Mine resource optimal configuration method based on big data analysis

Abstract

The invention discloses a mine resource optimal configuration method based on big data analysis, and relates to the field of resource optimization, and the method comprises the following steps: collecting mine resource data, setting a resource monitoring unit, and obtaining real-time resource data of a corresponding mine; according to the obtained mine resource data and the real-time resource data, setting a mining process sequence in a corresponding mine mining process, and setting corresponding mining resource data and an initial resource configuration table; obtaining a resource lag coefficient and a resource configuration coefficient between the mining process sequences, and setting a lag resource configuration table according to the resource lag coefficient; carrying out confluence analysis according to the obtained lagging resource configuration table and the corresponding resource configuration coefficient, and constructing a corresponding resource cyclic configuration map by combining real-time resource data corresponding to the corresponding mining process sequence; performing optimization processing according to the resource cyclic configuration map and the corresponding real-time resource data; according to the invention, the collaboration in the resource optimization process is improved.

Description

Technical Field

[0001] The present invention relates to the field of resource optimization, and in particular to a method for optimizing the configuration of mining resources based on big data analysis. Background Art

[0002] With the development of society and economic growth, people's demand for natural resources is increasing. As one of the main suppliers of energy and raw materials, the development and utilization of mine resources are becoming more and more important. However, in the process of mining resources, due to the influence of geological conditions, equipment conditions, personnel quality and other factors, problems such as resource waste and environmental damage often occur. These problems not only affect the economic benefits of mines, but also cause irreversible damage to the surrounding environment. Therefore, how to effectively optimize the allocation of mine resources, improve resource utilization and reduce environmental impact has become a problem that needs to be solved urgently in the current mining industry.

[0003] However, in the process of optimizing mining resources, it is currently impossible to coordinate and optimize according to the order of mining operations. Instead, a single resource optimization process is performed on each mining process in turn, resulting in the failure to consider the synergy between the various processes in the optimization process of each mining process. Therefore, how to improve the synergy of mining process resource optimization is a problem we need to solve. To this end, a mining resource optimization configuration method based on big data analysis is provided. Summary of the invention

[0004] In order to solve the above technical problems, the purpose of the present invention is to provide a method for optimizing the allocation of mining resources based on big data analysis.

[0005] The purpose of the present invention can be achieved by the following technical solution: A method for optimizing the configuration of mining resources based on big data analysis, comprising the following steps:

[0006] Step S1: Collecting mine resource data, setting a resource monitoring unit according to the mine resource data, acquiring real-time resource data of the corresponding mine, and marking the collection time;

[0007] Step S2: setting a mining process sequence in the corresponding mining process according to the obtained mining resource data and real-time resource data, and setting corresponding mining resource data for the corresponding mining process sequence, and obtaining an initial resource configuration table according to the real-time resource data and the mining resource data;

[0008] Step S3: Obtain corresponding resource lag coefficients and resource allocation coefficients according to the real-time resource data obtained from each mining process sequence, and obtain corresponding lag resource allocation table according to the resource lag coefficients;

[0009] Step S4: integrating and analyzing the obtained delayed resource allocation table and the corresponding resource allocation coefficient, and building a corresponding resource cycle configuration map in combination with the real-time resource data corresponding to the corresponding mining process sequence;

[0010] Step S5: Optimize the resource cycle configuration map and the corresponding real-time resource data to obtain the resource optimization data corresponding to each mining process sequence, and make real-time adjustments based on the resource optimization data.

[0011] Furthermore, the process of collecting the mine resource data, setting a resource monitoring unit according to the mine resource data, and obtaining the real-time resource data of the corresponding mine includes:

[0012] Setting up a mine resource optimization platform, which is used for relevant work management personnel to input ore resource data; the mine resource data includes mining equipment backup information, mine address information, mine mineral information, drilling data, exploration data and sample analysis data;

[0013] Construct a three-dimensional visualization model corresponding to the corresponding mine based on the mine resource data, map the mining equipment backup information into the three-dimensional visualization model, and set up the corresponding resource monitoring unit based on the mining equipment backup information;

[0014] The resource monitoring unit is used to obtain real-time resource data at corresponding positions in the three-dimensional visualization model and mark the acquisition time thereof.

[0015] Furthermore, the process of setting a mining process sequence in a corresponding mining process according to the obtained mining resource data and real-time resource data includes:

[0016] Acquire the three-dimensional visualization model and the real-time resource data corresponding to each resource monitoring unit therein; perform analysis and processing according to the acquisition time obtained by the corresponding resource monitoring unit in the three-dimensional visualization model;

[0017] Obtain the change data of the corresponding real-time resource data and its corresponding collection time;

[0018] Set the corresponding mining process sequence according to the order of collection time corresponding to the change data;

[0019] The mining process sequence corresponds to the mining process data corresponding to the change data.

[0020] Furthermore, the process of setting corresponding mining resource data for the corresponding mining process sequence and obtaining an initial resource configuration table according to the real-time resource data and the mining resource data includes:

[0021] Obtain the mining process sequence corresponding to the three-dimensional visualization model in the corresponding mine management space in the mine resource optimization platform, set up the corresponding data storage sub-library, and store the ore resource data corresponding to the corresponding mining process sequence and the collected real-time resource data in the data storage sub-library;

[0022] Obtain mining process data corresponding to the mining process sequence, and obtain mining resource data corresponding to the mining equipment in the corresponding mining process sequence based on the mining process data;

[0023] Compare and analyze the real-time resource data and the mining resource data in the corresponding mining process sequence, obtain the deployable resource data in the mining process sequence, and obtain the initial resource configuration table corresponding to each mining process sequence based on the deployable resource data.

[0024] Furthermore, the process of obtaining corresponding resource lag coefficients and resource allocation coefficients according to the real-time resource data obtained from each mining process sequence includes:

[0025] Arrange the corresponding data storage sub-databases in order according to the mining process sequence;

[0026] The corresponding real-time resource data is set to a corresponding mining data set according to the mining process sequence, wherein the mining data set includes the collection time interval corresponding to the corresponding real-time resource data in the corresponding mining process sequence;

[0027] Acquire multiple mining data sets to generate a mining data set group, wherein the mining data set group includes multiple mining data sets, and mark the acquisition time intervals corresponding to the corresponding mining process sequences in the mining data set group with digits:

[0028] According to the result of the digit marking, the collection time interval corresponding to each mining data set in the mining data set group is analyzed and processed, the collection time interval corresponding to the corresponding digit marking is obtained for weighted average calculation, the corresponding calculation result is obtained according to the weighted average calculation result, and the obtained calculation result is marked as the resource lag coefficient corresponding to the corresponding mining process sequence;

[0029] Analyze and process the real-time resource data corresponding to different mining process sequences according to the resource lag coefficient, and set the historical resource data corresponding to different mining process sequences;

[0030] According to the corresponding ore analysis data, the historical resource data set corresponding to the corresponding historical resource data is selected, and each mining process sequence is combined to obtain the historical resource data set corresponding to the mining process sequence in the corresponding combination for analysis and processing, and obtain the resource allocation coefficient between the mining process sequences in the corresponding combination.

[0031] Furthermore, the process of obtaining the corresponding hysteresis resource configuration table according to the resource hysteresis coefficient includes:

[0032] Obtain the corresponding deployable resource data in the initial resource allocation table and the resource lag coefficient corresponding to each mining resource sequence;

[0033] According to the arrangement order of each mining resource sequence, column arrangement and row arrangement are respectively performed, and the resource lag coefficients between the corresponding mining resource sequences are obtained according to the results of the column arrangement and the row arrangement;

[0034] According to the real-time resource data corresponding to the mining resource sequence and the resource lag coefficients corresponding to other mining resource sequences, the corresponding deployable resource data are analyzed and processed to obtain the corresponding lagged deployment resource data, and the obtained lagged deployment resource data are respectively mapped to the corresponding row and column positions, and the lagged resource configuration table is obtained according to the mapping results.

[0035] Furthermore, the process of integrating and analyzing the obtained delayed resource allocation table with the corresponding resource allocation coefficient and building the corresponding resource cycle allocation map in combination with the real-time resource data corresponding to the corresponding mining process sequence includes:

[0036] Obtain the lagged resource allocation table and the resource allocation coefficients corresponding to each mining resource sequence;

[0037] Obtain the sorting order of each mining process sequence in the delayed resource allocation table, set the corresponding mining process sequence as the main process sequence in turn according to the sorting order, obtain the resource allocation coefficients corresponding to the main process sequence and other mining process sequences, adjust the delayed resource allocation data of other mining process sequences with the obtained resource allocation coefficients, and obtain the corresponding comprehensive allocation resource data; when other mining process sequences are the main process sequences, obtain the comprehensive allocation resource data set for them by other main process sequences before, and cyclically process the corresponding comprehensive allocation resource data for other mining process sequences;

[0038] Integrate the comprehensive resource allocation data corresponding to each main process sequence to obtain the corresponding resource cycle configuration map.

[0039] Furthermore, the real-time resource data obtained from the corresponding mining resource process and the corresponding comprehensive allocation resource data in the resource cycle configuration map are obtained, the obtained comprehensive allocation resource data are optimized according to the real-time resource data, the working status of the mining equipment obtained from the mining process data corresponding to the corresponding mining process sequence is adjusted, the corresponding resource optimization data is obtained, and the resource cycle configuration map is updated according to the resource optimization data.

[0040] Compared with the prior art, the beneficial effects of the present invention are as follows: by setting the resource lag coefficient and the corresponding resource allocation coefficient between the corresponding mining resource sequences, each mining resource sequence is comprehensively analyzed, and the comprehensive resource allocation data corresponding to each mining resource sequence is set, so as to integrate other mining process sequences according to the mining order corresponding to the mining process sequence and the collection time of its real-time resource data, thereby realizing the resource optimization processing of the whole process, and to a certain extent increasing the coordination of the resource optimization processing of each mining process sequence in the mining process. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 This is a schematic diagram of a method for optimizing mine resource configuration based on big data analysis according to an embodiment of the present application. DETAILED DESCRIPTION

[0042] like Figure 1 As shown, a method for optimizing the configuration of mining resources based on big data analysis includes the following steps:

[0043] Step S1: Setting up a mine resource optimization platform, collecting mine resource data, setting up a resource monitoring unit according to the mine resource data, obtaining real-time resource data of the corresponding mine, and marking the collection time;

[0044] Step S2: setting corresponding mine resource utilization process data according to the resource monitoring unit corresponding to the mine resource data, and setting the obtained mine resource utilization process data into a resource utilization process sequence;

[0045] Step S3: storing the real-time resource data corresponding to the mine resource data according to the resource utilization process sequence, acquiring the corresponding historical resource data, analyzing and processing the acquired historical resource data, and acquiring the resource allocation coefficient corresponding to the resource utilization process sequence;

[0046] Step S4: setting the mineral resource configuration table corresponding to each resource utilization process sequence according to the resource configuration coefficient, analyzing and processing the obtained mineral resource configuration table, and setting the corresponding resource cycle configuration map;

[0047] Step S5: acquiring the real-time resource data corresponding to the resource utilization process sequence according to the set resource cycle configuration map, setting corresponding resource optimization data according to the real-time resource data, and mapping it into the resource cycle configuration map to generate a resource optimization configuration map;

[0048] Step S6: Integrate the resource optimization data corresponding to each resource utilization process sequence in the obtained resource optimization configuration map to generate comprehensive resource optimization data; map the comprehensive resource optimization data to the corresponding resource utilization process sequence respectively for adjustment;

[0049] It should be further explained that, in the specific implementation process, the process of setting up a mine resource optimization platform, collecting mine resource data, setting up a resource monitoring unit according to the mine resource data, obtaining real-time resource data of the corresponding mine, and marking the collection time includes:

[0050] Setting up a mine resource optimization platform, which is used to analyze and process corresponding mine resources and optimize the configuration of mine resources;

[0051] The mine resource optimization platform is provided with an information input window and an information collection window;

[0052] The information entry window is used by the work management personnel in the mine resource optimization platform to enter the corresponding mine resource information, which includes mine mineral information, mine geological information, mining equipment backup information and business license information, among which:

[0053] The mine mineral information includes the corresponding ore type and ore grade quality information;

[0054] The mine address information includes the corresponding mining area location information, geological background information and ore body characteristic information;

[0055] The mining equipment backup information includes the corresponding equipment type, equipment configuration, equipment quantity and equipment number, and mining method backup;

[0056] The operating license information includes the mining license, environmental permit and safety compliance record information of the corresponding mine;

[0057] Verify the obtained mining resource information and determine whether the corresponding mining resource information is authentic and valid based on the verification results;

[0058] The information collection window is used to collect corresponding mine resource data according to the mine resource information;

[0059] The information collection window is associated with corresponding information collection equipment, which includes drilling equipment, geological exploration instruments, satellite remote sensing equipment and ore sample analysis equipment, wherein:

[0060] Drilling equipment is used to collect information about underground ore bodies and obtain corresponding drilling data, thereby recording the depth, location, address level and rock samples of the borehole;

[0061] Geological exploration instruments are used to explore the exploration data of the corresponding ore body based on seismic waves;

[0062] Satellite remote sensing equipment is used to obtain geographical and environmental data of the corresponding mining areas;

[0063] The ore sample analysis equipment is used to conduct detailed analysis on the obtained rock samples and ore samples and obtain the corresponding sample analysis data;

[0064] Analyze and process the obtained mining resource data;

[0065] If the corresponding mine resource information is verified and analyzed and is valid, a mine management space is generated, and the mine management space is used to obtain the corresponding mine resource information and mine resource data, analyze and process the corresponding data information, and isolate different mines in the mine resource optimization platform;

[0066] The mine management space acquires mine resource data and mine resource information, and performs data integration according to the drilling data, exploration data and sample analysis data corresponding to the mine resource data;

[0067] Construct a three-dimensional space model, map the drilling data and exploration data into the three-dimensional space model, and obtain the corresponding three-dimensional ore body model and three-dimensional geological model respectively;

[0068] Mapping the sample analysis data to the corresponding three-dimensional ore body model and three-dimensional geological model, and integrating the three-dimensional ore body model and the three-dimensional geological model to obtain a three-dimensional visualization model, wherein the three-dimensional visualization model is used to display the ore body model in a three-dimensional graphic, thereby helping users to intuitively understand the spatial distribution and geological characteristics of the ore body;

[0069] Acquire mining resource information and back up mining equipment information in the acquired mining resource information;

[0070] Correlating the mining methods in the mining equipment backup information with the corresponding equipment types;

[0071] The operation steps corresponding to the mining method corresponding to the equipment type are marked, and a corresponding resource monitoring unit is set according to the marking result. The resource monitoring unit is used to obtain real-time resource data of the corresponding equipment type during the mining process of mine resources:

[0072] In the corresponding mining process, the corresponding mining equipment is mapped into the three-dimensional visualization model, and the real-time resource data corresponding to the mining equipment is marked in the corresponding three-dimensional visualization model;

[0073] Analyze and process the marking results of the real-time resource data obtained by the corresponding resource monitoring unit in the three-dimensional visualization model and the corresponding mining method;

[0074] Obtain the mining process corresponding to the mining method, set corresponding monitoring requirements according to the mining process, and match each resource monitoring unit in the 3D visualization model with the corresponding monitoring requirements;

[0075] If all monitoring requirements are met, the real-time monitoring data corresponding to the marked results corresponding to the resource monitoring units in the three-dimensional visualization model are stored;

[0076] If the monitoring requirements are not met, the resource monitoring units corresponding to the monitoring requirements are set in the three-dimensional visualization model according to the monitoring requirements, the real-time monitoring data corresponding to the monitoring requirements are obtained, and the corresponding resource monitoring units are marked;

[0077] The resource monitoring unit acquires the corresponding real-time monitoring data by marking the collection time corresponding to the real-time monitoring data.

[0078] It should be further explained that, in the specific implementation process, the resource monitoring unit corresponding to the mine resource data sets the corresponding mine resource utilization process data, and sets the resource process sequence with the obtained mine resource utilization process data. The specific implementation process includes:

[0079] Obtain the three-dimensional visualization model and the real-time resource data corresponding to each resource monitoring unit therein;

[0080] Analyze and process the real-time resource data obtained by each resource monitoring unit according to the collection time;

[0081] Analyze and process the acquisition time obtained by the corresponding resource monitoring unit in the three-dimensional visualization model;

[0082] Obtain the change data of the corresponding real-time resource data and its corresponding collection time;

[0083] Set the corresponding mining process sequence according to the order of collection time corresponding to the change data;

[0084] Correlating the corresponding mining process sequence with the corresponding mining equipment, and generating the corresponding mining resource process sequence according to the mining equipment associated with the mining process sequence;

[0085] The resource mining process sequence is the resource information and sequence information required to be used in the corresponding data mining process during the corresponding mining process.

[0086] It should be further explained that, in the specific implementation process, the real-time resource data corresponding to the mine resource data is stored according to the resource utilization process sequence, the corresponding historical resource data is obtained, the obtained historical resource data is analyzed and processed, and the resource allocation coefficient corresponding to the resource utilization process sequence is obtained. The specific implementation process includes:

[0087] Obtain the mining process sequence corresponding to the three-dimensional visualization model in the corresponding mine management space in the mine resource optimization platform, and set up a corresponding data storage library according to the mine management space;

[0088] The data storage library is used to store the mine resource information, mine resource data and real-time resource data obtained in the mine management space, wherein corresponding data storage sub-libraries are provided according to corresponding mining process sequences;

[0089] The real-time resource data corresponding to the corresponding collection time in the mining process sequence is stored in the corresponding data storage sub-database, and the corresponding data storage sub-database is arranged in sequence according to the mining process sequence;

[0090] Setting resource lag coefficients of different data storage sub-databases according to the order of the data storage sub-databases and the collection time of the corresponding real-time resource data;

[0091] The resource lag coefficient is the lag time in the process of obtaining the same batch of mineral resources in different mining process sequences, and the specific acquisition process includes:

[0092] The corresponding real-time resource data is set to a corresponding mining data set according to the mining process sequence, wherein the mining data set includes the collection time interval corresponding to the corresponding real-time resource data in the corresponding mining process sequence;

[0093] Acquire multiple mining data sets to generate a mining data set group, wherein the mining data set group includes multiple mining data sets, and mark the acquisition time intervals corresponding to the corresponding mining process sequences in the mining data set group with digits:

[0094] According to the result of the digit marking, the collection time interval corresponding to each mining data set in the mining data set group is analyzed and processed, the collection time interval corresponding to the corresponding digit marking is obtained for weighted average calculation, the corresponding calculation result is obtained according to the weighted average calculation result, and the obtained calculation result is marked as the resource lag coefficient corresponding to the corresponding mining process sequence;

[0095] Analyze and process the real-time resource data corresponding to different mining process sequences according to the resource lag coefficient, set the historical resource data corresponding to different mining process sequences, and integrate the various historical resource data;

[0096] Generate a resource data set, wherein the resource data set includes historical resource data corresponding to a corresponding mining process sequence, match the obtained historical resource data, and obtain historical resource data corresponding to a corresponding resource lag coefficient;

[0097] Match the historical resource data corresponding to each mining process sequence;

[0098] According to the corresponding ore analysis data, the historical resource data set corresponding to the corresponding historical resource data is selected, each mining process sequence is combined, and the correlation data analysis is performed to obtain the historical resource data set corresponding to the mining process sequence in the corresponding combination for analysis and processing. The specific implementation process includes:

[0099] Analyze and process each historical resource data in the historical resource data set corresponding to the corresponding mining process sequence, obtain the mean data of the corresponding historical resource data set, and record it as and

[0100] Among them, the observation value of the corresponding historical resource data in the corresponding historical resource data set is obtained and marked as X i and Y i ; R n The resource allocation coefficients marked as corresponding mining process sequences;

[0101]

[0102] The resource allocation coefficients corresponding to the corresponding mining process sequence are stored.

[0103] It should be further explained that, in the specific implementation process, the mineral resource allocation table corresponding to each resource utilization process sequence is set according to the resource allocation coefficient, the obtained mineral resource allocation table is analyzed and processed, and the corresponding resource cycle configuration map is set. The specific implementation process includes:

[0104] Obtain the resource allocation coefficients corresponding to the mining process sequences in the corresponding mine management space in the mine resource optimization platform, analyze and process according to the resource allocation coefficients, and obtain the corresponding mineral resource allocation table;

[0105] Analyze and process the corresponding real-time resource data according to the mining resource sequence;

[0106] According to the real-time resource data corresponding to the resource monitoring unit corresponding to the mining resource sequence and the mining resource data corresponding to the mining equipment, the deployable resource data of the corresponding mining resource sequence at the current moment is obtained, and the deployable resource data is the difference data between the mining resource data and the real-time resource data;

[0107] Correlating the obtained deployable resource data with the corresponding mining resource sequence to generate an initial resource allocation table;

[0108] According to the real-time resource data corresponding to the mining resource sequence and the resource lag coefficients corresponding to other mining resource sequences, the corresponding deployable resource data are analyzed and processed to obtain the corresponding lagged deployment resource data, and the obtained lagged deployment resource data are respectively mapped to the corresponding row and column positions, and the lagged resource configuration table is obtained according to the mapping results.

[0109] It should be further explained that, in the specific implementation process, the process of integrating and analyzing the obtained delayed resource allocation table with the corresponding resource allocation coefficient and building the corresponding resource cycle configuration map in combination with the real-time resource data corresponding to the corresponding mining process sequence includes:

[0110] Obtain the lagged resource allocation table and the resource allocation coefficients corresponding to each mining resource sequence;

[0111] Obtain the sorting order of each mining process sequence in the delayed resource allocation table, set the corresponding mining process sequence as the main process sequence in turn according to the sorting order, obtain the resource allocation coefficients corresponding to the main process sequence and other mining process sequences, adjust the delayed resource allocation data of other mining process sequences with the obtained resource allocation coefficients, and obtain the corresponding comprehensive allocation resource data; when other mining process sequences are the main process sequences, obtain the comprehensive allocation resource data set for them by other main process sequences before, and cyclically process the corresponding comprehensive allocation resource data for other mining process sequences;

[0112] Integrate the comprehensive resource allocation data corresponding to each main process sequence to obtain the corresponding resource cycle configuration map.

[0113] Acquire the real-time resource data obtained from the corresponding mining resource process and the corresponding comprehensive allocation resource data in the resource cycle configuration map, optimize the obtained comprehensive allocation resource data according to the real-time resource data, adjust the working status of the mining equipment obtained from the mining process data corresponding to the corresponding mining process sequence, obtain the corresponding resource optimization data, and update the resource cycle configuration map according to the resource optimization data.

[0114] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A method for optimizing the allocation of mining resources based on big data analysis, characterized in that: The following steps are involved: Step S1: Collecting mine resource data, setting a resource monitoring unit according to the mine resource data, acquiring real-time resource data of the corresponding mine, and marking the collection time; Step S2: setting a mining process sequence in the corresponding mining process according to the obtained mining resource data and real-time resource data, and setting corresponding mining resource data for the corresponding mining process sequence, and obtaining an initial resource configuration table according to the real-time resource data and the mining resource data; Step S3: Obtain corresponding resource lag coefficients and resource allocation coefficients according to the real-time resource data obtained from each mining process sequence, and obtain corresponding lag resource allocation table according to the resource lag coefficients; Step S4: integrating and analyzing the obtained delayed resource allocation table and the corresponding resource allocation coefficient, and building a corresponding resource cycle configuration map in combination with the real-time resource data corresponding to the corresponding mining process sequence; Step S5: Optimize the resource cycle configuration map and the corresponding real-time resource data to obtain the resource optimization data corresponding to each mining process sequence, and make real-time adjustments based on the resource optimization data.

2. The method for optimizing mine resource allocation based on big data analysis according to claim 1, characterized in that: The process of collecting the mine resource data, setting a resource monitoring unit according to the mine resource data, and obtaining the real-time resource data of the corresponding mine includes: A mine resource optimization platform is set up, and the mine resource optimization platform is used for relevant work management personnel to enter ore resource data; the mine resource data includes mining equipment backup information, mine address information, mine mineral information, drilling data, exploration data and sample analysis data; Construct a three-dimensional visualization model corresponding to the corresponding mine based on the mine resource data, map the mining equipment backup information into the three-dimensional visualization model, and set up the corresponding resource monitoring unit based on the mining equipment backup information; The resource monitoring unit is used to obtain real-time resource data at corresponding positions in the three-dimensional visualization model and mark the acquisition time thereof.

3. The method for optimizing mine resource configuration based on big data analysis according to claim 2 is characterized in that: The process of setting the mining process sequence in the corresponding mining process according to the obtained mining resource data and real-time resource data includes: Acquire the three-dimensional visualization model and the real-time resource data corresponding to each resource monitoring unit therein; perform analysis and processing according to the acquisition time obtained by the corresponding resource monitoring unit in the three-dimensional visualization model; Obtain the change data of the corresponding real-time resource data and its corresponding collection time; Set the corresponding mining process sequence according to the order of collection time corresponding to the change data; The mining process sequence corresponds to the mining process data corresponding to the change data.

4. The method for optimizing mine resource configuration based on big data analysis according to claim 3 is characterized in that: The process of setting corresponding mining resource data for the corresponding mining process sequence and obtaining the initial resource configuration table according to the real-time resource data and the mining resource data includes: Obtain the mining process sequence corresponding to the three-dimensional visualization model in the corresponding mine management space in the mine resource optimization platform, set up the corresponding data storage sub-library, and store the ore resource data corresponding to the corresponding mining process sequence and the collected real-time resource data in the data storage sub-library; Obtain mining process data corresponding to the mining process sequence, and obtain mining resource data corresponding to the mining equipment in the corresponding mining process sequence based on the mining process data; Compare and analyze the real-time resource data and the mining resource data in the corresponding mining process sequence, obtain the deployable resource data in the mining process sequence, and obtain the initial resource configuration table corresponding to each mining process sequence based on the deployable resource data.

5. The method for optimizing mine resource configuration based on big data analysis according to claim 4 is characterized in that: The process of obtaining the corresponding resource lag coefficient and resource allocation coefficient according to the real-time resource data obtained from each mining process sequence includes: Arrange the corresponding data storage sub-databases in order according to the mining process sequence; The corresponding real-time resource data is set to a corresponding mining data set according to the mining process sequence, wherein the mining data set includes the collection time interval corresponding to the corresponding real-time resource data in the corresponding mining process sequence; Acquire multiple mining data sets to generate a mining data set group, wherein the mining data set group includes multiple mining data sets, and mark the acquisition time intervals corresponding to the corresponding mining process sequences in the mining data set group with digits: According to the result of the digit marking, the collection time interval corresponding to each mining data set in the mining data set group is analyzed and processed, the collection time interval corresponding to the corresponding digit marking is obtained for weighted average calculation, the corresponding calculation result is obtained according to the weighted average calculation result, and the obtained calculation result is marked as the resource lag coefficient corresponding to the corresponding mining process sequence; Analyze and process the real-time resource data corresponding to different mining process sequences according to the resource lag coefficient, and set the historical resource data corresponding to different mining process sequences; According to the corresponding ore analysis data, the historical resource data set corresponding to the corresponding historical resource data is selected, and each mining process sequence is combined to obtain the historical resource data set corresponding to the mining process sequence in the corresponding combination for analysis and processing, and obtain the resource allocation coefficient between the mining process sequences in the corresponding combination.

6. The method for optimizing mine resource allocation based on big data analysis according to claim 5 is characterized in that: The process of obtaining the corresponding hysteresis resource configuration table according to the resource hysteresis coefficient includes: Obtain the corresponding deployable resource data in the initial resource allocation table and the resource lag coefficient corresponding to each mining resource sequence; According to the arrangement order of each mining resource sequence, column arrangement and row arrangement are respectively performed, and the resource lag coefficients between the corresponding mining resource sequences are obtained according to the results of the column arrangement and the row arrangement; According to the real-time resource data corresponding to the mining resource sequence and the resource lag coefficients corresponding to other mining resource sequences, the corresponding deployable resource data are analyzed and processed to obtain the corresponding lagged deployment resource data, and the obtained lagged deployment resource data are respectively mapped to the corresponding row and column positions, and the lagged resource configuration table is obtained according to the mapping results.

7. The method for optimizing mine resource allocation based on big data analysis according to claim 6 is characterized in that: The process of integrating and analyzing the obtained delayed resource allocation table and the corresponding resource allocation coefficients and building the corresponding resource cycle allocation map in combination with the real-time resource data corresponding to the corresponding mining process sequence includes: Obtain the lagged resource allocation table and the resource allocation coefficients corresponding to each mining resource sequence; Obtain the sorting order of each mining process sequence in the delayed resource allocation table, set the corresponding mining process sequence as the main process sequence in turn according to the sorting order, obtain the resource allocation coefficients corresponding to the main process sequence and other mining process sequences, adjust the delayed resource allocation data of other mining process sequences with the obtained resource allocation coefficients, and obtain the corresponding comprehensive allocation resource data; when other mining process sequences are the main process sequences, obtain the comprehensive allocation resource data set for them by other main process sequences before, and cyclically process the corresponding comprehensive allocation resource data for other mining process sequences; Integrate the comprehensive resource allocation data corresponding to each main process sequence to obtain the corresponding resource cycle configuration map.

8. The method for optimizing the allocation of mining resources based on big data analysis according to claim 7 is characterized in that: Acquire the real-time resource data obtained from the corresponding mining resource process and the corresponding comprehensive allocation resource data in the resource cycle configuration map, optimize the obtained comprehensive allocation resource data according to the real-time resource data, adjust the working status of the mining equipment obtained from the mining process data corresponding to the corresponding mining process sequence, obtain the corresponding resource optimization data, and update the resource cycle configuration map according to the resource optimization data.

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