A mining method considering the dip angle of gold ore bodies

Abstract

This invention discloses a mining method considering the dip angle of a gold ore body, belonging to the field of mineral resource exploration. The mining method considering the dip angle of a gold ore body includes: Step 1: Constructing a mine simulation model; Step 2: Obtaining the reserves of the ore body and designing a gold mining plan; Step 3: Simulating the gold mining process; Step 4: Obtaining the dip angle data of the gold ore body; Step 5: Obtaining the optimal mining conditions; Step 6: Mining using the optimal mining conditions. This invention solves the problem that existing technologies, due to the complex environment of the mine and the large number of parameters considered, cannot accurately reflect the actual situation during blasting, thus affecting the efficiency of mining operations. This invention can significantly improve mining efficiency and adaptability, reduce mining costs, increase resource utilization, and can promptly detect potential safety hazards, ensuring the safe conduct of mining operations and providing strong support for the sustainable development of gold mining.

Description

Technical Field

[0001] This invention relates to the field of mineral resource exploration technology, specifically a mining method that takes into account the dip angle of a gold ore body. Background Technology

[0002] A gold mine refers to gold ore or a gold deposit. Gold ore is a mineral aggregate containing sufficient gold for industrial use. A gold mine is a place where gold is obtained through mining operations; it is a large-scale accumulation of industrially usable gold ore formed through mineralization. Gold deposits are complex and diverse in type.

[0003] Chinese patent CN111608660A discloses a mining method suitable for gold ore bodies with dip angles of 50°-55°. The method includes five steps: stope selection, mining sequence, pre-cutting, rock drilling and blasting, and stope ore extraction. This method enables mining operations in ore bodies with dip angles of 50°-55°. By selecting ore blocks of the required specifications as stopes, the stability of the stopes after establishment is ensured. Mining is carried out in a top-down sequence. Simultaneously, anchor bolts or pillars are used to support the goaf, enhancing its stability and making the ore body more stable. Expanded rock explosives are used as the main blasting material, and micro-differential blasting is achieved by skipping sections between rows within the same row, improving blasting accuracy and reducing the occurrence of collapses during blasting. This method is suitable for mining operations in ore bodies with dip angles of 50°-55°.

[0004] In practical use, the aforementioned patents involve mining operations through direct blasting. However, due to the complex environment of the mine and the large number of parameters to consider, the blasting process cannot accurately reflect the actual situation, thus affecting the efficiency of mining operations. Therefore, it does not meet the existing needs. To address this, we propose a mining method that considers the dip angle of the gold ore body. Summary of the Invention

[0005] The purpose of this invention is to provide a mining method that considers the dip angle of a gold ore body. By optimizing the mining scheme based on the dip angle variation, the mining scheme with the highest resource utilization efficiency can be selected. This method can significantly improve mining efficiency and adaptability, reduce mining costs, and increase resource utilization. By predicting the dip angle of the ore body, potential safety hazards can be detected in a timely manner, allowing for the implementation of corresponding safety measures to ensure the safe conduct of mining operations. This provides a strong guarantee for the sustainable development of gold mining and solves the problems mentioned in the background art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: a mining method considering the dip angle of a gold ore body, comprising the following steps:

[0007] Step 1: Collect and process mining data in real time, and build a mining simulation model based on the acquired data using the model generation module;

[0008] Step 2: Calculate resource reserves using the prediction module to obtain the reserves of the ore body and design a gold mining plan;

[0009] Step 3: Simulate the gold mining process on a mine simulation model based on the designed gold mining plan;

[0010] Step 4: Compare, analyze, and process the dip angle data of the ore body during the gold mining process to obtain the dip angle data of the gold ore body;

[0011] Step 5: Predict the dip angle of the ore body, and optimize the gold mining plan based on the predicted dip angle value to obtain the best mining conditions;

[0012] Step Six: Utilize optimal mining conditions for subsequent gold mining.

[0013] Preferably, the real-time acquisition and processing of mine data, and the construction of a mine simulation model using a model generation module based on the acquired data, includes:

[0014] Real-time data collection of geological features of ore bodies, topographic data, data on buildings and equipment in the mining area, and mining conditions data; and processing of the collected data.

[0015] Based on topographic data, a topographic model of the mining area is constructed; based on ore body geological feature data, a geological model of the mining area is constructed; and based on mining area building and equipment data, a model of buildings, bridges, roads, and equipment within the mining area is constructed.

[0016] The terrain model, geological body model, and models of buildings, bridges, roads and equipment in the mining area are integrated to form a complete mine simulation model. The integrated model is then optimized.

[0017] The processing of the collected data specifically includes:

[0018] Data cleaning: Converting collected data into a uniform format, and then processing outliers or erroneous data after conversion;

[0019] Data format conversion: Converting collected data into a unified format;

[0020] Abnormal data handling: Inspect and handle outlier or erroneous values ​​in the data.

[0021] Preferably, the prediction process of the prediction module specifically includes:

[0022] Resource reserves are calculated based on a mine simulation model using geometric methods, specifically the reserves of the ore body.

[0023] A gold mining plan is designed based on the reserves of the ore body. The gold mining plan includes the mining sequence, mining methods and equipment selection.

[0024] Based on the designed gold mine mining simulation model, the gold mining process is simulated on the mining simulation model, and the change of the dip angle of the ore body during the mining process is analyzed.

[0025] The simulated dip angle change data of the ore body was extracted and compared and processed to obtain the dip angle data of the gold ore body during the actual mining process;

[0026] A dip angle prediction model for the ore body is constructed. The dip angle data of the gold ore body during the actual mining process is input into the dip angle prediction model, and the predicted results of the dip angle change of the ore body are output.

[0027] The gold mining plan is optimized based on the predicted results of the ore body dip angle change, such as blasting parameters and transportation parameters.

[0028] Preferably, the resource reserves are calculated based on the mine simulation model using the geometric method, and the reserves of the ore body are calculated.

[0029] Extract ore body features and ore features from the geological feature data of the ore body. Based on the ore body features and ore features combined with the ore distribution characteristics, divide the mine simulation model into several blocks, calculate the resource reserves of each block and sum them up.

[0030] The cross-sectional map of the ore body is generated by using the ore body characteristics and ore characteristics in the block, and the ore body area and corresponding ore body thickness of the cross-sectional map are obtained.

[0031] The volume of the ore body is calculated using the area and thickness of the ore body in the cross-sectional diagram. The ore reserves are then calculated using the volume of the ore body and the average weight of the ore.

[0032] Preferably, the step of extracting dip angle data of the ore body during gold mining and performing comparative analysis and processing to obtain dip angle data of the gold ore body during actual mining specifically includes:

[0033] Dip angle monitoring points were set at different locations and depths in the mine simulation model to monitor changes in the ore body during the simulation process;

[0034] Extract the dip angle data of the ore body from the real-time monitoring data, and visualize the real-time monitoring data in the form of charts to obtain the data on the change of the dip angle of the ore body during the simulated mining process.

[0035] Preferably, the construction of the orebody dip angle prediction model specifically includes:

[0036] Obtain orebody dip data, which includes the geological characteristics of the orebody, mining conditions, and historical dip data;

[0037] The acquired tilt angle data is cleaned and normalized. After processing, the data is divided into training set and validation set.

[0038] A BP neural network model was selected and trained using a training dataset. During the training process, a genetic algorithm was used to optimize the neural network, resulting in a ore body dip angle prediction model.

[0039] The orebody dip angle prediction model was validated using a validation set, and its performance was evaluated using cross-validation.

[0040] Once the ore body dip angle prediction model is trained, the real-time collected data on the changes in the ore body dip angle is input into the model, and the predicted ore body dip angle value is output.

[0041] Preferably, the model generation module includes:

[0042] The construction module is used to construct topographic and geomorphological models of the mining area, geological body models, and models of buildings, bridges, roads, and equipment within the mining area based on topographic and geomorphological data, ore body geological feature data, and mining area building and equipment data, respectively.

[0043] The integration module is used to integrate terrain and landform models, geological body models, and models of buildings, bridges, roads, and equipment within the mining area;

[0044] The optimization module is used to remove feature variables that are not beneficial to the integrated mine simulation model through feature selection and dimensionality reduction.

[0045] Preferably, the prediction module includes:

[0046] The calculation module is used to calculate the reserves of the ore body and design a gold mining plan based on the reserves of the ore body.

[0047] The analysis module is used to simulate the gold mining process on a mining simulation model and analyze the changes in the dip angle of the ore body during the mining process.

[0048] The results output module is used to construct a ore body dip angle prediction model and obtain the predicted ore body dip angle value using the ore body dip angle prediction model.

[0049] Preferably, the analysis module includes:

[0050] The real-time monitoring data is classified according to the type, location and depth of the ore body, while abnormal or erroneous data points are removed.

[0051] By comparing dip angle data of different ore bodies, different regions, or different time periods, we can analyze the distribution pattern, trend of change, and formation mechanism of ore body dip angle. For example, we can compare the dip angle changes of the same ore body at different depths, or compare the dip angle characteristics of different ore bodies in the same geological structural zone.

[0052] The data from real-time monitoring is visualized using charts to obtain data on the changes in the dip angle of the ore body during the simulated mining process.

[0053] Compared with the prior art, the beneficial effects of the present invention are:

[0054] This invention simulates the mining process using a mine simulation model to obtain dip angle variation data of the ore body. It then uses this data to predict the dip angle variation value of the ore body and optimizes the mining plan based on the dip angle variation value. This allows for the selection of the mining plan with the highest resource utilization efficiency, significantly improving mining efficiency and adaptability, reducing mining costs, and increasing resource utilization. By predicting the ore body dip angle, potential safety hazards can be identified in a timely manner, enabling the implementation of corresponding safety measures and ensuring the safe operation of mining activities. This provides a strong guarantee for the sustainable development of gold mining. Attached Figure Description

[0055] Figure 1 This is a schematic diagram of the mining method of the present invention that takes into account the dip angle of the gold ore body;

[0056] Figure 2 This is a schematic diagram of a mining method module that takes into account the dip angle of a gold ore body according to the present invention. Detailed Implementation

[0057] 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. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0058] To address the issue that existing mining technologies, which rely on direct blasting for mining operations, often fail to accurately reflect the actual conditions due to the complex environment and numerous parameters in a mining site, thus impacting mining efficiency, please refer to [the relevant documentation / reference]. Figures 1-2 This embodiment provides the following technical solution:

[0059] A mining method taking into account the dip angle of a gold ore body includes the following steps:

[0060] Step 1: Collect and process mining data in real time, and build a mining simulation model based on the acquired data using the model generation module;

[0061] Step 2: The prediction module uses geometric methods to calculate resource reserves based on the mine simulation model, obtains the reserves of the ore body, and designs a gold mine mining plan.

[0062] Step 3: Simulate the gold mining process on a mine simulation model based on the designed gold mining plan;

[0063] Step 4: Extract dip angle data of the ore body during the gold mining process and perform comparative analysis and processing to obtain dip angle data of the gold ore body during the actual mining process;

[0064] Step 5: Predict the dip angle of the ore body, and optimize the gold mining plan based on the predicted dip angle value to obtain the best mining conditions;

[0065] Step Six: Utilize optimal mining conditions for subsequent gold mining.

[0066] Real-time acquisition and processing of mining data; construction of a mining simulation model based on the acquired data using a model generation module, including:

[0067] Real-time acquisition of geological feature data of ore bodies, topographic data, data on buildings and equipment in the mining area, and mining condition data of the mine. The acquired data is processed. Topographic data includes topographic maps and contour maps of the area where the mine is located. Data on buildings and equipment in the mining area includes design drawings, renderings, and real color photos of buildings, bridges, roads, and equipment in the mining area. Geological feature data of ore bodies includes ore body features, ore features, surrounding rock features, and structural features of the deposit. Ore body features include the shape, size, and occurrence of the ore body. Ore features include the material composition, structure, and quality of the ore.

[0068] Based on topographic data, a topographic model of the mining area is constructed; based on ore body geological feature data, a geological model of the mining area is constructed; and based on mining area building and equipment data, a model of buildings, bridges, roads, and equipment within the mining area is constructed.

[0069] The terrain model, geological body model, and models of buildings, bridges, roads, and equipment within the mining area are integrated to form a complete mine simulation model. The integrated model is then optimized by adjusting the model scale, correcting positional relationships, and adding detailed features to improve the model's accuracy and realism.

[0070] By constructing a mine simulation model to simulate the gold mining process, mining efficiency can be improved, resource utilization optimized, safety risks reduced, and technological innovation promoted. The simulation model can more intuitively demonstrate the mining effects at different orebody dip angles, and accurately analyze the spatial distribution characteristics of volumetric strain, temperature gradient, pore pressure gradient, fluid migration, and mineralization precipitation during the mineralization period. This provides a scientific basis for selecting the most suitable mining method. Especially when dealing with steeply dipping thin ore bodies, the mine simulation model can obtain dip angle variation data, and then use this data to predict the dip angle variation value. Based on the dip angle variation value, the mining plan can be optimized to select the mining scheme with the highest resource utilization efficiency. By simulating key parameters such as stress changes and rock mass stability during the mining process, potential safety hazards can be predicted, and corresponding preventive measures can be taken to ensure the safe conduct of mining operations.

[0071] In conclusion, simulating the gold mining process by constructing a mine simulation model has many benefits for mining methods that take into account the dip angle of the gold ore body. It can not only improve mining efficiency, optimize resource utilization, and reduce safety risks, but also promote the innovation and development of mining technology.

[0072] The collected data is processed, specifically including:

[0073] Data cleaning: Converting the collected data into a uniform format, and processing outliers or erroneous data after conversion to facilitate subsequent processing and ensure the accuracy and reliability of the data;

[0074] Data format conversion: Converting the collected data into a unified format to facilitate subsequent processing;

[0075] Outlier handling: Inspect and process outliers or erroneous data to ensure data accuracy and reliability.

[0076] The prediction process of the prediction module specifically includes:

[0077] Resource reserves are calculated based on a mine simulation model using geometric methods, specifically the reserves of the ore body.

[0078] A gold mining plan is designed based on the reserves of the ore body. The gold mining plan includes the mining sequence, mining methods and equipment selection.

[0079] Based on the designed gold mine mining simulation model, the gold mining process is simulated on the mining simulation model, and the change of the dip angle of the ore body during the mining process is analyzed.

[0080] The simulated dip angle change data of the ore body was extracted and compared and processed to obtain the dip angle data of the gold ore body during the actual mining process;

[0081] A dip angle prediction model for the ore body is constructed. The dip angle data of the gold ore body during the actual mining process is input into the dip angle prediction model, and the predicted results of the dip angle change of the ore body are output.

[0082] Based on the predicted results of the ore body dip angle change, the gold mining plan is optimized, such as blasting parameters and transportation parameters, in order to improve mining efficiency and economic benefits.

[0083] By training a orebody dip angle prediction model, it can quickly and accurately predict new orebody dip angle data based on existing data samples, greatly improving the efficiency and accuracy of gold mining. Through steps such as constructing a mine simulation model, conducting simulated mining tests, extracting and analyzing orebody dip angle data, and using intelligent algorithms to optimize and predict orebody dip angle, dip angle data of gold ore bodies in actual mining processes can be effectively obtained.

[0084] Resource reserves are calculated based on a mine simulation model using geometric methods, specifically the reserves of the ore body.

[0085] Extract ore body features and ore features from the geological feature data of the ore body. Based on the ore body features and ore features combined with the ore distribution characteristics, divide the mine simulation model into several blocks, calculate the resource reserves of each block and sum them up.

[0086] The cross-sectional map of the ore body is generated by using the ore body characteristics and ore characteristics in the block, and the ore body area and corresponding ore body thickness of the cross-sectional map are obtained.

[0087] The volume of the ore body is calculated using the area and thickness of the ore body in the cross-sectional diagram. The ore reserves are then calculated using the volume of the ore body and the average weight of the ore.

[0088] Dip angle data of the ore body during gold mining was extracted, analyzed, and processed to obtain dip angle data of the gold ore body during actual mining, specifically including:

[0089] Dip angle monitoring points were set at different locations and depths in the mine simulation model to monitor changes in the ore body during the simulation process;

[0090] Extract the dip angle data of the ore body from the real-time monitoring data, and visualize the real-time monitoring data in the form of charts to obtain the data on the change of the dip angle of the ore body during the simulated mining process.

[0091] By extracting the dip angle data of the ore body and conducting comparative analysis and processing, the dip angle data of the gold ore body during the actual mining process can be obtained, ensuring the accuracy and reliability of the data.

[0092] Constructing a dip angle prediction model for ore bodies, specifically including:

[0093] Obtain orebody dip data, which includes the geological characteristics of the orebody, mining conditions, and historical dip data;

[0094] The acquired tilt angle data is cleaned and normalized. After processing, the data is divided into training set and validation set.

[0095] The BP neural network model is selected and trained using the training dataset. During the training process, the neural network is optimized using a genetic algorithm to obtain the ore body dip angle prediction model, which can minimize the prediction error and thus improve the prediction ability of the neural network.

[0096] The orebody dip angle prediction model was validated using a validation set, and its performance was evaluated using cross-validation.

[0097] Once the ore body dip angle prediction model is trained, the real-time collected data on the changes in the ore body dip angle is input into the model, and the predicted ore body dip angle value is output, effectively improving the accuracy and reliability of ore body dip angle prediction.

[0098] Predicting the dip angle of ore bodies during gold mining can significantly improve mining efficiency and adaptability. Traditional gold mining methods often rely solely on experience or consider limited parameters, which can lead to poor adaptability in actual operations due to the complexity and variability of the mining environment. Predicting the dip angle allows for a more accurate understanding of the actual shape and distribution of the ore body, providing more reliable data support for selecting mining methods and improving mining accuracy and efficiency. During the mining process, predicting the dip angle enables more scientific planning of mining schemes, such as determining appropriate mining depths and sequences. Mining methods and other factors can optimize mining conditions, reduce mining costs, and improve resource utilization. Changes in the dip angle of the ore body can affect the safety of mining operations. Predicting the dip angle can help identify potential safety hazards, such as landslides and collapses, and allow for the implementation of appropriate safety measures to ensure the safe conduct of mining operations. Using an ore body dip angle prediction model can quickly and accurately predict the dip angle value, which not only improves data processing efficiency but also significantly enhances prediction accuracy. This provides more reliable technical support for the development of mining methods and provides a strong guarantee for the sustainable development of gold mining.

[0099] The model generation module includes:

[0100] The construction module is used to construct topographic and geomorphological models of the mining area, geological body models, and models of buildings, bridges, roads, and equipment within the mining area based on topographic and geomorphological data, ore body geological feature data, and mining area building and equipment data, respectively.

[0101] The integration module is used to integrate terrain and landform models, geological body models, and models of buildings, bridges, roads, and equipment within the mining area;

[0102] The optimization module is used to reduce the complexity of the integrated mine simulation model and improve its generalization ability by removing feature variables that are not beneficial to the model through feature selection and dimensionality reduction.

[0103] The prediction module includes:

[0104] The calculation module is used to calculate the reserves of the ore body and design a gold mining plan based on the reserves of the ore body.

[0105] The analysis module is used to simulate the gold mining process on a mining simulation model and analyze the changes in the dip angle of the ore body during the mining process.

[0106] The results output module is used to construct a ore body dip angle prediction model and obtain the predicted ore body dip angle value using the ore body dip angle prediction model.

[0107] The analysis module includes:

[0108] The real-time monitoring data is classified according to the type, location and depth of the ore body, while abnormal or erroneous data points are removed.

[0109] By comparing dip angle data of different ore bodies, different regions, or different time periods, we can analyze the distribution pattern, trend of change, and formation mechanism of ore body dip angle. For example, we can compare the dip angle changes of the same ore body at different depths, or compare the dip angle characteristics of different ore bodies in the same geological structural zone.

[0110] The data from real-time monitoring is visualized using charts to obtain data on the changes in the dip angle of the ore body during the simulated mining process.

[0111] In summary, the mining method of this invention, which considers the dip angle of a gold ore body, simulates the mining process using a mine simulation model to obtain dip angle variation data of the ore body. This data is then used to predict the dip angle variation value, and the mining scheme is optimized based on the dip angle variation value. This allows for the selection of the mining scheme with the highest resource utilization efficiency, significantly improving mining efficiency and adaptability, reducing mining costs, and increasing resource utilization. Changes in the dip angle of the ore body may affect the safety of mining operations. Predicting the dip angle can help identify potential safety hazards, such as landslides and collapses, allowing for the implementation of corresponding safety measures to ensure the safe conduct of mining operations. The ore body dip angle prediction model can quickly and accurately predict the dip angle value, not only improving data processing efficiency but also significantly enhancing prediction accuracy, thus providing a strong guarantee for the sustainable development of gold mining.

[0112] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0113] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention.

Claims

1. A mining method considering the dip angle of a gold ore body, characterized in that, Includes the following steps: Step 1: Collect and process mining data in real time, and build a mining simulation model based on the acquired data using the model generation module; Step 2: Calculate resource reserves using the prediction module to obtain the reserves of the ore body and design a gold mining plan; Step 3: Simulate the gold mining process on a mine simulation model based on the designed gold mining plan; Step 4: Compare, analyze, and process the dip angle data of the ore body during the gold mining process to obtain the dip angle data of the gold ore body; Step 5: Predict the dip angle of the ore body, and optimize the gold mining plan based on the predicted dip angle value to obtain the best mining conditions; Step Six: Utilize optimal mining conditions for subsequent gold mining.

2. The mining method considering the dip angle of a gold ore body according to claim 1, characterized in that: The process of real-time acquisition and processing of mining data, and the construction of a mining simulation model using a model generation module based on the acquired data, includes: Real-time data collection of geological features of ore bodies, topographic data, data on buildings and equipment in the mining area, and mining conditions data; and processing of the collected data. Based on topographic data, a topographic model of the mining area is constructed; based on ore body geological feature data, a geological model of the mining area is constructed; and based on mining area building and equipment data, a model of buildings, bridges, roads, and equipment within the mining area is constructed. The terrain model, geological body model, and models of buildings, bridges, roads and equipment in the mining area are integrated to form a complete mine simulation model. The integrated model is then optimized.

3. A mining method considering the dip angle of a gold ore body according to claim 2, characterized in that: The processing of the collected data specifically includes: Data cleaning: Converting collected data into a uniform format, and then processing outliers or erroneous data after conversion; Data format conversion: Converting collected data into a unified format; Abnormal data handling: Inspect and handle outlier or erroneous values ​​in the data.

4. A mining method considering the dip angle of a gold ore body according to claim 1, characterized in that: The prediction process of the prediction module specifically includes: Resource reserves are calculated based on a mine simulation model using geometric methods, specifically the reserves of the ore body. A gold mining plan is designed based on the reserves of the ore body. The gold mining plan includes the mining sequence, mining methods and equipment selection. Based on the designed gold mine mining simulation model, the gold mining process is simulated on the mining simulation model, and the change of the dip angle of the ore body during the mining process is analyzed. The simulated dip angle change data of the ore body was extracted and compared and processed to obtain the dip angle data of the gold ore body during the actual mining process; A dip angle prediction model for the ore body is constructed. The dip angle data of the gold ore body during the actual mining process is input into the dip angle prediction model, and the predicted results of the dip angle change of the ore body are output. The gold mining plan is optimized based on the predicted results of the ore body dip angle change, such as blasting parameters and transportation parameters.

5. A mining method considering the dip angle of a gold ore body according to claim 4, characterized in that: The method of using geometric figures to calculate resource reserves based on a mine simulation model is described, and the reserves of the ore body are calculated. Extract ore body features and ore features from the geological feature data of the ore body. Based on the ore body features and ore features combined with the ore distribution characteristics, divide the mine simulation model into several blocks, calculate the resource reserves of each block and sum them up. The cross-sectional map of the ore body is generated by using the ore body characteristics and ore characteristics in the block, and the ore body area and corresponding ore body thickness of the cross-sectional map are obtained. The volume of the ore body is calculated using the area and thickness of the ore body in the cross-sectional diagram. The ore reserves are then calculated using the volume of the ore body and the average weight of the ore.

6. A mining method considering the dip angle of a gold ore body according to claim 4, characterized in that: The process of extracting dip angle data of the ore body during gold mining and performing comparative analysis and processing yields dip angle data of the gold ore body during actual mining, specifically including: Dip angle monitoring points were set at different locations and depths in the mine simulation model to monitor changes in the ore body during the simulation process; Extract the dip angle data of the ore body from the real-time monitoring data, and visualize the real-time monitoring data in the form of charts to obtain the data on the change of the dip angle of the ore body during the simulated mining process.

7. A mining method considering the dip angle of a gold ore body according to claim 4, characterized in that: The construction of the ore body dip angle prediction model specifically includes: Obtain orebody dip data, which includes the geological characteristics of the orebody, mining conditions, and historical dip data; The acquired tilt angle data is cleaned and normalized. After processing, the data is divided into training set and validation set. A BP neural network model was selected and trained using a training dataset. During the training process, a genetic algorithm was used to optimize the neural network, resulting in a ore body dip angle prediction model. The orebody dip angle prediction model was validated using a validation set, and its performance was evaluated using cross-validation. Once the ore body dip angle prediction model is trained, the real-time collected data on the changes in the ore body dip angle is input into the model, and the predicted ore body dip angle value is output.

8. A mining method considering the dip angle of a gold ore body according to claim 1, characterized in that: The model generation module includes: The construction module is used to construct topographic and geomorphological models of the mining area, geological body models, and models of buildings, bridges, roads, and equipment within the mining area based on topographic and geomorphological data, ore body geological feature data, and mining area building and equipment data, respectively. The integration module is used to integrate terrain and landform models, geological body models, and models of buildings, bridges, roads, and equipment within the mining area; The optimization module is used to remove feature variables that are not beneficial to the integrated mine simulation model through feature selection and dimensionality reduction.

9. A mining method considering the dip angle of a gold ore body according to claim 1, characterized in that: The prediction module includes: The calculation module is used to calculate the reserves of the ore body and design a gold mining plan based on the reserves of the ore body. The analysis module is used to simulate the gold mining process on a mining simulation model and analyze the changes in the dip angle of the ore body during the mining process. The results output module is used to construct a ore body dip angle prediction model and obtain the predicted ore body dip angle value using the ore body dip angle prediction model.

10. A mining method considering the dip angle of a gold ore body according to claim 9, characterized in that: The analysis module includes: The real-time monitoring data is classified according to the type, location and depth of the ore body, while abnormal or erroneous data points are removed. By comparing dip angle data of different ore bodies, different regions, or different time periods, we can analyze the distribution pattern, variation trend, and formation mechanism of ore body dip angle. The data from real-time monitoring is visualized using charts to obtain data on the changes in the dip angle of the ore body during the simulated mining process.

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