Coal quality structure data acquisition and analysis system

Abstract

The invention provides a coal quality structure data acquisition and analysis system, and belongs to the technical field of coal mine resource monitoring and analysis, and the system comprises an information acquisition module which is used for determining a plurality of key point locations of a coal mine, deploying scanning equipment at the key point locations of the coal mine, and obtaining the structure information of the coal quality; the parameter acquisition module is used for performing micro-splitting analysis on the structural information of the coal quality so as to acquire microstructure parameters of the coal quality; the parameter analysis module is used for analyzing the microstructure parameters of the coal quality so as to determine the characteristic parameters of a plurality of coal samples; the parameter determining module is used for determining coal sample grading parameters based on the characteristic parameters of all the coal samples and a preset model; and the report generation module is used for acquiring coal quality related information of coal in the coal mine based on a preset sensor group, determining grading information of the coal in the coal mine by combining the coal sample grading parameters and generating a coal quality analysis report. The traditional sampling limitation is broken through, the data acquisition coverage rate and the analysis precision are comprehensively improved, and the coal resource management efficiency is remarkably optimized.

Description

Technical Field

[0001] The present invention relates to the technical field of coal mine resource monitoring and analysis, and particularly to a coal quality structure data acquisition and analysis system. Background Art

[0002] With the wide application of coal resources, the accurate analysis of coal quality structure and classification has become an important requirement in the coal mine industry. However, traditional coal quality monitoring technologies usually rely on manual sampling and laboratory testing, with low efficiency and unable to achieve real-time monitoring and accurate analysis of large-scale coal quality data.

[0003] In the prior art, some coal quality detection methods based on scanning devices and sensors have been proposed. For example, some solutions use optical scanning or ultrasonic sensors to collect partial structure data on the surface of coal samples, and obtain coal quality parameters through laboratory model analysis. However, these methods mostly have the following defects: the data acquisition coverage is limited and cannot comprehensively reflect the overall situation of coal quality in the coal mine; there is a lack of fine analysis of the microscopic structure of coal quality, resulting in inaccurate characteristic parameters; it is unable to dynamically generate a classification analysis report by combining real-time monitoring data, resulting in a lag in the classification results and affecting the optimal utilization of coal resources.

[0004] Therefore, the present invention provides a coal quality structure data acquisition and analysis system. Summary of the Invention

[0005] The present invention provides a coal quality structure data acquisition and analysis system, which is used to accurately obtain microscopic structure parameters of coal quality through the combination of a scanning device and micro-fission analysis, and realize dynamic classification and analysis of coal samples by combining a preset model and a sensor group. This system breaks through the limitations of traditional sampling, comprehensively improves the data acquisition coverage rate and analysis accuracy, provides real-time and intelligent coal quality classification reports, and significantly optimizes the management efficiency of coal resources.

[0006] The present invention provides a coal quality structure data acquisition and analysis system, including: Information acquisition module: Determine several key points in the coal mine, deploy scanning devices at the key points in the coal mine, and then obtain the structural information of coal quality; Parameter acquisition module: Perform micro-fission analysis on the structural information of coal quality, and then obtain the microscopic structure parameters of coal quality; Parameter analysis module: Analyze the microscopic structure parameters of coal quality, and then determine the characteristic parameters of several coal samples; Parameter determination module: Determine the parameters for coal sample classification based on the characteristic parameters of all coal samples and a preset model; Report generation module: Obtain coal quality-related information of coal in the coal mine based on a preset sensor group, combine the parameters for coal sample classification to determine the classification information of coal in the coal mine, and generate a coal quality analysis report.

[0007] The present invention provides a coal quality structure data acquisition and analysis system, an information acquisition module, including: Data analysis unit: determining exploration data of coal quality based on a preset geological exploration report of a coal mine and formation analysis data; First analysis unit: performing a first analysis on the exploration data of coal quality to determine a number of key coal seams; Second analysis unit: performing a second analysis on the exploration data of coal quality to determine key points of each key coal seam; Demand analysis unit: obtaining preset production demands and coal quality monitoring demands of a coal mine and performing demand analysis to determine a number of types of coal quality data to be collected; Equipment determination unit: determining a scanning device corresponding to each type of coal quality data based on a preset type - equipment database; Data acquisition unit: deploying scanning devices at key points of each key coal seam and collecting structure data of key points of each coal mine.

[0008] The present invention provides a coal quality structure data acquisition and analysis system, a parameter acquisition module, including: Characteristic acquisition unit: performing characteristic analysis on the structure information of coal quality to obtain characteristics of the structure information of coal quality; Parameter acquisition unit: determining a micro - splitting analysis method based on the characteristics of the structure information of coal quality and a preset characteristic - method database, and then obtaining microscopic structure parameters of coal quality.

[0009] The present invention provides a coal quality structure data acquisition and analysis system, a parameter acquisition unit, including: Information disassembling sub - unit: disassembling the structure information of coal quality based on a preset segmentation algorithm to disassemble the structure information of coal quality into a number of information units; Unit classification sub - unit: classifying all information units based on a preset classification algorithm to obtain an information unit group corresponding to each type of information unit; First analysis sub - unit: analyzing the first information unit group based on a first preset analysis method to extract a number of first structure parameters; Second analysis sub - unit: analyzing the second information unit group based on a second preset analysis method to extract a number of second structure parameters; Third analysis sub - unit: analyzing the third information unit group based on a third preset analysis method to extract a number of third structure parameters; Parameter determination sub - unit: determining the first structure parameters, the second structure parameters, and the third structure parameters as microscopic structure parameters of coal quality.

[0010] The present invention provides a coal quality structure data acquisition and analysis system The first preset analysis method is the pore and fracture analysis method, the second preset analysis method is the mineral composition analysis method, and the third preset analysis method is the coal particle structure analysis method.

[0011] The present invention provides a coal quality structure data acquisition and analysis system, and a parameter analysis module, including: An algorithm determination unit: determining a feature extraction algorithm corresponding to the structural parameters corresponding to each type of information unit group based on a preset type - algorithm database; A feature extraction unit: extracting features of the microscopic structural parameters of the coal quality based on the feature extraction algorithm corresponding to the structural parameters corresponding to each type of information unit group, and further determining the feature parameters of a plurality of coal samples.

[0012] The present invention provides a coal quality structure data acquisition and analysis system, and a report generation module, including: Obtaining coal quality - related information of coal in a coal mine based on a preset sensor group and analyzing it, and further determining coal quality - related parameters of coal samples in the coal mine; Determining a grading coefficient of the coal quality of coal samples in the coal mine based on the parameters of coal sample grading and the coal quality - related parameters of coal samples in the coal mine: According to the grading coefficient of the coal quality of coal samples in the coal mine and a preset grading threshold, classifying the coal samples, and further determining the grades of a plurality of coal samples; Generating a coal quality analysis report of coal based on the grades of coal samples and the coal quality - related parameters of the corresponding coal samples.

[0013] The present invention provides a coal quality structure data acquisition and analysis system, and a coal quality analysis report of coal, including: basic information of coal samples, analysis of coal sample properties, and coal quality grading information.

[0014] Compared with the prior art, the beneficial effects of the present application are as follows: By combining a scanning device with micro - splitting analysis, accurately obtaining the microscopic structural parameters of coal quality, and realizing dynamic grading and analysis of coal samples by combining a preset model with a sensor group. This system breaks through the limitations of traditional sampling, comprehensively improves the data acquisition coverage rate and analysis accuracy, provides real - time and intelligent coal quality grading reports, and significantly optimizes the management efficiency of coal resources. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0016] Figure 1 It is a schematic structural diagram of a coal quality structure data acquisition and analysis system provided by an embodiment of the present invention. Specific Embodiments

[0017] To make the objectives, technical solutions, and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below with reference to the accompanying drawings in the present invention. Apparently, the described embodiments are some but not all of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present invention without creative efforts shall fall within the protection scope of the present invention.

[0018] Embodiment 1: An embodiment of the present invention provides a coal quality structure data acquisition and analysis system, as Figure 1 shown, including: Information acquisition module: Determine several key points in the coal mine, deploy scanning devices at the key points in the coal mine, and then acquire the structural information of the coal quality. Parameter acquisition module: Perform micro-fission analysis on the structural information of the coal quality, and then acquire the microstructural parameters of the coal quality. Parameter analysis module: Analyze the microstructural parameters of the coal quality, and then determine the characteristic parameters of several coal samples. Parameter determination module: Determine the parameters for coal sample classification based on the characteristic parameters of all coal samples and a preset model. Report generation module: Acquire the coal quality-related information of the coal in the coal mine based on a preset sensor group, determine the classification information of the coal in the coal mine in combination with the parameters for coal sample classification, and generate a coal quality analysis report.

[0019] In this embodiment, the structural information of the coal quality refers to the external and internal structural characteristic data collected from the coal sample by the scanning device, including pore distribution, fracture morphology, mineral composition, etc. These information are the basic data sources for subsequent analysis. For example: The scanning device at a key point in a coal mine detects a coal sample, and its structural information includes: the porosity is 12%, the fracture width is 0.01 mm, the fracture trend is longitudinal, and the mineral particle distribution is uniform. This information is used to preliminarily evaluate the gas storage performance and structural stability of the coal sample.

[0020] In this embodiment, micro-fission analysis refers to the refined analysis of the coal sample structural information through high-precision data processing technology to obtain microstructural parameters, such as micro-fracture density, pore size distribution, mineral crystal morphology, etc. These parameters reflect the mesoscopic characteristics of the coal quality. For example: Analyze a coal sample using micro-fission analysis technology, and obtain the following microstructural parameters: the microfracture density is 4 fractures / mm², the pore size ranges from 0.1 to 0.5 mm, and the average diameter of mineral crystals is 0.2 mm. These parameters indicate that the coal sample has high adsorption performance and is suitable for coalbed methane extraction.

[0021] In this embodiment, the characteristic parameters of the coal sample are key characteristic indicators further calculated based on the microstructural parameters, which are used to comprehensively reflect the properties of the coal sample, including sulfur content, ash content, calorific value, strength, etc. For example, the characteristic parameters of a certain coal sample include: sulfur content is 1.2%, ash content is 9%, calorific value is 28 MJ / kg, and strength is 15 MPa. Through these parameters, it can be judged that the coal sample is a high-quality coal type with medium sulfur, low ash, and high calorific value, and is suitable for power generation.

[0022] In this embodiment, the parameters for coal sample classification are classification indicators calculated through characteristic parameters and a preset model, which are used to classify coal samples, such as first-class and second-class coal, or classification by application fields (fuel coal, coking coal, etc.). For example, based on the characteristic parameters, the classification parameters of a certain coal sample are calculated as first-class coal (suitable for efficient combustion), while another coal sample is classified as second-class coal (suitable for medium- and low-efficiency industrial boilers) due to its relatively high sulfur content and low calorific value. These classification information can guide the sorting and market placement of coal.

[0023] Beneficial effects of the above technical solution: By combining a scanning device with micro-fission analysis, accurately obtain the microstructural parameters of coal quality, and combine a preset model and a sensor group to achieve dynamic classification and analysis of coal samples. This system breaks through the limitations of traditional sampling, comprehensively improves the data acquisition coverage rate and analysis accuracy, provides real-time and intelligent coal quality classification reports, and significantly optimizes the management efficiency of coal resources.

[0024] Example 2: The embodiment of the present invention provides a coal quality structure data acquisition and analysis system, and the information acquisition module includes: Data analysis unit: Determine the exploration data of coal quality based on the preset geological exploration report of the coal mine and the formation analysis data; First analysis unit: Conduct a first analysis on the exploration data of coal quality to determine several key coal seams; Second analysis unit: Conduct a second analysis on the exploration data of coal quality to determine the key points of each key coal seam; Demand analysis unit: Obtain the preset production demand and coal quality monitoring demand of the coal mine and conduct demand analysis to determine several types of coal quality data to be collected; Equipment determination unit: Determine the scanning equipment corresponding to each type of coal quality data based on the preset type-equipment database; Data acquisition unit: Scanning devices are deployed at key points of each key coal seam to collect structural data of key points in each coal mine.

[0025] In this embodiment, the key coal seams are coal seams with important economic value or research significance selected through geological exploration data and stratigraphic analysis results of the coal mine. These coal seams may have high calorific value, low sulfur content or rich mineral resources, and are the key targets for coal mining. For example, in the geological exploration report of a certain coal mine, the geological characteristics of multiple coal seams are marked. Through analysis, it is found that the third coal seam at a depth of 300 - 350 meters has excellent characteristics such as an average calorific value of 30 MJ / kg, a sulfur content of less than 1.0%, and a thickness of 8 meters, and is determined as a key coal seam, suitable for mining as an efficient fuel for power plants.

[0026] In this embodiment, the types of coal quality data refer to the categories of coal - related data that need to be collected according to the production requirements and monitoring requirements of the coal mine. Common data types include porosity, fracture distribution, ash content, sulfur content, calorific value, mineral composition, etc. For example, a certain coal mine plans to optimize the coal separation process, and its monitoring requirements include the following types of coal quality data: fracture distribution data (used to evaluate the mining difficulty of the coal seam); calorific value data (used to classify high - calorific - value and low - calorific - value coal); mineral composition data (used to identify rare mineral components); sulfur content data (used for environmental protection and fuel classification). Based on the requirements, the system will select the corresponding scanning device for accurate data collection.

[0027] Beneficial effects of the above - mentioned technical solution: Based on geological exploration data and monitoring requirements, accurate screening of key coal seams is achieved, and scanning devices are efficiently matched in combination with the type - device database, ensuring that the collected coal quality data is comprehensive, accurate and efficient, meeting the needs of coal mine production optimization and decision - making support.

[0028] Embodiment 3: The embodiment of the present invention provides a coal quality structure data acquisition and analysis system. The parameter acquisition module includes: Characteristic acquisition unit: Analyze the characteristics of the structural information of coal quality to obtain the characteristics of the structural information of coal quality; Parameter acquisition unit: Determine the micro - fracture analysis method based on the characteristics of the structural information of coal quality and the preset characteristic - method database, and then obtain the microscopic structure parameters of coal quality.

[0029] In this embodiment, the characteristics of the structural information of coal quality refer to specific characteristic parameters extracted by analyzing the structural information of coal quality (such as pores, fractures, mineral distribution, etc.). These characteristics reflect the internal structural characteristics of coal quality, such as porosity, fracture width, fracture connectivity, etc., and are used to guide the selection and analysis of subsequent microstructure analysis. For example, after scanning and analyzing a certain coal sample, the characteristics of the structural information of coal quality include: porosity: 10%, fracture width: average 0.03 mm, fracture connectivity: poor, mineral distribution uniformity: high. These characteristics indicate that this coal sample has low gas permeability and is suitable as a target for coalbed methane storage. At the same time, its high mineral distribution uniformity is suitable for further extraction of rare minerals.

[0030] In this embodiment, the preset characteristic-method database is a mapping table that associates different coal quality characteristics (such as fracture width, porosity, etc.) with corresponding microfracture analysis methods (such as specific algorithms or scanning modes) to achieve the selection of characteristic-driven analysis methods. This database automatically matches suitable analysis methods through preset rules or models, improving the analysis efficiency and accuracy. For example, the preset characteristic-method database contains the following mapping rules: when the porosity is less than 15% and the fracture width is less than 0.05 mm, a high-resolution CT scanning analysis method is used; when the fracture width is greater than 0.1 mm and the connectivity is high, a three-dimensional modeling analysis method is used; when the mineral distribution uniformity is high, a spectral imaging analysis method is used. In practical applications, if a certain coal sample has a porosity of 12%, a fracture width of 0.03 mm, and poor fracture connectivity, the system will automatically select a high-resolution CT scanning analysis method to more accurately obtain microstructure parameters.

[0031] Beneficial effects of the above technical solutions: The characteristics of the structural information of coal quality provide a quantitative description of the coal sample structure, laying a data foundation for subsequent analysis. The characteristic-method database optimizes the analysis process through the dynamic matching of characteristics and analysis methods, improving automation and accuracy. The characteristic-driven analysis process not only improves the analysis efficiency but also ensures that specific coal quality characteristics are targeted for excavation, significantly improving the resource utilization value. For example, by selecting the optimal analysis method, the coalbed methane storage capacity or mineral extraction potential can be accurately evaluated.

[0032] Example 4: The embodiment of the present invention provides a coal quality structure data acquisition and analysis system, and the parameter acquisition unit includes: Information disassembling subunit: Disassemble the structural information of coal quality based on a preset segmentation algorithm, and then disassemble the structural information of coal quality into several information units; Unit classification subunit: Classify all information units based on a preset classification algorithm, and then obtain the information unit group corresponding to each type of information unit; The first analysis subunit: Analyze the first information unit group based on the first preset analysis method, and then extract a number of first structure parameters; The second analysis subunit: Analyze the second information unit group based on the second preset analysis method, and then extract a number of second structure parameters; The third analysis subunit: Analyze the third information unit group based on the third preset analysis method, and then extract a number of third structure parameters; The parameter determination subunit: Determine the first structure parameter, the second structure parameter, and the third structure parameter as the microscopic structure parameters of the coal quality.

[0033] In this embodiment, the preset classification algorithm is a set of rules or calculation methods for classifying the segmented information units according to the characteristics of the coal quality structure information. The basis for classification can be the geometric shape, physical properties, chemical composition, or other characteristics of the information units. The role of this algorithm is to organize complex coal quality data into analyzable classification groups, providing a basis for subsequent targeted analysis. For example, when analyzing a certain coal sample, the preset classification algorithm may include the following rules: Geometric classification rule: According to the size of the information unit, pore information units are divided into small pores (diameter < 0.1 mm) and large pores (diameter ≥ 0.1 mm); Physical property classification rule: According to the density difference, information units are divided into high density (mineral particles) and low density (coal-based substances); Chemical classification rule: Based on the spectral analysis results, information units are divided into sulfur-containing units, sulfur-free units, and mineral-rich units. In practical applications, after the scanning device collects the structure data of the coal sample, the preset classification algorithm classifies it into the following information unit groups: The first information unit group: small pores (pore diameter < 0.1 mm); The second information unit group: sulfur-rich fracture units; The third information unit group: mineral crystal units. These classifications provide accurate input data for subsequent targeted analysis methods (such as porosity analysis, fracture connectivity calculation, mineral composition extraction).

[0034] The beneficial effects of the above technical solution: Through the information disassembling subunit and the unit classification subunit, the complex coal quality structure information is refined into several information unit groups and scientifically classified. This can carry out targeted analysis for different types of structural characteristics, improve the analysis efficiency and accuracy, select different analysis methods (the first, second, and third preset analysis methods) based on different classified information unit groups, realize multi-dimensional and multi-level microscopic structure analysis, ensure the comprehensiveness and depth of the data, and synthesize the first, second, and third structure parameters into the microscopic structure parameters of the coal quality, which not only ensures the integrity of the parameters but also provides more scientific data support for coal sample grading and utilization.

[0035] Example 5: The embodiment of the present invention provides a coal quality structure data acquisition and analysis system, The first preset analysis method is the pore and fracture analysis method, the second preset analysis method is the mineral composition analysis method, and the third preset analysis method is the coal particle structure analysis method.

[0036] In this embodiment, the first preset analysis method: the pore and fracture analysis method is used to detect the porosity, fracture distribution and their morphological characteristics inside the coal sample. By analyzing the scanning data of the coal sample, parameters such as porosity, fracture width and connectivity are quantified to evaluate the gas storage performance and mechanical properties of the coal. For example, by using a scanning device to obtain the internal structure information of the coal sample, it is found that the porosity of the coal sample is 15%, the average fracture width is 0.02 mm, and the fracture connectivity is poor. The results show that this coal sample has low gas permeability and high gas storage capacity, and is suitable as a target area for coalbed methane development; In this embodiment, the second preset analysis method: the mineral composition analysis method detects the mineral content and distribution of the coal sample to identify the types and proportions of sulfur-containing, ash-containing components and rare minerals in the coal. This method helps to judge the combustion performance and industrial uses of the coal. For example, by using the mineral composition analysis method, it is detected that the sulfur content of a certain coal sample is 2.5%, the ash content is 10%, and the content of rare earth minerals (such as cerium and lanthanum) is 0.02%. The analysis results show that this coal sample is a high-sulfur coal and is not suitable for use as an environmentally friendly fuel, but the content of rare earth minerals has certain development value; In this embodiment, the third preset analysis method: the coal particle structure analysis method evaluates the internal compactness and mechanical strength of the coal sample by analyzing the morphology, particle size distribution and arrangement structure of the coal particles, so as to judge the mining and transportation performance of the coal. For example, through the coal particle structure analysis of a certain coal sample, the results show that the average particle size of the coal particles is 0.5 mm, the particle size distribution is uniform, the arrangement structure is relatively compact, and the mechanical strength is high, which is suitable for mechanized mining and long-distance transportation, reducing pulverization and loss.

[0037] The beneficial effects of the above technical solutions: By analyzing the pores and fractures in the coal sample, the microscopic structural characteristics of the coal quality are obtained. By analyzing the components of the minerals in the coal, the mineral content and its distribution of the coal are evaluated. By analyzing the structure of the coal particles, the morphology, size and distribution characteristics of the coal particles are understood. The three analysis methods work together to provide basic data and analysis basis for the comprehensive evaluation and utilization of coal quality.

[0038] Embodiment 6: The embodiment of the present invention provides a coal quality structure data acquisition and analysis system, and a parameter analysis module, including: Algorithm determination unit: Based on the preset type - algorithm database, determine the feature extraction algorithm corresponding to the structure parameters of each type of information unit group; Feature extraction unit: Based on the feature extraction algorithm corresponding to the structure parameters of each type of information unit group, extract the features of the microscopic structure parameters of the coal quality, and then determine the feature parameters of several coal samples.

[0039] In this embodiment, the feature extraction algorithm is a mathematical or statistical calculation method used to extract specific feature information from the microscopic structure parameters of coal quality. These algorithms extract key data that can characterize the structural characteristics of coal quality, such as the connectivity of fissures, porosity, mineral composition, etc., according to the type of information unit group and the characteristics of its structural parameters. The feature extraction algorithm is an important tool for achieving accurate analysis and can provide a scientific basis for coal quality grading and utilization. For example, when analyzing a certain coal sample, the system uses the following feature extraction algorithms: Fissure connectivity algorithm: Apply the connectivity calculation algorithm to the fissure information unit group to extract the connectivity index of the fissure network. For example, the calculated connectivity index is 0.75, indicating that the fissures are relatively well-connected and suitable for coalbed methane development. Porosity calculation algorithm: Apply the porosity calculation formula based on volume ratio to the pore information unit group to extract a porosity of 12%, indicating that the coal sample has a certain gas storage capacity. Mineral composition extraction algorithm: Based on the spectral analysis-based composition extraction algorithm, extract the main mineral composition from the mineral information unit group and determine its proportion. For example, in a certain coal sample, kaolinite accounts for 35%, quartz accounts for 15%, and other minerals account for 50%. These feature extraction algorithms convert the microscopic structure parameters into quantifiable coal sample feature parameters, providing a basis for further coal quality grading.

[0040] Beneficial effects of the above technical solution: Based on the type-algorithm database, the system can automatically match the feature extraction algorithm that best suits the characteristics of the information unit group. For example, different types of pores (micropores, macropores) use different algorithms, which helps to improve the accuracy and reliability of the extraction results. Through targeted algorithms, the system can comprehensively extract the microscopic features of coal quality from multiple dimensions (such as pore characteristics, fissure characteristics, mineral properties, etc.), providing multi-level support for subsequent coal quality grading and evaluation. Different coal samples have complex microscopic structures. By dynamically selecting appropriate algorithms, the system can flexibly handle various types of coal sample characteristics, enhancing generality and applicability.

[0041] Example 7: The embodiment of the present invention provides a coal quality structure data acquisition and analysis system, a report generation module, including: Obtain coal quality-related information of coal in the coal mine based on a preset sensor group and analyze it, and then determine the coal quality-related parameters of the coal sample in the coal mine; Determine the grading coefficient of the coal quality of the coal sample in the coal mine based on the parameters of coal sample grading and the coal quality-related parameters of the coal sample in the coal mine: According to the grading coefficient of the coal quality of the coal sample in the coal mine and the preset grading threshold, classify the coal sample, and then determine several coal sample grades; Generate a coal quality analysis report based on the coal sample grade and the corresponding coal quality-related parameters of the coal sample.

[0042] In this embodiment, the classification coefficient of coal quality is a value calculated by combining the coal-quality-related parameters (such as ash content, volatile content, calorific value, etc.) of coal samples in a coal mine with the coal sample classification standard, and is used to represent the grade of the coal quality of the coal sample. The classification coefficient is actually a quantitative index used to convert different coal-quality characteristics of coal into corresponding classification identifiers. Suppose the ash content of a coal sample is 30%, the volatile content is 15%, and the calorific value is 5,000 kcal / kg. Through the preset analysis standard and formula, the classification coefficient of this coal sample may be 1.2, and this value can reflect the position of this coal sample in the coal-quality grade; In this embodiment, the preset classification threshold is a value set according to the coal-quality classification standard and is used to divide coal samples into different grades. The classification threshold is usually the upper or lower limit value set for different coal-quality parameters (such as ash content, volatile content, calorific value, etc.). The classification coefficient of coal quality is compared with these thresholds to determine the specific grade of the coal sample. For example, suppose the coal-quality classification standard is: Grade A: classification coefficient above 1.0; Grade B: classification coefficient between 0.8 and 1.0; Grade C: classification coefficient between 0.5 and 0.8; Grade D: classification coefficient below 0.5. If the coal-quality classification coefficient obtained from the analysis of the coal sample is 0.75, then according to the above preset classification threshold, this coal sample will be classified as Grade C.

[0043] In this embodiment, the coal sample grade is the grade finally determined after comparing the coal-quality-related parameters and classification coefficient of the coal sample with the preset classification threshold. Usually, these grades are used to reflect the quality of the coal sample. For example, Grade A indicates higher quality, and Grade D indicates lower quality. Example: Based on the previous threshold example, if the classification coefficient of a coal sample is 0.9, then it is classified as a Grade B coal sample. The grade of the coal sample can be further used for market sales, evaluating the resource quality of the coal mine, or selecting appropriate combustion methods according to coals of different grades.

[0044] Advantages of the above technical solution: By based on multiple coal-quality-related parameters and sensor group data, it can more accurately reflect the actual coal quality of coal samples. The systematic and automated coal-quality classification process avoids manual subjective judgment, reduces human errors, and improves the classification efficiency. Based on the grade and related parameters of coal samples, a coal quality analysis report is automatically generated, which is convenient for coal mine enterprises to make scientific decisions and improve the coal mine management level. Through the precise analysis and grade division of coal quality, coal mine enterprises can better grasp the quality status of coal resources, rationally allocate resources, and improve economic benefits.

[0045] Embodiment 8: The embodiment of the present invention provides a coal-quality structure data acquisition and analysis system, a coal quality analysis report for coal, including: basic information of coal samples, analysis of coal sample properties, and coal-quality classification information.

[0046] In this embodiment, the basic information of the coal sample refers to the basic data related to the coal sample, usually including the time of sample collection, location, coal mine name, sample number, sampling depth, etc. This part of information is the basis of the analysis report. For example, the basic information of a certain coal sample is as follows: Collection time: December 15, 2024, Sampling location: No. 15 mining area of a coal mine in Shanxi, Sample number: S20241215-01, Sampling depth: 300 meters underground, Coal mine name: XX Coal Mine. These basic information can trace the source of the coal sample; In this embodiment, the analysis of the properties of the coal sample is a process of detecting and analyzing the physical and chemical characteristics of the coal, mainly including indicators such as ash content, volatile matter, fixed carbon, moisture content, calorific value, sulfur content, etc. These parameters are the core of coal quality evaluation. For example, the analysis results of the properties of the coal sample are as follows: Ash content: 28%, Volatile matter: 18%, Fixed carbon: 50%, Moisture content: 4%, Calorific value: 5300 kcal / kg, Sulfur content: 1.2%. These data comprehensively reflect the combustion performance, pollutant emission characteristics, etc. of the coal, and are the basis for coal quality classification; In this embodiment, the coal quality classification information is to classify the coal sample and provide the classification result based on the analysis results of the properties of the coal sample, combined with the classification coefficient and classification threshold. It directly indicates the classification of the coal sample in terms of quality, such as whether it is high-quality coal, high-sulfur coal, power coal, etc. For example, based on the classification analysis of the coal sample, the results are as follows: Classification coefficient: 0.85, Coal grade: Grade B (medium-quality power coal). The coal quality classification information provides an important reference for the subsequent application of coal. For example, Grade B coal is suitable for industrial boilers, but may not be suitable for use as high-quality coking coal.

[0047] Beneficial effects of the above technical solution: By integrating the basic information of the coal sample, the analysis results of the properties, and the classification information, a systematic and complete coal quality analysis report is formed, which is convenient for users to quickly understand the core indicators and classification results of the coal sample, provides a clear reference for coal quality grades for coal mining enterprises or users. By recording the basic information of the coal sample (such as sampling time, location, and number, etc.), the coal quality data can be traced, which is convenient for quality management or traceability. According to the analysis report, coal mining enterprises can reasonably plan the mining, storage, and sales of coal, so as to maximize economic benefits.

[0048] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A coal quality structure data acquisition and analysis system, characterized in that, Including: Information acquisition module: Determine several key points in the coal mine, deploy scanning devices at the key points of the coal mine, and then acquire the structural information of the coal quality. Parameter acquisition module: Perform micro-fission analysis on the structural information of the coal quality, and then acquire the microscopic structure parameters of the coal quality. Parameter analysis module: Analyze the microscopic structure parameters of the coal quality, and then determine the characteristic parameters of several coal samples. Parameter determination module: Determine the parameters for coal sample classification based on the characteristic parameters of all coal samples and a preset model. Report generation module: Acquire the coal quality-related information of the coal in the coal mine based on a preset sensor group, combine the parameters for coal sample classification to determine the classification information of the coal in the coal mine, and generate a coal quality analysis report.

2. The coal quality structure data acquisition and analysis system according to claim 1, characterized in that The information acquisition module includes: Data analysis unit: Determine the exploration data of the coal quality based on the preset geological exploration report of the coal mine and the formation analysis data. First analysis unit: Perform a first analysis on the exploration data of the coal quality, and then determine several key coal seams. Second analysis unit: Perform a second analysis on the exploration data of the coal quality, and then determine the key points of each key coal seam. Requirement analysis unit: Acquire the preset production requirements and coal quality monitoring requirements of the coal mine, perform requirement analysis, and then determine several types of coal quality data to be collected. Device determination unit: Determine the scanning device corresponding to each type of coal quality data based on a preset type-device database. Data acquisition unit: Deploy scanning devices at the key points of each key coal seam, and collect the structural data of the key points of each coal mine.

3. The coal quality structure data acquisition and analysis system according to claim 1, characterized in that, The parameter acquisition module includes: Characteristic acquisition unit: Perform characteristic analysis on the structural information of the coal quality, and then acquire the characteristics of the structural information of the coal quality. Parameter acquisition unit: Determine the micro-fission analysis method based on the characteristics of the structural information of the coal quality and a preset characteristic-method database, and then acquire the microscopic structure parameters of the coal quality.

4. A coal quality structure data acquisition and analysis system according to claim 1, characterized in that, The parameter acquisition unit includes: Information disassembling sub-unit: Disassemble the structural information of the coal quality based on a preset segmentation algorithm, and then disassemble the structural information of the coal quality into several information units. Unit classification sub-unit: Classify all information units based on a preset classification algorithm, and then acquire the information unit groups corresponding to each type of information unit. First analysis sub-unit: Analyze the first information unit group based on a first preset analysis method, and then extract several first structural parameters. Second analysis sub-unit: Analyze the second information unit group based on a second preset analysis method, and then extract several second structural parameters. Third analysis sub-unit: Analyze the third information unit group based on a third preset analysis method, and then extract several third structural parameters. Parameter determination sub-unit: Determine the first structural parameters, the second structural parameters, and the third structural parameters as the microscopic structure parameters of the coal quality.

5. The coal quality structure data acquisition and analysis system according to claim 1, characterized in that The first preset analysis method is a pore and fracture analysis method, the second preset analysis method is a mineral composition analysis method, and the third preset analysis method is a coal particle structure analysis method.

6. The coal quality structure data acquisition and analysis system according to claim 5, characterized in that The parameter analysis module includes: Algorithm determination unit: Determine the feature extraction algorithm corresponding to the structural parameters of each type of information unit group based on a preset type - algorithm database; Feature extraction unit: Extract features from the microscopic structural parameters of coal quality based on the feature extraction algorithm corresponding to the structural parameters of each type of information unit group, and then determine the feature parameters of several coal samples.

7. A coal quality structure data acquisition and analysis system according to claim 1, characterized in that, Report generation module, including: Obtain the coal quality - related information of the coal in the coal mine based on a preset sensor group and analyze it, and then determine the coal quality - related parameters of the coal samples in the coal mine; Determine the grading coefficient of the coal quality of the coal samples in the coal mine based on the parameters of coal sample grading and the coal quality - related parameters of the coal samples in the coal mine: According to the grading coefficient of the coal quality of the coal samples in the coal mine and a preset grading threshold, divide the grades of the coal samples, and then determine the grades of several coal samples; Generate a coal quality analysis report based on the grades of the coal samples and the corresponding coal quality - related parameters of the coal samples.

8. The coal quality structure data acquisition and analysis system according to claim 1, characterized in that Coal quality analysis report, including: basic information of coal samples, analysis of coal sample properties, and coal quality grading information.

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