Field quality evaluation method and system for vein quartz ore for high purity quartz

Abstract

The present invention relates to the field of mineral resource technology, specifically to a method and system for evaluating the quality of vein quartz ore in the field for high-purity quartz, comprising the following steps: using an image acquisition device to photograph vein quartz ore, analyzing image data, identifying and marking impurities on the surface of the ore by identifying the color and texture information of the ore surface, and generating surface impurity marking information. In the present invention, by analyzing the image data of the vein quartz ore, various impurities on the surface of the ore are detected and identified, and the ore size is evaluated in combination with the identification of edge information. By analyzing the reflection and refraction data of the ore under various spectra, an accurate evaluation of the transparency of the ore is achieved, the density of the ore is calculated, and the compressive strength is measured, the physical properties of the ore are evaluated, and the purity index of the ore is calculated according to the relationship between the various properties of the ore and the purity, thereby achieving a comprehensive quality evaluation of the vein quartz ore under field conditions.

Description

Technical Field

[0001] The invention relates to the technical field of mineral resources, in particular to a field quality evaluation method and system for vein quartz ore for high-purity quartz. Background Art

[0002] The field of mineral resource evaluation technology focuses on the detection, evaluation and classification of geological and mineral resources. It combines knowledge from multiple disciplines such as geology, mineralogy, chemistry and geophysics, and combines on-site exploration with laboratory analysis to evaluate the type, distribution, reserves and quality of mineral resources, including geochemical analysis, mineral identification, X-ray diffraction, optical and electron microscope observations, aiming to provide a scientific basis for the mining and utilization of minerals, ensure the effective use of resources, evaluate environmental impacts and economic value, and support sustainable mining development.

[0003] Among them, the field quality evaluation method of vein quartz ore for high-purity quartz is used to directly analyze and grade the quality of vein quartz ore under field conditions, to realize the detection of high-purity quartz, and to determine the purity and impurity content of quartz through geological surveys and chemical analysis of mineral samples, to ensure the application quality of quartz materials in high-tech industries, including the production of optical fibers, semiconductors and optoelectronic products, to effectively guide field mining operations, optimize resource extraction and utilization, and reduce unnecessary processing costs and environmental damage.

[0004] Traditional vein quartz ore quality evaluation methods rely on geological surveys and laboratory analysis, including geochemical analysis and X-ray diffraction methods to evaluate mineral resources. Samples need to be brought back to the laboratory for analysis, which is costly and inefficient. Its application in field environments is limited and it cannot provide instant ore evaluation, resulting in mining decisions that cannot be adjusted in real time according to ore quality, leading to waste of resources, failure to identify low-quality ores in a timely manner, resulting in unnecessary mining operations, increased processing costs and environmental damage, and a lack of ability to combine multiple properties with the actual application quality requirements of the ore when evaluating the optical and physical properties of the ore. Summary of the invention

[0005] In order to solve the technical problem that it is difficult to evaluate the quality of ore in the field in the prior art, the embodiment of the present invention provides a method and system for evaluating the quality of vein quartz ore in the field for high-purity quartz. The technical solution is as follows:

[0006] On the one hand, a method for evaluating the quality of vein quartz ore in the field for high-purity quartz is provided, the method comprising:

[0007] S1: Use image acquisition equipment to photograph vein quartz ore, analyze image data, identify and mark impurities on the ore surface by identifying color and texture information on the ore surface, and generate surface impurity marking information;

[0008] S2: According to the surface impurity mark information, by analyzing the edge information in the image data, identifying the ore particle boundary and measuring the diameter and geometric shape of the ore, analyzing the size distribution characteristics of the vein quartz ore, and generating ore size information;

[0009] S3: Based on the ore size information, by analyzing the reflection and absorption of the ore under various light sources, measuring the surface reflectivity and transmittance of the ore, evaluating the transparency of the ore, and generating optical property analysis results;

[0010] S4: Based on the optical property analysis results, the volume and weight information of the ore is measured, the density of the ore is calculated, the stress response is recorded in combination with the pressure sensor, the compressive strength of the ore is evaluated, and an ore density data set is generated;

[0011] S5: Based on the ore density data set, according to the relationship between surface texture, surface impurities, ore size, optical properties, ore density, compressive resistance and ore purity, calculate the purity index of the ore, evaluate the quality grade of the ore, and generate an ore quality evaluation result.

[0012] As a further solution of the present invention, the surface impurity marking information includes color differences, texture features, and impurity type identification results of the ore surface; the ore size information includes the ore's geometric shape, size information, and particle shape heterogeneity measurement; the optical property analysis results include the ore's surface reflectivity, ore transmittance, and transparency evaluation data; the ore density data set includes ore volume measurement results, density calculation values, and stress response characteristic data; and the ore quality evaluation results include ore quality index, correlation data set, and ore characteristic data.

[0013] As a further solution of the present invention, an image acquisition device is used to photograph vein quartz ore, analyze image data, and identify and mark impurities on the surface of the ore by identifying the color and texture information of the surface of the ore. The steps of generating surface impurity marking information are specifically as follows:

[0014] S101: Using an image acquisition device, photographing the vein quartz ore at multiple angles, acquiring surface image data of the vein quartz ore, and generating an ore image data set;

[0015] S102: Based on the ore image data set, analyzing the image data, identifying the texture features and color information of the ore surface, and generating color texture feature data;

[0016] S103: Based on the color texture feature data, by comparing with the surface texture and color information of multiple known impurities, the impurities on the surface of the ore are identified, the positions and types of the identified impurities are marked, and surface impurity marking information is generated.

[0017] As a further solution of the present invention, according to the surface impurity marking information, by analyzing the edge information in the image data, identifying the ore particle boundaries and measuring the diameter and geometric shape of the ore, analyzing the size distribution characteristics of the vein quartz ore, the steps of generating the ore size information are specifically as follows:

[0018] S201: Based on the surface impurity marking information, by identifying edge information in the ore image data, marking boundaries of multiple ore particles, and generating a particle boundary recognition result;

[0019] S202: Based on the particle boundary recognition result, measuring the diameters and geometric shapes of multiple particles, recording the size data, calculating the particle size distribution and morphology index, and generating geometric shape data;

[0020] S203: Based on the geometric shape data, analyze the size distribution characteristics of the vein quartz ore, evaluate the uniformity of the ore size, and generate ore size information.

[0021] As a further solution of the present invention, based on the ore size information, by analyzing the reflection and absorption of the ore under various light sources, measuring the surface reflectivity and transmittance of the ore, evaluating the transparency and optical purity of the ore, and generating the optical property analysis results, the specific steps are:

[0022] S301: Based on the ore size information, irradiate the ore using multiple light sources, record reflection images and light transmission images of the ore under multiple spectra, and generate reflection and light transmission data;

[0023] S302: Based on the reflected light transmittance data, calculate the light transmittance of the ore under multiple spectra, record the spectral absorption characteristics, and generate the optical response characteristics of the ore;

[0024] S303: Based on the optical response characteristics of the ore, considering the correlation between the spectral data and the physical size of the ore, evaluating the transparency of the ore, and generating optical characteristic analysis results.

[0025] As a further solution of the present invention, the specific formula for calculating the light transmittance of the ore under multiple spectra is:

[0026] ,

[0027] in, Represents the light transmittance of the ore, which is the ratio of the intensity of light after passing through the ore to the initial light intensity. Represents the intensity of light after passing through the ore. Represents the initial light intensity, which is the reference light intensity in the transmittance calculation. is the base of the natural logarithm, used to describe the exponential decay process, Represents the material's absorption coefficient, reflecting the mineral's ability to absorb light. This coefficient quantifies the mineral's ability to absorb light. Represents the thickness of the ore material.

[0028] As a further solution of the present invention, based on the optical property analysis results, the volume and weight information of the ore is measured, the density of the ore is calculated, the stress response is recorded in combination with the pressure sensor, and the compressive strength of the ore is evaluated. The steps of generating the ore density data set are specifically as follows:

[0029] S401: Based on the optical characteristic analysis result, measure the volume and weight of the ore sample to generate volume weight data;

[0030] S402: Calculate the density of the vein quartz ore sample based on the volume weight data to generate density calculation data;

[0031] S403: Based on the density calculation data, using a pressure sensor, record the stress response state of the ore under various pressures, evaluate the compressive strength of the ore, and generate an ore density data set.

[0032] As a further solution of the present invention, based on the ore density data set, according to the relationship between surface texture, surface impurities, ore size, optical properties, ore density, compressive performance and ore purity, the purity index of the ore is calculated, and the quality grade of the ore is evaluated. The steps of generating the ore quality evaluation result are specifically as follows:

[0033] S501: extracting surface texture, surface impurities, ore size, reflection and transmittance measurement results, and compressive performance data of the vein quartz ore sample based on the ore density data set to generate quality analysis data;

[0034] S502: Based on the quality analysis data, according to the relationship between the multiple characteristics and the purity of the ore, the purity index of the ore is calculated to generate a quality index calculation result;

[0035] S503: Based on the quality index calculation result, the commercial and industrial values ​​of ores of various purities are considered, the quality grade of the ore is evaluated, and an ore quality evaluation result is generated.

[0036] As a further solution of the present invention, the specific formula for evaluating the quality grade of the ore is:

[0037] ,

[0038] in, Represents the comprehensive quality grade of the ore. Indicates the ore purity index, Indicates the compressive performance index of the ore. Represents the ore size distribution uniformity index, Indicates the optical property index of the ore, is the weight of the purity index, is the weight of the compression performance index, is the weight of the size distribution index, is the weight of the optical property index.

[0039] On the other hand, a field quality evaluation system for vein quartz ore for high-purity quartz is provided, which is applied to a field quality evaluation method for vein quartz ore for high-purity quartz, and the system comprises:

[0040] The surface image acquisition module uses image acquisition equipment to take multi-angle photos of vein quartz ore, analyze the color and texture information of the ore sample, and generate ore image data;

[0041] The surface impurity detection module marks surface impurities based on the ore image data and generates surface impurity marking information by analyzing the color and texture information of the ore surface;

[0042] The ore size measurement module analyzes ore image information based on the surface impurity mark information, identifies the boundaries of ore particles, measures the diameters and geometric shapes of multiple ores, and generates ore size information;

[0043] The optical property analysis module measures the surface reflectivity and transmittance based on the ore size information, analyzes the reflection and absorption of the ore under various light sources, evaluates the transparency of the ore, and generates optical property information;

[0044] The physical property analysis module measures the volume and weight of the ore based on the optical property information, calculates the density of the ore, and combines with the pressure sensor to analyze the response state of the ore under various pressures to evaluate the compressive strength of the ore and generate an ore density data set;

[0045] The purity calculation module calculates the purity index of the ore based on the ore density data set and the relationship between various characteristic parameters of the ore and the ore purity, evaluates the quality grade of the ore, and generates an ore quality evaluation result.

[0046] The beneficial effects brought about by the technical solution provided by the embodiment of the present invention include at least:

[0047] By analyzing the image data of vein quartz ore, various impurities on the ore surface are detected and identified, and the ore size is evaluated by combining the identification of edge information. By analyzing the reflection and refraction data of the ore under various spectra, the transparency of the ore is accurately evaluated, the density of the ore is calculated, and the compressive strength is measured. The physical properties of the ore are evaluated, and the purity index of the ore is calculated based on the relationship between the various properties of the ore and its purity, thus achieving a comprehensive quality evaluation of vein quartz ore under field conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0049] Figure 1 It is a schematic diagram of the workflow of the present invention;

[0050] Figure 2 This is a detailed flow chart of S1 of the present invention;

[0051] Figure 3 This is a detailed flow chart of S2 of the present invention;

[0052] Figure 4 This is a detailed flow chart of S3 of the present invention;

[0053] Figure 5 This is a detailed flow chart of S4 of the present invention;

[0054] Figure 6 This is a detailed flow chart of S5 of the present invention;

[0055] Figure 7 It is a system flow chart of the present invention. DETAILED DESCRIPTION

[0056] The technical solution of the present invention is described below in conjunction with the accompanying drawings.

[0057] In the embodiments of the present invention, words such as "exemplarily" and "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "example" in the present invention should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of the word "example" is intended to present the concept in a specific way. In addition, in the embodiments of the present invention, the meaning expressed by "and / or" can be both, or it can be either of the two.

[0058] In the embodiments of the present invention, "image" and "picture" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same. "of", "corresponding, relevant" and "corresponding" can sometimes be used interchangeably. It should be noted that when the difference between them is not emphasized, the meanings they intend to express are the same.

[0059] In the embodiments of the present invention, sometimes a subscript such as W1 may be written as a non-subscript such as W1. When the difference is not emphasized, the meanings to be expressed are the same.

[0060] In order to make the technical problems, technical solutions and advantages to be solved by the present invention more clear, a detailed description will be given below with reference to the accompanying drawings and specific embodiments.

[0061] The embodiment of the present invention provides a method for evaluating the quality of vein quartz ore in the field for high-purity quartz. Figure 1 The flow chart of the field quality evaluation method for vein quartz ore for high-purity quartz shown in the figure can include the following steps:

[0062] S1: Use image acquisition equipment to photograph vein quartz ore, analyze image data, identify and mark impurities on the ore surface by identifying color and texture information on the ore surface, and generate surface impurity marking information;

[0063] S2: Based on the surface impurity marking information, by analyzing the edge information in the image data, identifying the ore particle boundaries and measuring the diameter and geometric shape of the ore, analyzing the size distribution characteristics of the vein quartz ore, and generating ore size information;

[0064] S3: Based on the ore size information, by analyzing the reflection and absorption of the ore under various light sources, the surface reflectivity and transmittance of the ore are measured, the transparency of the ore is evaluated, and the optical property analysis results are generated;

[0065] S4: Based on the results of optical property analysis, the volume and weight information of the ore are measured, the density of the ore is calculated, and the stress response is recorded by the pressure sensor to evaluate the compressive strength of the ore and generate an ore density data set;

[0066] S5: Based on the ore density data set, according to the relationship between surface texture, surface impurities, ore size, optical properties, ore density, compressive resistance and ore purity, the purity index of the ore is calculated, the quality grade of the ore is evaluated, and the ore quality evaluation result is generated.

[0067] Surface impurity marking information includes color differences, texture features, and impurity type identification results of the ore surface. Ore size information includes the ore's geometric shape, size information, and particle shape heterogeneity measurement. Optical property analysis results include the ore's surface reflectivity, ore transmittance, and transparency evaluation data. Ore density data sets include ore volume measurement results, density calculation values, and stress response characteristic data. Ore quality evaluation results include ore quality index, correlation data set, and ore characteristic data.

[0068] See also Figure 2, use image acquisition equipment to shoot vein quartz ore, analyze image data, identify and mark impurities on the ore surface by identifying the color and texture information on the ore surface, and generate surface impurity marking information in the following steps:

[0069] S101: Using an image acquisition device, photographing the vein quartz ore at multiple angles, acquiring surface image data of the vein quartz ore, and generating an ore image data set;

[0070] In sub-step S101, based on the on-site conditions, the parameters of the image acquisition equipment, including ISO sensitivity, shutter speed and focal length, are set to adapt to different external lighting conditions and the reflective characteristics of the ore surface to ensure that high-quality image data is obtained. The equipment is fixed on a tripod and adjusted to multiple angles to ensure that a full-range image of the ore is captured from the top, side and different inclinations. A high-resolution image sensor is used to capture subtle surface textures. During the shooting process, the light source is gradually adjusted, and soft light and reflective panels are used to reduce shadows and highlights to improve the uniformity and recognizability of the image. After shooting, image processing software is used to perform preliminary color correction and contrast enhancement, and subsequent image analysis is performed. All image data obtained from the shooting are summarized into an ore image data set to provide a data basis for the next step of texture and color analysis.

[0071] S102: Based on the ore image data set, analyzing the image data, identifying the texture features and color information of the ore surface, and generating color texture feature data;

[0072] In sub-step S102, a computer vision algorithm is used to analyze the image, a high-pass filter is used to enhance the texture edges in the image, and the color features of the ore are extracted through color space conversion, including converting the RGB color space into the HSV color space to distinguish different color levels. Texture analysis algorithms such as the gray-level co-occurrence matrix are used to quantify the texture information of the image. The GLCM algorithm describes the roughness, directionality and uniformity of the image texture by calculating the frequency of a specific combination of distances and angles between pixel points in the image. The color and texture information is integrated to generate color texture feature data. The data provides an accurate scientific basis for identifying the type and distribution of impurities in the ore.

[0073] S103: Based on the color texture feature data, by comparing with the surface texture and color information of multiple known impurities, the impurities on the surface of the ore are identified, the positions and types of the identified impurities are marked, and surface impurity marking information is generated;

[0074] In the above content, the formula is used , using color texture feature data to identify impurities on the surface of ore;

[0075] In the formula, Representative The impurity recognition score of feature points is and The sample ore is The texture and color values ​​of feature points, and are the reference texture and color values ​​corresponding to the impurities;

[0076] Detailed explanation of the formula and the process of formula calculation and derivation:

[0077] Assume that the sample ore texture value of a feature point , color value , and the reference texture value of known impurities , reference color value , calculate the degree of difference:

[0078] ,

[0079] ,

[0080] The result shows that the overall difference in texture and color between the feature point and the known impurities is 50.99. Combined with the set threshold, it is determined whether the point is an impurity. By applying it to all feature points on the ore surface, the impurity position and type are marked.

[0081] See also Figure 3 According to the surface impurity marking information, by analyzing the edge information in the image data, identifying the ore particle boundaries and measuring the diameter and geometry of the ore, analyzing the size distribution characteristics of the vein quartz ore, the steps for generating ore size information are as follows:

[0082] S201: Based on the surface impurity marking information, by identifying the edge information in the ore image data, marking the boundaries of multiple ore particles, and generating a particle boundary recognition result;

[0083] In sub-step S201, an edge detection algorithm, such as the Canny algorithm, is used to process the ore image. The position of the boundary is determined by calculating the gradient of the image. The threshold parameters of the algorithm are adjusted to adapt to images of different brightness and contrast to ensure that the particle boundary is accurately captured. The image is filtered to remove noise and enhance the edge features of the particles in the image. The boundary identified by the algorithm is displayed through a graphical interface for the operator to check and fine-tune to ensure the correct marking of the boundary. The boundary of the ore particle is accurately marked to form a particle boundary recognition result. The result records the outer contour of each ore particle, providing the necessary basic data for subsequent size measurement and shape analysis.

[0084] S202: Based on the particle boundary recognition result, measuring the diameter and geometric shape of multiple particles, recording the size data, calculating the particle size distribution and morphology index, and generating geometric shape data;

[0085] In sub-step S202, the particle boundary recognition results are used to apply image measurement tools, such as ImageJ software, to measure the diameter and geometric shape of each particle, including using an image ruler to calibrate the size, selecting a suitable measurement tool to directly measure the maximum and minimum diameters of each particle on the image, and using an ellipse fitting method to estimate the shape of the particle, thereby calculating the morphological index. The morphological index is calculated through the major and minor axes of the particle to describe the regularity and ellipticity of the particle. After the measurement data are summarized, the statistical analysis software is used to calculate the distribution of particle size and the mean and standard deviation of the morphological index and other statistical parameters. The generated geometric shape data includes detailed information on the size and morphology of each particle, providing a scientific basis for evaluating the quality and suitability of the ore.

[0086] S203: Analyze the size distribution characteristics of the vein quartz ore based on the geometric shape data, evaluate the uniformity of the ore size, and generate ore size information;

[0087] In sub-step S203, based on the geometric shape data, statistical analysis methods such as variance analysis are used to evaluate the size distribution characteristics of vein quartz ore. During the operation, geometric shape data, including the size and morphological index of the particles, are imported, the number distribution of particles in each size category and the distribution pattern of each morphological index are calculated, the data are analyzed to determine whether the size distribution of the ore is uniform and whether there are significantly small or large particle groups. Graphical representations such as histograms and box plots are used to display the distribution of size and morphological indexes, and the mean, median, mode, skewness and kurtosis statistical indicators of the size data are calculated. The generated ore size information displays the overall and detailed size distribution characteristics of the ore, providing a basis for further quality evaluation and processing decisions.

[0088] See also Figure 4 Based on the ore size information, by analyzing the reflection and absorption of the ore under various light sources, measuring the surface reflectivity and transmittance of the ore, evaluating the transparency and optical purity of the ore, the steps to generate the optical property analysis results are as follows:

[0089] S301: Based on the ore size information, the ore is illuminated by using multiple light sources, and the reflection image and the light transmission image of the ore under multiple spectra are recorded to generate reflection and light transmission data;

[0090] In sub-step S301, multiple light sources, including ultraviolet light, visible light and infrared light, are configured to irradiate the ore, and a multi-wavelength spectral imaging system is used to record the reflection and transmittance images of the ore, capture optical data at multiple wavelengths, and capture images synchronously to ensure that the images at each wavelength have the same spatial alignment. After irradiation, the irradiation conditions are recorded, including light source intensity, irradiation angle, irradiation time, and the specific placement position and angle of the ore to ensure the repeatability of the experiment. The captured images are pre-processed by image processing software, including correction, denoising and enhancement, to generate reflection and transmittance data of spectral reflection and transmittance information, and the data provides a basis for further optical property analysis.

[0091] S302: Based on the reflection and light transmission data, the light transmittance of the ore under various spectra is calculated, the spectral absorption characteristics are recorded, and the optical response characteristics of the ore are generated;

[0092] The specific formula for calculating the transmittance of minerals under various spectra is:

[0093] ,

[0094] in, Represents the light transmittance of the ore, which is the ratio of the intensity of light after passing through the ore to the initial light intensity. Represents the intensity of light after passing through the ore. Represents the initial light intensity, which is the reference light intensity in the transmittance calculation. is the base of the natural logarithm, used to describe the exponential decay process, Represents the material's absorption coefficient, reflecting the mineral's ability to absorb light. This coefficient quantifies the mineral's ability to absorb light. Represents the thickness of the ore material.

[0095] formula:

[0096] ;

[0097] Detailed explanation of the formula and the process of formula calculation and derivation:

[0098] The formula calculates the transmittance ratio of light after it passes through the ore based on the law of light intensity attenuation. The result reflects the ore's light absorption and transmittance properties.

[0099] Parameter meaning and setting value:

[0100] is the light intensity after passing through the ore, assumed to be 200 units;

[0101] is the initial light intensity, assumed to be 1000 units;

[0102] is the absorption coefficient of the material, assumed to be 0.005 ;

[0103] is the thickness of the ore material, assumed to be 10 cm;

[0104] is the base of natural logarithms, approximately equal to 2.71828;

[0105] Substitute the parameters into the formula for calculation:

[0106] ;

[0107] The result 0.19025 indicates that the transmittance is 19.025%, which indicates that the ore has a high light absorption capacity and is suitable for applications where light transmission needs to be limited. The numerical results show that the ore has a strong absorption characteristic for light of a specific wavelength.

[0108] S303: Based on the optical response characteristics of the ore, considering the correlation between the spectral data and the physical size of the ore, evaluating the transparency of the ore, and generating optical characteristic analysis results;

[0109] In sub-step S303, the transparency of the ore is evaluated, including combining the spectral absorption characteristics with the ore size data, and calculating the transparency through a mathematical model. The model takes into account the light scattering and absorption changes caused by the ore size when the light passes through the ore. By adjusting the model parameters, such as the average size and shape factor of the ore, the transparency is quantitatively evaluated. The transparency data of ores of different sizes are statistically analyzed to evaluate their distribution and uniformity. In order to ensure the accuracy of the analysis, the experiment is repeated to verify the repeatability and stability of the results. The generated optical property analysis results provide a scientific basis for the quality rating and further application of the ore, and record the correlation between the ore transparency and physical size and its impact on the transparency.

[0110] See also Figure 5 Based on the results of optical property analysis, the volume and weight information of the ore are measured, the density of the ore is calculated, and the stress response is recorded by the pressure sensor to evaluate the compressive strength of the ore. The specific steps for generating the ore density data set are as follows:

[0111] S401: Based on the optical characteristic analysis results, the volume and weight of the ore sample are measured to generate volume weight data;

[0112] In sub-step S401, an electronic scale and a volume measuring device are set up to measure the weight and volume of the ore sample, including placing the ore sample on the electronic scale, recording the weight, and determining the volume using the liquid displacement method, that is, immersing the ore in a known volume of liquid, measuring the volume increment of the liquid displacement, accurately determining the volume of irregularly shaped ores, ensuring the accuracy and repeatability of the measurement data, recording the weight and volume data of each sample during the operation, and calibrating and error analyzing the data to ensure the accuracy of the results, and generating volume weight data. The data records the physical parameters of each ore sample and provides the necessary basic information for density calculation.

[0113] S402: Calculate the density of the vein quartz ore sample based on the volume weight data to generate density calculation data;

[0114] In sub-step S402, the density calculation formula ρ=m / V, where ρ is density, m is mass, and V is volume, is used to calculate the density of each ore sample, including inputting the mass and volume data of each sample into the calculation system, using software to automatically calculate the density, batch processing all sample data to ensure the efficiency and accuracy of the calculation process, and performing statistical analysis on the calculation results, including calculating the average density, variance, and standard deviation, and evaluating the density variability between samples. The generated density calculation data includes detailed density values ​​of each sample and its statistical analysis results, which provide key scientific data for evaluating the quality characteristics of the ore.

[0115] S403: Based on the density calculation data, using a pressure sensor, recording the stress response state of the ore under various pressures, evaluating the compressive strength of the ore, and generating an ore density data set;

[0116] In sub-step S403, the density calculation data is used in conjunction with a pressure sensor to record and analyze the stress response of the ore sample under various pressures. During the operation, the ore sample is fixed in the experimental press, the pressure is gradually increased, and the stress data is recorded in real time through the connected pressure sensor. The pressure and stress response data are automatically collected using a data acquisition system to evaluate the compressive strength of the ore, including calculating the stress-strain curve of the ore under different pressures. The compressive resistance and brittleness of the ore are evaluated by the slope and fracture point of the curve. The generated ore density data set includes the analysis results of the ore compressive characteristics, such as compressive strength, elastic modulus and fracture pressure. The data is crucial for understanding the physical properties and applicability of the ore.

[0117] See also Figure 6 Based on the ore density data set, according to the relationship between surface texture, surface impurities, ore size, optical properties, ore density, compressive performance and ore purity, the purity index of the ore is calculated to evaluate the quality grade of the ore. The specific steps for generating the ore quality evaluation result are as follows:

[0118] S501: Based on the ore density data set, extract the surface texture, surface impurities, ore size, reflection and transmittance measurement results, and compressive performance data of the vein quartz ore sample to generate quality analysis data;

[0119] In sub-step S501, various data from previous analyses are integrated and extracted, including the surface texture of the ore obtained through image analysis technology, surface impurity information identified through high-precision scanning and image processing software, ore size data recorded through stereo measurement technology, and reflectivity and transmittance measured by a spectrometer. The compressive performance data is obtained through the stress-strain curve recorded by the pressure testing device. These data are summarized and pre-processed through a data management system to ensure data consistency and accuracy. Statistical analysis software is used for data fusion and feature extraction to generate comprehensive quality analysis data. The data set includes detailed information reflecting the key factors of ore quality, providing a comprehensive scientific basis for the next step of quality assessment.

[0120] S502: Based on the quality analysis data, according to the relationship between the multiple characteristics and the purity of the ore, the purity index of the ore is calculated to generate a quality index calculation result;

[0121] In sub-step S502, a multivariate statistical analysis method is applied to calculate the purity index of the ore. The principal component analysis and linear regression model are used to explore the relationship between different ore characteristics and purity. The surface texture, impurity information, size data, and optical and physical performance parameters of the ore are used as input variables. The PCA method is used to reduce the dimension and extract the main features. Based on the main features, a linear regression model is constructed to predict the purity index of the ore. By adjusting the parameters of the model, the accuracy of the prediction is optimized. The generated quality index calculation results provide a quantitative basis for further classification and evaluation of the ore, and provide a scientific basis for the judgment of market value.

[0122] S503: Based on the quality index calculation result, considering the commercial and industrial value of ores of various purities, evaluating the quality grade of the ore, and generating an ore quality evaluation result;

[0123] The specific formula for evaluating the quality grade of ore is:

[0124] ,

[0125] in, Represents the comprehensive quality grade of the ore. Indicates the ore purity index, Indicates the compressive performance index of the ore. Represents the ore size distribution uniformity index, Indicates the optical property index of the ore, is the weight of the purity index, is the weight of the compression performance index, is the weight of the size distribution index, is the weight of the optical property index.

[0126] formula:

[0127] ;

[0128] Detailed explanation of the formula and the process of formula calculation and derivation:

[0129] The formula is used to calculate the comprehensive quality grade of the ore, and the result is used for ore quality rating;

[0130] Parameter meaning and setting value:

[0131] is the ore purity index, assumed to be 0.85;

[0132] is the compressive performance index of ore, which is assumed to be 0.75, and is used to evaluate the ability of ore to resist deformation and crushing when subjected to stress;

[0133] is the ore size distribution uniformity index, assumed to be 0.65, describing the uniform distribution of ore particle size;

[0134] is the optical property index of the ore, assumed to be 0.90, reflecting the reflection and transmittance of the ore under different light sources;

[0135] are the weight coefficients of the corresponding indicators, assuming to be 0.25, 0.25, 0.25, and 0.25;

[0136] Substitute the parameters into the formula for calculation:

[0137] ;

[0138] The result of 0.7875 indicates that the comprehensive quality grade of the ore is at a high level, reflecting that the ore has good comprehensive performance in purity, compressive resistance, size uniformity and optical properties. The result is used to grade the quality of the ore, which affects the market value and applicability of the ore.

[0139] See also Figure 7 A field quality evaluation system for vein quartz ore for high-purity quartz, the field quality evaluation system for vein quartz ore for high-purity quartz is used to execute the field quality evaluation method for vein quartz ore for high-purity quartz, the system comprises:

[0140] The surface image acquisition module uses image acquisition equipment to take multi-angle photos of vein quartz ore, analyze the color and texture information of the ore sample, and generate ore image data;

[0141] The surface impurity detection module is based on the ore image data, by analyzing the color and texture information of the ore surface, marking the surface impurities and generating surface impurity marking information;

[0142] The ore size measurement module analyzes ore image information based on surface impurity marking information, identifies the boundaries of ore particles, measures the diameter and geometry of multiple ores, and generates ore size information;

[0143] The optical property analysis module is based on the ore size information. By analyzing the reflection and absorption of the ore under various light sources, the surface reflectivity and transmittance are measured, the transparency of the ore is evaluated, and the optical property information is generated.

[0144] The physical property analysis module measures the volume and weight of the ore based on the optical property information, calculates the density of the ore, and combines with the pressure sensor to analyze the response state of the ore under various pressures to evaluate the compressive strength of the ore and generate an ore density data set;

[0145] The purity calculation module is based on the ore density data set and the relationship between the ore's various characteristic parameters and ore purity. It calculates the ore's purity index, evaluates the ore's quality grade, and generates ore quality evaluation results.

[0146] The above embodiments can be implemented in whole or in part by software, hardware (such as circuits), firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When a computer instruction or computer program is loaded or executed on a computer, a process or function according to an embodiment of the present invention is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a tape), an optical medium (for example, a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0147] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding.

[0148] In the present invention, "at least one" means one or more, and "plurality" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, and c can be single or multiple.

[0149] It should be understood that in various embodiments of the present invention, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0150] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of the present invention.

[0151] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the above-described equipment, devices and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0152] In the several embodiments provided by the present invention, it should be understood that the disclosed devices, apparatuses and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another device, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0153] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0154] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0155] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of various embodiments of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc., various media that can store program codes.

[0156] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art who is familiar with the technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention should be based on the protection scope of the claims.

Claims

1. A method for evaluating the quality of vein quartz ore in the field for high-purity quartz, characterized in that: The method comprises: Use image acquisition equipment to photograph vein quartz ore, analyze image data, identify and mark impurities on the ore surface by identifying color and texture information on the ore surface, and generate surface impurity marking information; According to the surface impurity mark information, by analyzing the edge information in the image data, identifying the ore particle boundaries and measuring the diameter and geometric shape of the ore, analyzing the size distribution characteristics of the vein quartz ore, and generating ore size information; Based on the ore size information, by analyzing the reflection and absorption of the ore under various light sources, measuring the surface reflectivity and transmittance of the ore, evaluating the transparency of the ore, and generating optical property analysis results; Based on the optical property analysis results, the volume and weight information of the ore is measured, the density of the ore is calculated, and the stress response is recorded in combination with the pressure sensor to evaluate the compressive strength of the ore and generate an ore density data set; Based on the ore density data set, according to the relationship between surface texture, surface impurities, ore size, optical properties, ore density, compressive resistance and ore purity, the purity index of the ore is calculated, the quality grade of the ore is evaluated, and the ore quality evaluation result is generated; Wherein, based on the ore density data set, according to the relationship between surface texture, surface impurities, ore size, optical properties, ore density, compressive performance and ore purity, the purity index of the ore is calculated, the quality grade of the ore is evaluated, and the steps of generating the ore quality evaluation result are specifically as follows: Extracting surface texture, surface impurities, ore size, reflection and transmittance measurement results, and compressive performance data of vein quartz ore samples based on the ore density data set to generate quality analysis data; Based on the quality analysis data, according to the relationship between the multiple characteristics and the purity of the ore, the purity index of the ore is calculated to generate a quality index calculation result; Based on the quality index calculation result, considering the commercial and industrial value of ores of various purities, the quality grade of the ore is evaluated to generate an ore quality evaluation result; The specific formula for evaluating the quality grade of the ore is: ， in, Represents the comprehensive quality grade of the ore. Indicates the ore purity index, Indicates the compressive performance index of the ore. Represents the ore size distribution uniformity index, Indicates the optical property index of the ore, is the weight of the purity index, is the weight of the compression performance index, is the weight of the size distribution index, is the weight of the optical property index.

2. The method for evaluating the quality of vein quartz ore for high-purity quartz according to claim 1, characterized in that: The surface impurity marking information includes the color difference, texture characteristics, and impurity type identification results of the ore surface; the ore size information includes the geometric shape, size information, and particle shape heterogeneity measurement of the ore; the optical property analysis results include the surface reflectivity, ore transmittance, and transparency evaluation data of the ore; the ore density data set includes the ore volume measurement results, density calculation values, and stress response characteristic data; the ore quality evaluation results include the ore quality index, correlation data set, and ore characteristic data.

3. The field quality evaluation method of vein quartz ore for high-purity quartz according to claim 1, characterized in that: Use image acquisition equipment to photograph vein quartz ore, analyze image data, identify and mark impurities on the ore surface by identifying the color and texture information on the ore surface, and generate surface impurity marking information in the following steps: Using image acquisition equipment, taking multi-angle photos of the vein quartz ore, collecting surface image data of the vein quartz ore, and generating an ore image data set; Based on the ore image data set, analyzing the image data, identifying the texture features and color information of the ore surface, and generating color texture feature data; Based on the color texture feature data, by comparing with the surface texture and color information of multiple known impurities, impurities on the surface of the ore are identified, the positions and types of the identified impurities are marked, and surface impurity marking information is generated.

4. The field quality evaluation method of vein quartz ore for high-purity quartz according to claim 1, characterized in that: According to the surface impurity marking information, by analyzing the edge information in the image data, identifying the ore particle boundary and measuring the diameter and geometric shape of the ore, analyzing the size distribution characteristics of the vein quartz ore, and generating the ore size information in the specific steps are: Based on the surface impurity marking information, by identifying edge information in the ore image data, marking boundaries of multiple ore particles, and generating a particle boundary recognition result; Based on the particle boundary recognition results, the diameters and geometric shapes of multiple particles are measured, the size data are recorded, the particle size distribution and morphology index are calculated, and the geometric shape data are generated; Based on the geometric shape data, the size distribution characteristics of the vein quartz ore are analyzed, the uniformity of the ore size is evaluated, and the ore size information is generated.

5. The field quality evaluation method of vein quartz ore for high-purity quartz according to claim 1, characterized in that: Based on the ore size information, by analyzing the reflection and absorption of the ore under various light sources, measuring the surface reflectivity and transmittance of the ore, evaluating the transparency and optical purity of the ore, and generating the optical property analysis results, the specific steps are: Based on the ore size information, the ore is illuminated by using a variety of light sources, and the reflection images and light transmission images of the ore under a variety of spectra are recorded to generate reflection and light transmission data; Based on the reflected light transmittance data, the transmittance of the ore under various spectra is calculated, the spectral absorption characteristics are recorded, and the optical response characteristics of the ore are generated; Based on the optical response characteristics of the ore, the correlation between the spectral data and the physical size of the ore is considered, the transparency of the ore is evaluated, and the optical characteristic analysis results are generated.

6. The method for evaluating the quality of vein quartz ore in the field for high-purity quartz according to claim 5, characterized in that: The specific formula for calculating the light transmittance of the ore under multiple spectra is: ， in, Represents the light transmittance of the ore, which is the ratio of the intensity of light after passing through the ore to the initial light intensity. Represents the intensity of light after passing through the ore. Represents the initial light intensity, which is the reference light intensity in the transmittance calculation. is the base of the natural logarithm, used to describe the exponential decay process, Represents the material's absorption coefficient, reflecting the mineral's ability to absorb light. This coefficient quantifies the mineral's ability to absorb light. Represents the thickness of the ore material.

7. The method for evaluating the quality of vein quartz ore in the field for high-purity quartz according to claim 1, characterized in that: Based on the optical property analysis results, the volume and weight information of the ore is measured, the density of the ore is calculated, the stress response is recorded in combination with the pressure sensor, and the compressive strength of the ore is evaluated. The specific steps of generating the ore density data set are as follows: Based on the optical property analysis results, the volume and weight of the ore sample are measured to generate volume and weight data; Calculating the density of the vein quartz ore sample based on the volume weight data to generate density calculation data; Based on the density calculation data, a pressure sensor is used to record the stress response state of the ore under various pressures, evaluate the compressive strength of the ore, and generate an ore density data set.

8. A field quality evaluation system for vein quartz ore for high-purity quartz, characterized in that: According to the method for field quality evaluation of vein quartz ore for high-purity quartz according to any one of claims 1 to 7, the system comprises: The surface image acquisition module uses image acquisition equipment to take multi-angle photos of vein quartz ore, analyze the color and texture information of the ore sample, and generate ore image data; The surface impurity detection module marks surface impurities based on the ore image data and generates surface impurity marking information by analyzing the color and texture information of the ore surface; The ore size measurement module analyzes ore image information based on the surface impurity mark information, identifies the boundaries of ore particles, measures the diameters and geometric shapes of multiple ores, and generates ore size information; The optical property analysis module measures the surface reflectivity and transmittance based on the ore size information, analyzes the reflection and absorption of the ore under various light sources, evaluates the transparency of the ore, and generates optical property information; The physical property analysis module measures the volume and weight of the ore based on the optical property information, calculates the density of the ore, and combines with the pressure sensor to analyze the response state of the ore under various pressures to evaluate the compressive strength of the ore and generate an ore density data set; The purity calculation module calculates the purity index of the ore based on the ore density data set and the relationship between various characteristic parameters of the ore and the ore purity, evaluates the quality grade of the ore, and generates an ore quality evaluation result.

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