. The process involves identifying risk sub-regions. Within the virtual model of the target work area, the risk sub-region integration analysis unit explicitly labels each risk sub-region with its assigned number based on the risk assessment analysis results. It then integrates and judges each sub-region with its adjacent sub-regions, starting from any risk sub-region. The integration process involves connecting the midpoints of the two risk sub-regions if one is also a risk sub-region, and continuing to the next adjacent sub-region for further assessment. Conversely, if the adjacent sub-region is a normal sub-region, the process continues to the next adjacent sub-region. After integrating and judging all risk sub-regions, the area formed by connecting the midpoints of each risk sub-region is recorded as the risk integration region. Slope geological stability fluctuation data analysis is then performed on the risk integration region within the virtual model of the target work area, combining the stability assessment analysis data of each risk sub-region with the stability assessment analysis data of the normal sub-regions within the risk integration region for analysis and calculation.

[0020] Furthermore, the anomaly assessment module includes a regional data anomaly assessment unit and a status feedback unit; The regional data anomaly judgment unit retrieves the average historical slope geological data stability assessment values ​​of each sub-region of the target operation area from the database, and analyzes the absolute value of the difference between the average slope geological data stability assessment values ​​of each sub-region of the current target operation area and the average slope geological data stability assessment values ​​of the current target operation area. By analyzing the area ratio of the risk integration area in the target operation area and combining the slope geological stability fluctuation data of the risk integration area in the virtual model of the current target operation area, a comprehensive slope geological data anomaly fluctuation analysis is performed on the current target operation area. The status feedback unit analyzes the abnormal fluctuations in the comprehensive slope geological data of the current target operation area to determine whether there are any abnormalities in the slope geological data of the current target operation area. If it is determined to be abnormal, the risk integration area in the current target operation area is fed back to the management terminal as an abnormal area; otherwise, it is determined to be normal, and a risk warning is issued for the risk integration area in the current target operation area. like Figure 2 As shown, the present invention provides another technical solution: An intelligent management method for geological data, comprising the following steps: By locating the target work area and constructing a real-time data perception system to collect slope geological data of the target work area, the collected data is processed with location tags and a location time series set is constructed. Using a simulation model, the location time series set corresponding to the target work area is imported into the model to conduct real-time scene simulation of the target work area and construct a scene simulation model of the target work area. By dividing the scene simulation model into local sub-regions, slope geological stability assessment and analysis are performed on each sub-region according to the division results. Based on the stability assessment results of each sub-region, risk sub-regions are determined, and risk integration areas within the target work area are determined based on the risk sub-regions. The slope geological stability fluctuation data of the risk integration area is analyzed, and combined with the historical slope geological data of the target work area, a comparative analysis is performed on the current target work area to determine the abnormal state of the slope geological data in the current target work area.

[0021] Furthermore, locating the target work area involves using a coordinate positioning method combined with the coordinate data of the target work area; the coordinate positioning method is satellite positioning, which can be GPS positioning or BeiDou positioning; the coordinate data of the target work area is stored in a database and can be retrieved by accessing the database. The data perception system includes a scene 3D data acquisition subsystem and a slope data acquisition subsystem. The 3D data acquisition subsystem collects 3D data of the target work area, while the slope data acquisition subsystem collects slope geological data of the target work area. The 3D data acquisition of the target work area involves using a remote sensing drone to identify environmental features of the scene and generating 3D cloud points for each feature based on the identification results. Environmental features include mountains, rock strata, soil layers, and water quality. Slope geological data includes topographic data, soil and rock condition data, and hydrological data. Topographic data includes slope height and slope angle; soil and rock condition data includes unit weight, density, and water content; and hydrological data includes groundwater level and pore water pressure. After the data sensing system completes data acquisition, it labels the acquired data with corresponding location data to construct location time series data, and constructs a location time series set according to the time sequence; the location time series set includes a 3D data location time series set and a slope geological data location time series set; the location data includes the coordinate data and acquisition time data of a certain acquisition point in the corresponding scene.

[0022] Furthermore, the simulation model constructs a corresponding scene space simulation based on the three-dimensional data positioning time series collected within the target work area, outputting a virtual model of the target work area. Within this virtual model, real-time slope geological data at each coordinate point in the slope geological data positioning time series collected from the actual target work area scene is used for updating and an update log is recorded. During the construction of the simulation model for the target work area, three-dimensional simulation is performed based on the environmental characteristics of each coordinate point in the positioning time series to recreate the actual target work area scene. Based on the output virtual model of the target operation area, the virtual model of the target operation area is divided into local sub-regions by gridding, and each sub-region is labeled and assigned a value according to the division result. The local sub-region division method is to divide the grid based on the smallest area monitored by the UAV in the target operation area within a unit period. Based on the local sub-region gridding of the virtual model of the target operation area, the slope geological data location time series collected in the target operation area is divided into corresponding sub-regions in a unified manner to construct a slope geological data location time series subset for each sub-region.

[0023] Furthermore, based on the local sub-region division results of the virtual model of the target operation area, slope geological data stability assessment and analysis are performed on each sub-region. The specific steps are as follows: S1. In the virtual model of the target work area, each sub-region is located and determined by sub-region labels, and the slope geological data location time series set at each coordinate point in the corresponding sub-region is retrieved according to the location results. S2. Based on the location time series set of slope geological data in the corresponding sub-region, classify and identify the environmental features at each coordinate point to determine the area proportion of different environmental features in the corresponding sub-region. S3. Stability assessment index analysis is performed on different environmental characteristics within each sub-region. Based on the area proportion of different environmental characteristics within the corresponding sub-region, the stability of the slope geological data of the sub-region is assessed and analyzed. The calculation is as follows: ; Among them, ST n S represents the slope geological data stability assessment value for the corresponding sub-region n; n S represents the area of ​​the subregion with the corresponding number n; m,n α represents the area of ​​the environmental feature numbered m in the corresponding subregion n; m,n This represents the average stability assessment value of environmental feature m in subregion n. The stability assessment values ​​of different environmental features are obtained by analyzing the collected geological data of the corresponding slope. n is the subregion number; m is the environmental feature number; i is the number of environmental features. The average stability assessment value of the corresponding environmental feature is obtained by calculating the average stability assessment values ​​of the environmental features at each coordinate point within the area of ​​the same environmental feature in the corresponding subregion. In this embodiment, if the environmental features are rock strata and soil layers, then the stability assessment value of the environmental features such as rock strata is calculated as follows: ;where α o,n v represents the stability assessment value of the corresponding rock strata environment characteristics in the corresponding sub-region numbered n; pm,z v represents the elastic longitudinal wave velocity of the rock mass at coordinate point z in the corresponding subregion n; pr The elastic longitudinal wave velocity of the rock mass is used as a reference to the environmental characteristics of the rock strata; the stability assessment value of the soil layer is then calculated as follows. ; where α k,n c represents the stability assessment value of the corresponding soil layer environmental characteristics in the corresponding sub-region numbered n; z The cohesion of the soil layer at coordinate point z in the corresponding subregion n on the sliding surface; z w represents the sliding length of the soil layer at coordinate point z in the corresponding subregion n; z β represents the self-weight of the soil layer at coordinate point z in the corresponding sub-region numbered n; z γ is the dip angle of the slip surface of the soil layer at coordinate point z in the corresponding subregion numbered n; zS4. Based on the stability assessment data of the slope geological data of each sub-region, determine the reference data of the slope geological data stability of the sub-region in the historical data through the database, and conduct comparative analysis to determine the risk sub-region; wherein the reference data of the slope geological data stability of the sub-region in the historical data is used as the comparison value, the comparison error is determined to construct the comparison interval, if the current sub-region slope geological data stability assessment value is within the comparison interval, it is judged as a normal sub-region; otherwise, it is judged as a risk sub-region. In the virtual model of the target work area, based on the risk assessment and analysis results of each sub-area, the risk sub-area numbers are explicitly marked, and any risk sub-area is used as the starting point for assessment and integration with its adjacent sub-areas. The assessment and integration process is as follows: if the adjacent sub-area of ​​a risk sub-area is also a risk sub-area, the midpoint of the two risk sub-areas is connected, and the assessment continues to the next adjacent sub-area; otherwise, if the adjacent sub-area of ​​a risk sub-area is a normal sub-area, the assessment continues to the next adjacent sub-area. When the assessment and integration of all risk sub-areas is completed, the area formed by connecting the midpoints of each risk sub-area is recorded as the risk integration area. The risk integration region comprises the area of ​​risk sub-regions and the area of ​​the sub-regions enclosed by lines connecting the points of the risk sub-regions. When risk sub-regions are not consecutively adjacent, the area constructed by the lines connecting their points will include normal sub-regions, and the normal sub-regions enclosed by the risk sub-regions will be affected by the risk. Therefore, the risk sub-regions and the surrounding normal sub-regions are integrated into the risk integration region. Slope geological stability fluctuation data analysis is performed on the risk integration region in the virtual model of the target operation area. This analysis combines the stability assessment data of each risk sub-region and the stability assessment data of the normal sub-regions within the risk integration region for calculation. The calculation formula is as follows: Where Dt is the fluctuation value of the geological stability of the slope in the risk integration area; S abn S represents the sum of the areas of risk sub-regions within the risk integration area; nor Sd represents the sum of the areas of normal sub-regions within the risk integration area; Sd represents the compensation unit area; ST represents the sum of the areas of normal sub-regions within the risk integration area. n∈N The slope geological data stability assessment value is the risk sub-region numbered n in the risk sub-region set N within the risk integration area; is the mean value of the slope geological data stability assessment value of the normal sub-region in the risk integration area; N is the set of numbers of the risk sub-regions in the risk integration area.

[0024] Furthermore, the average historical slope geological data stability assessment values ​​of each sub-region of the target operation area are retrieved from the database, and the absolute value of the difference between these values ​​and the average stability assessment values ​​of the current target operation area's slope geological data is analyzed. By analyzing the area proportion of the risk integration zone within the target operation area, combined with the slope geological stability fluctuation data of the risk integration zone in the current target operation area's virtual model, a comprehensive analysis of abnormal slope geological data fluctuations in the current target operation area is conducted. The calculation formula is as follows: Where Yt is the abnormal fluctuation index of the comprehensive slope geological data of the target operation area; SY is the area of ​​the risk integration area; SA is the area of ​​the target operation area; The average stability assessment value of slope geological data for each sub-region within the target operation area; R represents the average stability assessment value of historical slope geological data for each sub-region of the target operation area; R is the compensation value. Based on the analysis data of abnormal fluctuations in the comprehensive slope geological data of the current target operation area, it is determined whether there are any abnormalities in the slope geological data of the current target operation area. If it is determined to be abnormal, the risk integration area in the current target operation area is fed back to the management terminal as an abnormal area; otherwise, it is determined to be normal, and a risk warning is issued for the risk integration area in the current target operation area. In particular, by setting an abnormal fluctuation threshold, when the abnormal fluctuation data of the comprehensive slope geological data of the target operation area exceeds the threshold, it is determined to be an abnormal state; otherwise, it is determined to be normal.

[0025] It will be apparent to those skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered in all respects as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the present invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

Claims

1. An intelligent management method for geological data, characterized in that: The method includes the following steps: By locating the target work area and building a real-time data perception system, slope geological data of the target work area is collected, the collected data is processed with location tags, and a location time series set is constructed. Using a simulation model and importing the location time series set corresponding to the target work area into the model, a real-time scene simulation of the target work area is performed to construct a scene simulation model of the target work area. By dividing the scene simulation model into local sub-regions, slope geological stability assessment and analysis are performed on each sub-region according to the division results. Based on the slope geological stability assessment results of each sub-region, risk sub-regions are determined, and risk integration areas within the target work area are determined based on the risk sub-regions. The slope geological stability fluctuation data of the risk integration area are analyzed, and combined with the historical slope geological data of the target work area, a comparative analysis is performed on the current target work area to determine the abnormal state of the slope geological data in the current target work area.

2. The intelligent management method for geological data according to claim 1, characterized in that: The target work area is located by combining coordinate positioning method with the coordinate data of the target work area. The data perception system includes a scene 3D data acquisition subsystem and a slope data acquisition subsystem; The three-dimensional data acquisition subsystem is used to acquire three-dimensional data of the target work area; the slope data acquisition subsystem is used to acquire slope geological data of the target work area. After the data sensing system completes data acquisition, it labels the acquired data with corresponding location data to construct location time series data, and constructs a location time series set according to the time sequence; the location time series set includes a three-dimensional data location time series set and a slope geological data location time series set.

3. The intelligent management method for geological data according to claim 2, characterized in that: The simulation model is built based on the three-dimensional data positioning time series collected in the target work area to simulate the corresponding scene space and output a virtual model of the target work area. Based on the virtual model of the target work area, the slope geological data of each coordinate point in the positioning time series collected in the actual target work area scene is updated and the update log is recorded. Based on the output virtual model of the target work area, the virtual model of the target work area is divided into local sub-regions by gridding, and each sub-region is labeled and assigned a value according to the division result. Based on the local sub-region gridding of the virtual model of the target operation area, the slope geological data location time series collected in the target operation area is divided into corresponding sub-regions in a coordinated manner to construct a slope geological data location time series subset for each sub-region.

4. The intelligent management method for geological data according to claim 3, characterized in that: Based on the local sub-region division results of the virtual model of the target operation area, slope geological data stability assessment and analysis are performed for each sub-region. The specific steps are as follows: S1. In the virtual model of the target work area, each sub-region is located and determined by sub-region labels, and the slope geological data location time series set at each coordinate point in the corresponding sub-region is retrieved according to the location results. S2. Based on the location time series set of slope geological data in the corresponding sub-region, classify and identify the environmental features at each coordinate point to determine the area proportion of different environmental features in the corresponding sub-region. S3. Conduct stability assessment index analysis on different environmental features in the sub-regions respectively, and combine the area proportion of different environmental features in the corresponding sub-regions to assess and analyze the stability of the slope geological data of the sub-regions. S4. Based on the assessment and analysis data of slope geological data stability for each sub-region, determine the reference data for slope geological data stability in the historical data of the sub-region through the database, and conduct comparative analysis to identify risk sub-regions. In the virtual model of the target work area, based on the risk assessment and analysis results of each sub-area, the risk sub-area numbers are explicitly marked, and any risk sub-area is used as the starting point for judgment and integration with its adjacent sub-areas. The judgment and integration process is as follows: if the adjacent sub-area of ​​a risk sub-area is also a risk sub-area, the midpoint of the two risk sub-areas is connected, and the judgment continues to the next adjacent sub-area; otherwise, if the adjacent sub-area of ​​a risk sub-area is a normal sub-area, the judgment continues to the next adjacent sub-area. After the judgment and integration of all risk sub-areas is completed, the area formed by the line connecting the midpoints of each risk sub-area is recorded as the risk integration area. Slope geological stability fluctuation data analysis is performed on the risk integration area in the virtual model of the target operation area. The analysis and calculation are combined with the stability assessment data of each risk sub-region and the stability assessment data of the normal sub-region in the risk integration area.

5. The intelligent management method for geological data according to claim 4, characterized in that: Retrieve the average historical slope geological data stability assessment values ​​of each sub-region of the target operation area from the database, and analyze the absolute value of the difference between the average slope geological data stability assessment values ​​of each sub-region of the current target operation area and the average value of the current slope geological data stability assessment values ​​of each sub-region of the target operation area. By analyzing the area ratio of the risk integration area in the target operation area and combining the slope geological stability fluctuation data of the risk integration area in the virtual model of the current target operation area, conduct a comprehensive slope geological data abnormal fluctuation analysis of the current target operation area. Based on the analysis data of abnormal fluctuations in the comprehensive slope geological data of the current target operation area, determine whether there are any abnormalities in the slope geological data of the current target operation area. If an anomaly is detected, the risk integration area in the current target operation area will be reported back to the management end as an anomaly area. Conversely, if the condition is abnormal, it is considered normal, and a risk warning is issued for the risk integration area in the current target operation area.

6. An intelligent management system for geological data, characterized in that: The system includes a positioning and sensing module, a simulation construction module, a fluctuation data evaluation module, and an anomaly judgment module. The positioning and sensing module locates the target work area and constructs a real-time data sensing system to collect slope geological data of the target work area. It then processes the collected data with positioning tags and constructs a positioning time series set. The simulation construction module uses a simulation model and imports the positioning time series set corresponding to the target work area into the model to perform real-time scene simulation of the target work area, constructing a scene simulation model of the target work area and dividing the scene simulation model into local sub-regions. The fluctuation data assessment module performs slope geological stability assessment and analysis on each sub-region based on the division results. Based on the stability assessment results of each sub-region, it determines risk sub-regions and, based on the risk sub-regions, determines the risk integration area within the target work area. Analyze slope geological stability fluctuation data in the risk integration area; The anomaly assessment module combines historical slope geological data of the target work area to conduct comparative analysis of the current target work area, determine and report the abnormal status of the slope geological data in the current target work area.

7. The intelligent management system for geological data according to claim 6, characterized in that: The positioning sensing module includes a regional positioning unit and a data sensing and processing unit. The area positioning unit performs positioning operations based on the coordinate positioning method and the coordinate data of the target work area. The data perception and processing unit constructs a real-time data perception system to collect slope geological data of the target operation area; the data perception system includes a scene 3D data acquisition subsystem and a slope data acquisition subsystem. The three-dimensional data acquisition subsystem is used to acquire three-dimensional data of the target work area; the slope data acquisition subsystem is used to acquire slope geological data of the target work area; after the data sensing system completes data acquisition, it labels the acquired data with corresponding positioning data to construct positioning time series data, and constructs a positioning time series set according to the time sequence; the positioning time series set includes a three-dimensional data positioning time series set and a slope geological data positioning time series set.

8. The intelligent management system for geological data according to claim 7, characterized in that: The simulation construction module includes a simulation model building unit and a sub-region division unit; The simulation model building unit performs corresponding scene space simulation building based on the three-dimensional data positioning time series collected in the target operation area, and outputs a virtual model of the target operation area; based on the virtual model of the target operation area, the real-time collected slope geological data of each coordinate point in the slope geological data positioning time series collected in the actual target operation area scene is updated and the update log is recorded. The sub-region division unit divides the virtual model of the target work area into local sub-regions based on the output virtual model of the target work area, and assigns labels to each sub-region based on the division results. Based on the local sub-region gridding of the virtual model of the target operation area, the slope geological data location time series collected in the target operation area is divided into corresponding sub-regions in a coordinated manner to construct a slope geological data location time series subset for each sub-region.

9. An intelligent management system for geological data according to claim 8, characterized in that: The volatility data assessment module includes a sub-regional data assessment unit and a risk region integrated analysis unit. The sub-region data evaluation unit performs slope geological data stability assessment and analysis on each sub-region based on the local sub-region division results of the virtual model of the target operation area. In the virtual model of the target operation area, each sub-region is located using sub-region labels, and the slope geological data location time series set at each coordinate point in the corresponding sub-region is retrieved based on the location results. Based on the slope geological data location time series set in the corresponding sub-region, environmental features at each coordinate point are classified and identified to determine the area proportion of different environmental features in the corresponding sub-region. Stability assessment index analysis is performed on different environmental features in each sub-region, and the slope geological data stability of the sub-region is assessed and analyzed in conjunction with the area proportion of different environmental features in the corresponding sub-region. Based on the assessment and analysis data of slope geological data stability for each sub-region, reference data for slope geological data stability in the sub-region is determined from historical data through the database, and comparative analysis is performed to identify risky sub-regions. The risk area integration and analysis unit, within the virtual model of the target work area, explicitly labels each risk sub-region number based on the risk judgment and analysis results of each sub-region, and integrates and judges each sub-region with its adjacent sub-regions, using any risk sub-region as the starting point. The integration and judgment process involves connecting the midpoints of the two risk sub-regions if the adjacent sub-region is also a risk sub-region, and then proceeding to the next adjacent sub-region for further judgment. Conversely, if the adjacent sub-region is a normal sub-region, the process continues to the next adjacent sub-region for further judgment. After completing the integration and judgment of all risk sub-regions, the area formed by connecting the midpoints of each risk sub-region is recorded as the risk integration area. Slope geological stability fluctuation data analysis is performed on the risk integration area in the virtual model of the target operation area. The analysis and calculation are combined with the stability assessment data of each risk sub-region and the stability assessment data of the normal sub-region in the risk integration area.

10. An intelligent management system for geological data according to claim 9, characterized in that: The anomaly assessment module includes a regional data anomaly judgment unit and a status feedback unit; The regional data anomaly judgment unit retrieves the average historical slope geological data stability assessment value of each sub-region of the target operation area from the database, and analyzes the absolute value of the difference between the average slope geological data stability assessment value of each sub-region of the current target operation area and the average value of the current slope geological data stability assessment value of each sub-region of the target operation area. By analyzing the area ratio of the risk integration area in the target operation area and combining the slope geological stability fluctuation data of the risk integration area in the virtual model of the current target operation area, a comprehensive slope geological data anomaly fluctuation analysis is performed on the current target operation area. The status feedback unit determines whether there is an abnormal state in the slope geological data of the current target operation area based on the abnormal fluctuation status analysis data of the comprehensive slope geological data of the current target operation area. If an anomaly is detected, the risk integration area in the current target operation area will be reported back to the management end as an anomaly area. Conversely, if the condition is abnormal, it is considered normal, and a risk warning is issued for the risk integration area in the current target operation area.

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