Intelligent mine resource management method and system based on dynamic value proof mechanism

Abstract

The invention provides an intelligent mine resource management method and system based on a dynamic value proving mechanism, and the method and system achieve the dynamic evaluation of the mine value through combining a plurality of factors, such as the real-time ore remaining amount, the equipment utilization rate, the market supply and demand data, the ore grade, and the operation cost. And the equipment scheduling strategy of the mine is adjusted through dynamic evaluation of the mine value, so that the resource value of the mine is adjusted in real time, the mine production and mining plan is further optimized, and efficient management and intelligent scheduling of mine resources are realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of mine resource management, and particularly relates to an intelligent mine resource management method and system based on a dynamic value proof mechanism. BACKGROUND

[0002] With the continuous development of the global mining industry, the intelligence and automation level of mine resource management systems gradually improves. At present, most mining enterprises adopt a management architecture based on traditional systems such as GIS (geographic information system) + ERP (enterprise resource planning) + SCADA (data acquisition and monitoring). Although these traditional systems provide certain support in data storage, mine production monitoring, etc., the mine production scheduling of the traditional system relies on manual management, has a low level of intelligence, and is insufficiently optimized. SUMMARY

[0003] In view of the technical problems in the background art, the present application provides an intelligent mine resource management method and system based on a dynamic value proof mechanism, which realizes dynamic evaluation of mine value by constructing a real-time and dynamically adjusted mine value evaluation system, further optimizes mine production and mining plans, and thus achieves the technical effect of efficient management and intelligent scheduling of mine resources.

[0004] In a first aspect, the embodiments of the present application provide an intelligent mine resource management method based on a dynamic value proof mechanism, which specifically includes the following steps:

[0005] Real-time acquisition of mine data and market supply and demand situation data;

[0006] Establishment of a dynamic value proof model, and acquisition of a dynamic value change trend of the mine according to the mine data and the market supply and demand situation data;

[0007] Generation of a device scheduling strategy according to the dynamic value change trend, and scheduling of production device operation according to the device scheduling strategy.

[0008] Further, in the present embodiment, the mine data includes ore remaining amount, device utilization rate, ore grade, and operating cost;

[0009] Input of the ore remaining amount, the device utilization rate, the ore grade, the operating cost, and the market supply and demand situation data into a dynamic value proof model to obtain a dynamic value evaluation value;

[0010] Collection of the dynamic value evaluation value, and analysis and arrangement of the collected dynamic value evaluation value to obtain the dynamic value change trend.

[0011] Further, in the embodiment, the generating the equipment scheduling strategy according to the dynamic value change trend comprises:

[0012] When the dynamic value change trend is an upward trend, increasing the activation frequency of the production equipment, and preferentially exploiting the high-grade ore section;

[0013] When the dynamic value change trend is a downward trend, reducing the activation frequency of the production equipment, and performing preventive maintenance on the production equipment.

[0014] Further, in the embodiment, the method further comprises:

[0015] adjusting an ore sale strategy according to the dynamic value change trend; when the dynamic value change trend is an upward trend, accelerating the sale pace of the ore; and when the dynamic value change trend is a downward trend, slowing down the sale pace of the ore.

[0016] Further, in the embodiment, the method further comprises:

[0017] obtaining an execution structure of the production equipment running according to the equipment scheduling strategy, and inputting the execution result into the dynamic value proof model.

[0018] In a second aspect, the embodiments of the present application provide an intelligent mine resource management system based on a dynamic value proof mechanism, comprising:

[0019] a data acquisition module, configured to acquire mine data and market supply and demand data in real time;

[0020] a dynamic value analysis module, configured to establish a dynamic value proof model, and acquire a dynamic value change trend of the mine according to the mine data and the market supply and demand data;

[0021] an equipment scheduling adjustment module, configured to generate an equipment scheduling strategy according to the dynamic value change trend;

[0022] a strategy execution module, configured to schedule production equipment running according to the equipment scheduling strategy.

[0023] Further, in the embodiment, the mine data comprises ore remaining amount, equipment utilization rate, ore grade, and operation cost;

[0024] the acquiring the dynamic value change trend of the mine according to the mine data and the market supply and demand data comprises:

[0025] inputting the ore remaining amount, the equipment utilization rate, the ore grade, the operation cost, and the market supply and demand data into a dynamic value proof model to obtain a dynamic value evaluation value;

[0026] Collect the dynamic value evaluation values and analyze and arrange the collected dynamic value evaluation values to obtain the dynamic value change trend.

[0027] Further, in the embodiment, the generating a device scheduling strategy according to the dynamic value change trend comprises:

[0028] When the dynamic value change trend is an upward trend, the frequency of starting the production device is increased, and high-grade ore sections are preferentially mined;

[0029] When the dynamic value change trend is a downward trend, the frequency of starting the production device is reduced, and the production device is subjected to preventive maintenance.

[0030] Further, in the embodiment, it further comprises:

[0031] A sales strategy adjustment module is configured to adjust the ore sales strategy; when the dynamic value change trend is an upward trend, the sales pace of the ore is accelerated; and when the dynamic value change trend is a downward trend, the sales pace of the ore is slowed down.

[0032] Further, in the embodiment, it further comprises:

[0033] An execution feedback module is configured to obtain an execution result of the strategy execution module and feed back the execution result to the dynamic value analysis module.

[0034] Beneficial effects: the application provides an intelligent mine resource management method and system based on a dynamic value proof mechanism, combines real-time ore residual quantity, device utilization rate, market supply and demand data, ore grade and operation cost and other factors, realizes dynamic evaluation of mine value, adjusts the device scheduling strategy of the mine through the dynamic evaluation of the mine value, and then adjusts the resource value of the mine in real time, further optimizes mine production and mining plans, and realizes efficient management and intelligent scheduling of mine resources.

[0035] The above description is only a summary of the technical solutions of the application, in order to more clearly understand the technical means of the application, the specific embodiments of the application can be implemented according to the content of the description, and in order to make the above and other purposes, characteristics and advantages of the application more obvious and easy to understand, the following will specifically describe the embodiments of the application. BRIEF DESCRIPTION OF DRAWINGS

[0036] In order to more clearly illustrate the technical solutions of the application, the following will briefly introduce the drawings used in the application. Obviously, the drawings described below are only some embodiments of the application, and other drawings can be obtained by those skilled in the art without creative labor on the basis of these drawings.

[0037] Figure 1 A framework diagram of an intelligent mine resource management system based on a dynamic value proof mechanism is provided for the embodiments of the present application.

[0038] Figure 2 A flowchart of an intelligent mine resource management method based on a dynamic value proof mechanism is provided for the embodiments of the present application. DETAILED DESCRIPTION

[0039] The embodiments of the technical solutions of the present application will be described in detail below with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present application, and therefore only serve as examples, and cannot limit the protection scope of the present application.

[0040] In the following description, specific details such as specific system structures, techniques, etc. are presented in order to thoroughly understand the embodiments of the present application, but it should be clear to those skilled in the art that the present application can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to avoid unnecessary details that hinder the description of the present application.

[0041] The term "comprising" in this document indicates the presence of the described features, whole, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, whole, steps, operations, elements, components and / or sets thereof. The terms "comprise", "include", "have" and their variants mean "including but not limited to", excluding otherwise specifically emphasized. Hereinafter, the terms "first", "second" are only for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating one or more features. In the description of the embodiments of the present application, the meaning of "multiple" is two or more, unless otherwise specified.

[0042] In this document, the term "and / or" only describes the association relationship between the associated objects, which means that there can be three relationships, for example, A and / or B, which means that there are three cases of A alone, A and B together, and B alone. In addition, the character " / " in this document generally represents an "or" relationship between the front and rear associated objects.

[0043] With the continuous development of the global mining industry, the intelligent and automated level of mine resource management systems is gradually improving. At present, most mining enterprises use traditional management architectures based on GIS (Geographic Information System) + ERP (Enterprise Resource Planning) + SCADA (Data Acquisition and Monitoring) and other systems. Although these traditional systems provide some support in data storage, mine production monitoring, etc., they have the following main problems, which affect the efficiency and transparency of mine management:

[0044] (1) The value assessment of mine resources is lagging behind and difficult to reflect the dynamic changes of mine resources. Most of the current mine resource management systems use static data models to assess the value of mines. The value of mines is usually determined based on historical exploration data, fixed resource reserves and current market prices. This method ignores the dynamic factors in the mining process, such as ore grade, operation status of mine equipment, fluctuations in market demand, etc., which makes it difficult to quickly and accurately assess the actual value and profitability of mines. Especially in periods of large market fluctuations, the traditional evaluation system cannot reflect the real economic value of mine resources in real time, affecting the decision-making of mine operations and the judgment of investors. In special periods, it will also make investment decisions seriously deviate from the direction of industry development, leading to serious decision-making errors. With the rapid changes in market demand and mine production conditions, the value assessment of mines needs dynamic and real-time data support. Especially in the context of fierce global mining market competition, real-time assessment of mine resources becomes particularly important.

[0045] (2) The production scheduling of mines relies on manual management, has low intelligence level and is not optimized enough. The current production scheduling and equipment management of mines still mainly rely on manual planning and adjustment, and lack intelligent support in terms of equipment scheduling, maintenance, utilization rate assessment, etc. Due to the complex and changeable factors such as the operation status of equipment, load changes and equipment failures in the production process of mines, manual scheduling often cannot respond to the maintenance needs of equipment in a timely manner, leading to overloading or idling of mine equipment, and even causing equipment failures and production accidents. What's worse, the production scheduling of mines often lacks self-adaptive optimization capability. When market demand changes greatly, it is difficult for mine enterprises to adjust the mining plan in a timely manner, which can easily lead to production imbalance and resource waste.

[0046] In order to solve the technical problems of traditional systems that the production scheduling of mines relies on manual management, has low intelligence level and is not optimized enough, the present application provides an intelligent mine resource management method and system based on a dynamic value proof mechanism. By constructing a real-time and dynamically adjusted mine value assessment system, the dynamic assessment of mine value is realized, and the production and mining plan of mines is further optimized, so as to achieve the technical effect of efficient management and intelligent scheduling of mine resources.

[0047] Please refer to Figure 1 , Figure 1 The present application provides a framework diagram of an intelligent mine resource management system based on a dynamic value proof mechanism.

[0048] The intelligent mine resource management system comprises a data acquisition module, a dynamic value analysis module, a device scheduling and adjusting module, and a strategy execution module. The data acquisition module is configured to acquire mine data and market supply and demand data in real time. The dynamic value analysis module is configured to establish a dynamic value proof model and acquire a dynamic value change trend of the mine according to the mine data and the market supply and demand data. The device scheduling and adjusting module is configured to generate a device scheduling strategy according to the dynamic value change trend. The strategy execution module is configured to schedule production equipment operation according to the device scheduling strategy. In this embodiment, a real-time and dynamically adjusted mine value evaluation system is constructed by introducing a dynamic value proof (DVP) mechanism. By combining the mining conditions of mine resources, the equipment operation efficiency, and the market demand fluctuations, the dynamic evaluation of the mine value is realized. The device scheduling strategy of the mine is adjusted through the dynamic evaluation of the mine value, and the resource value of the mine is adjusted in real time. The mine production and mining plan is further optimized, and the efficient management and intelligent scheduling of mine resources are realized.

[0049] For example, in this embodiment, the specific execution method of the intelligent mine resource management system based on the dynamic value proof mechanism is as follows:

[0050] S1, acquiring mine data and market supply and demand data in real time;

[0051] In this embodiment, the mine data is acquired through geological exploration and real-time detection, and the market supply and demand data is acquired through market research and market demand prediction model.

[0052] For example, the mine data includes residual ore quantity, equipment utilization rate, ore grade, and operating cost.

[0053] Specifically, in this embodiment, the residual ore quantity can be acquired based on geological exploration data and real-time monitoring.

[0054] The ore grade can be acquired by ore quality detection based on XRF spectrum analysis and other technologies.

[0055] The equipment utilization rate can be acquired by calculation based on the production process control and scheduling automation system (SCADA system) and Internet of Things equipment monitoring data.

[0056] The operating cost can be acquired by calculation based on mine operation data (such as labor cost, maintenance cost, etc.) in the system.

[0057] S2, establishing a dynamic value proof model and acquiring a dynamic value change trend of the mine according to the mine data and the market supply and demand data;

[0058] For example, the remaining amount of ore and the grade of ore change as mining progresses, and market supply and demand data also change according to market supply and demand. Therefore, after the mine data and the market supply and demand data are input into the dynamic value proof model, the dynamic value evaluation value obtained will change as the mine data and the market supply and demand data change. Therefore, in this embodiment, the mine data and the market supply and demand data are obtained in chronological order, and a data set is formed. The data set is input into the dynamic value proof model to obtain a set of dynamic value evaluation values at different times. The set of dynamic value evaluation values is arranged in chronological order to obtain a dynamic value evaluation value change graph. The dynamic value change trend is obtained by analyzing the dynamic value evaluation value change graph.

[0059] S3, generating a device scheduling strategy according to the dynamic value change trend, and scheduling the operation of the production device according to the device scheduling strategy.

[0060] In this embodiment, when the device scheduling adjustment module detects that the dynamic value evaluation value changes significantly, the device scheduling adjustment module analyzes the trend of the dynamic value evaluation value, formulates a device scheduling strategy according to the trend of the dynamic value evaluation value, and schedules the key operating parameters of the production device according to the device scheduling strategy. The specific control strategy is as follows:

[0061] When the dynamic value change trend is an upward trend, that is, the dynamic value evaluation value continuously increases, which indicates that the economic value of the mine resources is in a high operating state. The device scheduling adjustment module increases the activation frequency of the production device and appropriately increases the ore mining amount per unit time. At the same time, the device scheduling adjustment module preferentially selects a mining section with a higher grade and a higher profit rate for operation, improves the ore output quality, and increases the conversion efficiency of economic value.

[0062] When the dynamic value change trend is a downward trend, that is, the dynamic value evaluation value continuously decreases, which indicates that the resource profit space is shrinking. The device scheduling adjustment module reduces the activation frequency of the production device and correspondingly reduces the scheduling intensity, delays the mining of low-grade mining sections, and reduces unnecessary equipment load. Some devices will enter a preventive maintenance state to improve subsequent operating efficiency.

[0063] In some embodiments, the system further includes a sales strategy adjustment module for adjusting the ore sales strategy. For example, when the sales strategy adjustment module detects that the dynamic value change trend is an upward trend, the sales strategy adjustment module accelerates the matching of market orders, speeds up the sales pace of the ore, timely releases the market value, maximizes the profit capture, and thereby increases the conversion efficiency of economic value. When the dynamic value change trend is a downward trend, the sales strategy adjustment module slows down the sales pace of the ore to avoid large-scale sale of ore at a market low point and avoid value loss.

[0064] In some embodiments, the system further comprises an execution feedback module, which obtains the execution result of the strategy execution module and feeds back the execution result to the dynamic value analysis module, so as to convert the actual effect of the strategy execution into a dynamic correction basis of the dynamic value proof model, thereby improving the self-adaptation capability of the system.

[0065] In the second aspect, refer to Figure 2 , Figure 2 An intelligent mine resource management method based on a dynamic value proof mechanism is provided for the embodiments of the present application, and the specific steps are as follows:

[0066] Real-time acquisition of mine data and market supply and demand data;

[0067] Establishing a dynamic value proof model and obtaining the dynamic value change trend of the mine according to the mine data and market supply and demand data;

[0068] Generating a device scheduling strategy according to the dynamic value change trend, and scheduling the production device to run according to the device scheduling strategy.

[0069] In some embodiments, the mine data includes ore remaining amount, device utilization rate, ore grade, and operating cost;

[0070] Inputting the ore remaining amount, device utilization rate, ore grade, operating cost, and market supply and demand data into the dynamic value proof model to obtain a dynamic value evaluation value;

[0071] Collecting the dynamic value evaluation value and analyzing and arranging the collected dynamic value evaluation value to obtain a dynamic value change trend.

[0072] In some embodiments, generating a device scheduling strategy according to the dynamic value change trend comprises:

[0073] When the dynamic value change trend is upward, the activation frequency of the production device is increased, and high-grade ore sections are preferentially mined;

[0074] When the dynamic value change trend is downward, the activation frequency of the production device is reduced, and the production device is subjected to preventive maintenance.

[0075] In some embodiments, the method further comprises adjusting an ore sales strategy according to the dynamic value change trend; when the dynamic value change trend is upward, the sales pace of the ore is accelerated; and when the dynamic value change trend is downward, the sales pace of the ore is slowed down.

[0076] In some embodiments, the method further comprises obtaining an execution structure of scheduling the production device to run according to the device scheduling strategy, and inputting the execution result into the dynamic value proof model.

[0077] Exemplarily, the embodiment of the present application provides a specific step of a smart mine resource management method based on a dynamic value proof mechanism as follows:

[0078] S1, real-time collection of ore remaining amount, equipment utilization rate, ore grade, operation cost and market supply and demand data and other parameter data;

[0079] S2, inputting the ore remaining amount, equipment utilization rate, ore grade, operation cost and market supply and demand data into a dynamic value proof model to obtain a dynamic value evaluation value;

[0080] Collecting the dynamic value evaluation value and analyzing and arranging the collected dynamic value evaluation value to obtain a dynamic value change trend.

[0081] Exemplarily, in the embodiment, the mathematical relationship of the dynamic value proof model is as follows:

[0082]

[0083] Wherein:

[0084] α i (t): weight of each factor, indicating the influence degree of different factors on the value of the mine, dynamically adjusted with time t.

[0085] R i (t): ore remaining amount, based on geological exploration data and real-time monitoring.

[0086] G i (t): ore grade, based on XRF spectrum analysis and other technologies for ore quality detection.

[0087] U i (t): equipment utilization rate, calculated based on SCADA system and Internet of Things equipment monitoring data.

[0088] L i (t): operation cost, calculated based on mine operation data (such as labor cost, maintenance cost, etc.) in the ERP system.

[0089] P i (t): market supply and demand data, predicted by market research and market demand prediction model.

[0090] The ore remaining amount and the ore grade change with the mining, and the real-time updating logic is as follows:

[0091] R i (t+1)=R i (t)―ΔR i (t)

[0092] Gi (t+1) = G i (t) - AG i (t)

[0093] Where, AR i (t): the amount of ore mined at time step t; AG i (t): the average grade change of the mined ore at time step t.

[0094] The equipment utilization reflects the load condition, downtime and equipment efficiency of the equipment:

[0095]

[0096] Where, The actual running time of equipment i at time t; The maximum available time of equipment i at time t.

[0097] Market price and demand prediction is carried out through a deep learning model, which is trained and predicted through historical market data and current mine production data:

[0098] P i (t) = f(historical data, mine production data, market supply and demand data)

[0099] S3, generating equipment scheduling strategy according to dynamic value change trend, and scheduling production equipment operation according to equipment scheduling strategy.

[0100] In order to improve the collaboration and intelligent level of the mine resource management system, the present application further proposes a resource management optimization mechanism based on dynamic value proof feedback on the basis of the dynamic value proof (DVP) mechanism. The mechanism analyzes the change trend of the evaluation results of the dynamic value proof, dynamically adjusts the equipment scheduling strategy, mining plan and sales execution of the mine, and realizes the self-adaptive resource management closed loop with the mine economic value as the core.

[0101] (1) Feedback control logic design

[0102] In the operation process of the system, the dynamic value proof model will evaluate the comprehensive value of the current mine in real time, which is influenced by multiple dimensions such as ore grade, equipment utilization, market price, resource remaining amount and environmental protection index. When the system detects that the dynamic value evaluation value changes obviously, the resource management module will adjust the key operation parameters accordingly, and the specific control strategy is as follows:

[0103] When the dynamic value change trend shows an upward trend, it indicates that the economic value of the mine resources is in a high operating state, and the system will automatically increase the equipment activation frequency and appropriately increase the ore mining amount per unit time. At the same time, the system will preferentially select the mine section with higher grade and higher profit rate for operation, improve the ore output quality, and speed up the matching of market orders to release market value in a timely manner.

[0104] When the dynamic value change trend shows a downward trend, it indicates that the resource profit space is shrinking, and the system will accordingly reduce the dispatching intensity, delay the mining of low-grade mine sections, and reduce unnecessary equipment load. Part of the equipment will enter the preventive maintenance state to improve the subsequent operation efficiency. At the same time, the system will dynamically adjust the sales rhythm to avoid large-scale sale of ore at the market low point.

[0105] It should be noted that this control strategy can be completed through automatic calculation of system parameters and contract triggering, ensuring the timeliness of decision-making and the stability of execution.

[0106] (2) Equipment scheduling strategy design and scheduling optimization objective function design

[0107] Equipment scheduling is to maximize the use of equipment under the premise of safety and reliability, and to ensure the utilization rate of each device in ore production. The optimization objective of equipment scheduling is:

[0108]

[0109] Where: A t : Equipment scheduling decision (whether to activate / maintain / stop); U t : Equipment utilization rate; C t : Equipment maintenance cost; M t : Equipment downtime loss. ω: Scheduling coefficient.

[0110] Equipment scheduling intelligent contract decision:

[0111]

[0112] Where, S t is the device state vector, which is used for reinforcement learning model, and the equipment scheduling strategy is optimized according to the real-time operating state of the mine. α is the weight value corresponding to the device state vector, (0, 1).

[0113] If At=1, the device is assigned a task, and At=0, the device remains idle.

[0114] Q function is a deep q learning function, i.e.

[0115] Q(S t ,A t ) = Q(S t ,A t ) + β[Zt + gamma max Q(S t+1 , A) - Q(S t , A t ]

[0116] Wherein, beta is learning rate, decide learning speed, gamma is discount silver, decide future income weight, Zt is current reward, namely actual use income of equipment after dispatching.

[0117] In order to realize the value-oriented scheduling optimization, the DVP evaluation value is used as one of key constraints and optimization targets in decision process in the application.The scheduling optimization function can be expressed as:

[0118] max [A t ·U t ―C t + lambda ·V(t)]

[0119] Wherein: A t : current equipment scheduling decision value, indicates equipment enablement or allocation intensity;U t : equipment utilization rate, reflects actual operation efficiency of equipment;C t : equipment operation and maintenance cost, including operation energy consumption, maintenance expenditure etc.;V(t): economic value of mine based on DVP mechanism real-time output;Lambda: value weight factor, indicates the influence degree of DVP on overall scheduling strategy, and its value can be dynamically adjusted through historical benefit data, to realize the continuous optimization of scheduling strategy.

[0120] Through the introduction of the mechanism, the multi-objective comprehensive balance between equipment utilization efficiency, operation and maintenance cost control and resource value growth can be realized, so that the scheduling behavior has stronger income orientation.

[0121] S4, obtain the execution structure of the production equipment running according to the equipment scheduling strategy, and input the execution result into the dynamic value proof model, convert the actual effect of strategy execution into the dynamic correction basis of the dynamic value proof model, so as to improve the self-adaptive ability of the system

[0122] It should be noted that the application is not limited to the above-mentioned embodiments. The above-mentioned embodiments are only examples, and embodiments having the same technical idea and playing the same role within the scope of the technical solution of the application are included in the technical scope of the application. In addition, within the scope of the main idea of the application, various modifications of the embodiments that can be thought of by those skilled in the art, and other ways constructed by combining part of the constituent elements in the embodiments are also included in the scope of the application.

Claims

1. An intelligent mine resource management method based on a dynamic value proof mechanism, characterized in that: The specific steps include: Real-time access to mine data and market supply and demand data; Establishing a dynamic value proof model and obtaining the dynamic value change trend of the mine based on the mine data and the market supply and demand data; An equipment scheduling strategy is generated according to the dynamic value change trend, and the production equipment operation is scheduled according to the equipment scheduling strategy.

2. The intelligent mine resource management method based on the dynamic value proof mechanism according to claim 1 is characterized in that: The mine data includes ore remaining, equipment utilization, ore grade and operating costs.

3. The intelligent mine resource management method based on dynamic value proof mechanism according to claim 1 is characterized in that: Generating a device scheduling strategy according to the dynamic value change trend includes: When the dynamic value change trend is upward, the activation frequency of production equipment is increased, and high-grade ore sections are mined first; When the dynamic value change trend is a downward trend, the activation frequency of the production equipment is reduced, and preventive maintenance is performed on the production equipment.

4. The intelligent mine resource management method based on dynamic value proof mechanism according to claim 1 is characterized in that: Also includes: Adjusting ore sales strategies based on the dynamic value trends; When the dynamic value change trend is upward, accelerate the sales pace of the ore; When the dynamic value change trend is downward, the sales pace of the ore will be slowed down.

5. The intelligent mine resource management method based on dynamic value proof mechanism according to claim 1 is characterized in that: Also includes: An execution structure for scheduling the operation of production equipment according to the equipment scheduling strategy is obtained, and the execution result is input into the dynamic value proof model.

6. An intelligent mine resource management system based on a dynamic value proof mechanism, characterized in that: include: Data acquisition module, used to obtain mine data and market supply and demand data in real time; A dynamic value analysis module, for establishing a dynamic value proof model and obtaining a dynamic value change trend of a mine based on the mine data and the market supply and demand data; An equipment scheduling adjustment module, configured to generate an equipment scheduling strategy based on the dynamic value change trend; The strategy execution module is used to schedule the operation of production equipment according to the equipment scheduling strategy.

7. The intelligent mine resource management system based on dynamic value proof mechanism according to claim 6 is characterized in that: The mine data includes ore remaining, equipment utilization, ore grade and operating costs.

8. The intelligent mine resource management system based on dynamic value proof mechanism according to claim 6 is characterized in that: Generating a device scheduling strategy according to the dynamic value change trend includes: When the dynamic value change trend is upward, the activation frequency of production equipment is increased, and high-grade ore sections are mined first; When the dynamic value change trend is a downward trend, the activation frequency of the production equipment is reduced, and preventive maintenance is performed on the production equipment.

9. The intelligent mine resource management system based on the dynamic value proof mechanism according to claim 6 is characterized in that: Also includes: Sales strategy adjustment module, used to adjust ore sales strategy; When the dynamic value change trend is upward, accelerate the sales pace of the ore; When the dynamic value change trend is downward, the sales pace of the ore will be slowed down.

10. The intelligent mine resource management system based on the dynamic value proof mechanism according to claim 6, characterized in that: Also includes: The execution feedback module is used to obtain the execution result of the strategy execution module and feed the execution result back to the dynamic value analysis module.

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