A method and system for continuous evaluation of rock mass quality using drill cores

Abstract

The present invention relates to the technical field of rock mass quality evaluation in mining engineering and underground rock engineering, and discloses a method and system for continuous rock mass quality evaluation using drill cores, which realizes refined, comprehensive and high-precision quality evaluation of drill cores. First, high-resolution three-dimensional image data of the drill cores is obtained through high-precision laser scanning technology. These images can record the geometric characteristics and fracture characteristics of the rock cores in detail. Then, advanced image processing algorithms are used to automatically analyze the three-dimensional images to extract information such as the geometric characteristics, fracture characteristics and mineral composition of the rock cores. This process greatly reduces interference from human factors and ensures the objectivity and accuracy of the data. At the same time, cross-hole radar tomography technology is used to obtain information on fracture zones, fractures and cavities inside the rock mass, making the evaluation results more comprehensive.

Description

Technical Field

[0001] The present invention relates to the technical field of rock mass quality evaluation in mining engineering and underground rock engineering, and in particular to a method and system for continuously evaluating rock mass quality by using drill cores. Background Art

[0002] In underground and geotechnical engineering, accurate rock mass quality assessment is crucial for project safety and economic viability. Traditional rock mass quality assessment methods primarily rely on physical and mechanical testing of drill cores. While drill core testing provides data on the physical and mechanical properties of the rock mass, this data is often discrete and fails to fully reflect the actual rock mass conditions throughout the entire borehole. Traditional methods lack high-resolution three-dimensional image data, resulting in incomplete spatial distribution information for evaluation results. Existing core image processing techniques often rely on manual analysis and fail to fully utilize advanced image processing algorithms, such as deep learning. This results in inaccurate identification and extraction of core features. Furthermore, existing evaluation methods typically focus on a single rock mass metric, such as rock strength or fracture density, while ignoring factors that significantly influence rock mass quality, such as mineral composition and groundwater status. This results in incomplete evaluation results and a relatively simple presentation of traditional rock mass quality assessment results. The lack of three-dimensional visualization and real-time updating of rock mass quality data makes it difficult to provide users with intuitive and interactive data display and analysis tools.

[0003] To overcome the shortcomings of existing technologies, this paper proposes an innovative method and system for continuous rock mass quality assessment using drill cores. By combining high-precision laser scanning technology, cross-hole radar tomography, image processing algorithms, deep learning techniques, and virtual reality technology, this method enables comprehensive, accurate, and real-time assessment of rock mass quality. Summary of the Invention

[0004] In response to the shortcomings of the existing technology, the present invention provides a method and system for continuous rock quality evaluation using drill cores, which solves the problem that existing evaluation methods usually only focus on a single indicator of the rock mass, such as rock strength or crack density, and ignore factors that have an important impact on rock quality, such as mineral composition and groundwater status, resulting in incomplete evaluation results and a relatively single display method for traditional rock quality evaluation results.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: a method for continuously evaluating rock mass quality using drill cores, the method comprising the following steps:

[0006] S1. Obtain drilling information, including the hole number, location, inclination, depth, drilling equipment parameters, and drilling speed;

[0007] S2. Use high-precision laser scanning technology to perform three-dimensional scanning on the core to obtain high-resolution three-dimensional images of the core;

[0008] S3, uploading the core 3D image data to the cloud platform and establishing a core 3D image database;

[0009] S4. Automated analysis of the three-dimensional core image using image processing algorithms to extract information on the core's geometric features, fracture characteristics, and mineral composition;

[0010] S5. Calculate the structural integrity index and fracture density index of the core based on the extracted geometric features and fracture characteristics;

[0011] S6. Calculate the mineral composition ratio and rock strength index of the rock based on the mineral composition information;

[0012] S7. Use cross-hole radar tomography technology to image the rock mass between the boreholes to obtain information on the fracture zones, cracks and cavities inside the rock mass;

[0013] S8. Calculate the rock mass joint spacing index within each minimum measurement range;

[0014] S9, uploading the cross-hole radar tomography data to the cloud platform and establishing a radar imaging database;

[0015] S0, integrating core 3D image data and cross-hole radar tomography data, establishing a core quality assessment model, evaluating the quality of each core section, and obtaining rock mass quality assessment results;

[0016] S11. Upload the rock mass quality evaluation results to the cloud platform, generate a continuous distribution map of rock mass quality, and perform a three-dimensional visual display.

[0017] Preferably, the drilling information also includes drilling environmental parameters, including temperature, pressure and humidity.

[0018] Preferably, the three-dimensional scanning technology is lidar scanning technology.

[0019] Preferably, the image processing algorithm includes a deep learning algorithm for automatically identifying and extracting geometric features and fracture features of the core.

[0020] Preferably, the mineral composition information is obtained by X-ray fluorescence spectroscopy.

[0021] Preferably, the structural integrity indicators include continuity, integrity and degree of fracture of the core.

[0022] Preferably, the crack density index includes the number of cracks per unit length and the opening degree of the cracks.

[0023] Preferably, the core quality assessment model is based on a multi-factor comprehensive evaluation method, which comprehensively considers structural integrity, crack density and mineral composition ratio factors. The continuous distribution map of rock mass quality is generated through a data visualization tool on a cloud platform and supports multi-perspective and multi-scale three-dimensional display.

[0024] Preferably, the rock mass joint spacing index comprises the following steps:

[0025] Data collection: Extract core samples from the borehole and record the joint length of each core section;

[0026] Joint length standardization: Joints longer than 1 cm are recorded as their actual length; joints less than 1 cm but greater than or equal to 0.5 cm are standardized to 1 cm; joints less than 0.5 cm are recorded as "joint-dense areas" and are not included in the joint spacing calculation;

[0027] Joint spacing measurement: Calculate the actual distance between each pair of adjacent joints and calculate the arithmetic mean of the joint spacing:

[0028]

[0029] Where D is the joint spacing index, d i is the distance between each pair of adjacent joints, and n is the number of joint pairs.

[0030] A system for continuously evaluating rock mass quality using drill cores, the system comprising:

[0031] Data acquisition module, used to automatically collect drilling information, core 3D images, and cross-hole radar tomography data;

[0032] Data processing module for processing and analyzing core 3D image data, radar tomography data, mineral composition data and structural integrity indicators;

[0033] Evaluation model module, used to calculate rock mass quality evaluation results based on a multi-factor comprehensive evaluation method, and to perform model optimization and calibration;

[0034] A data storage module for storing core three-dimensional image data, radar imaging data, quality evaluation results and related parameters;

[0035] Visualization module, used to generate and display continuous distribution maps of rock mass quality, including two-dimensional cloud maps and three-dimensional maps, supporting interactive data display;

[0036] Real-time update module, used to receive new data and update the evaluation results in real time, making dynamic adjustments to maintain the accuracy of the results;

[0037] The user interaction module is used to provide a user interface, allowing users to input parameters, view evaluation results, perform data analysis and export reports.

[0038] Beneficial effects

[0039] The present invention provides a method and system for continuously evaluating rock mass quality using drill cores. Compared with existing technologies, it has the following advantages:

[0040] 1. In the present invention, the evaluation method realizes the refined, comprehensive and high-precision quality evaluation of the drill core through the comprehensive application of multiple advanced technologies. First, high-resolution three-dimensional image data of the drill core is obtained through high-precision laser scanning technology. These images can record the geometric characteristics and fracture characteristics of the core in detail. Then, advanced image processing algorithms are used to automatically analyze the three-dimensional images to extract the geometric characteristics, fracture characteristics and mineral composition information of the core. This process greatly reduces the interference of human factors and ensures the objectivity and accuracy of the data. At the same time, the fracture zone inside the rock body is obtained through cross-hole radar tomography technology. , cracks and voids information, making the evaluation results more comprehensive. Subsequently, these data are uploaded to the cloud platform to establish a three-dimensional core image database and a radar imaging database. Through comprehensive analysis of multi-dimensional data, the system can fully grasp the internal structure and quality characteristics of the rock mass, calculate the key parameters of structural integrity indicators, crack density indicators and mineral composition ratios, and ensure the scientificity and reliability of the evaluation results. The multi-factor comprehensive evaluation method further improves the accuracy of rock mass quality evaluation, making the evaluation results more comprehensive, accurate and credible, providing a reliable scientific basis for engineering construction and resource development, thereby improving the safety and economy of engineering projects.

[0041] 2. In the present invention, the system establishes a three-dimensional core image database and a radar imaging database, achieving continuous distribution and three-dimensional visualization of rock mass quality evaluation results. First, through high-precision laser scanning technology and cross-hole radar tomography technology, detailed drill core data and rock mass internal structure information are obtained. After processing, this data is uploaded to the cloud platform to establish a complete database. Then, the system comprehensively analyzes this data and calculates the quality evaluation results of each core segment using a multi-factor comprehensive evaluation model. After uploading the evaluation results to the cloud platform, continuous distribution maps of rock mass quality are generated. These distribution maps not only intuitively reflect the structural characteristics and quality distribution of the rock mass, but also support multi-view and multi-scale three-dimensional display. Users can view, analyze, and export data through an interactive interface. The visual display enables users to more intuitively understand the distribution of rock mass quality, providing an important reference for decision-making. In addition, through the real-time update module, the system can dynamically receive new data and promptly update the evaluation results, ensuring the real-time and accuracy of the results. This real-time dynamic update capability ensures that the system can still provide accurate and reliable rock mass quality evaluation results in complex engineering environments, thereby significantly improving the management efficiency and safety of engineering projects. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 This is a flow chart of a method for continuous rock mass quality evaluation using drill cores proposed by the present invention;

[0043] Figure 2 The radar wave velocity CT cross-section diagram in Example 1;

[0044] Figure 3 This is a cross-sectional diagram of the wave impedance logging in Example 1;

[0045] Figure 4 This is the radar skin depth CT cross-section diagram in Example 1;

[0046] Figure 5 This is a system module flow chart of a system for continuously evaluating rock mass quality using drill cores proposed by the present invention. DETAILED DESCRIPTION

[0047] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0048] See also Figure 1 - Figure 5 The present invention provides two technical solutions, specifically including the following embodiments:

[0049] Example 1:

[0050] A method and system for continuously evaluating rock mass quality using drill cores, the method comprising the following steps:

[0051] S1. Obtain drilling information, including the hole number, location, inclination, depth, drilling equipment parameters, and drilling speed;

[0052] S2. Use high-precision laser scanning technology to perform three-dimensional scanning on the core to obtain high-resolution three-dimensional images of the core;

[0053] S3, uploading the core 3D image data to the cloud platform and establishing a core 3D image database;

[0054] S4. Automated analysis of the three-dimensional core image using image processing algorithms to extract information on the core's geometric features, fracture characteristics, and mineral composition;

[0055] S5. Calculate the structural integrity index and fracture density index of the core based on the extracted geometric features and fracture characteristics;

[0056] S6. Calculate the mineral composition ratio and rock strength index of the rock based on the mineral composition information;

[0057] S7. Use cross-hole radar tomography technology to image the rock mass between the boreholes and obtain information about the fracture zones, cracks and cavities inside the rock mass. The radar's transmitting power is related to the wave impedance.

[0058] The antenna's transmitted power in a borehole varies with depth and is related to the wave impedance. Given the antenna's length L, current I, and wavelength λ, the antenna's transmitted power P is proportional to the wave impedance Z of the surrounding medium, as shown in the following equation.

[0059]

[0060] Generally speaking, the higher the wave impedance, the greater the transmission power, and vice versa. Wave impedance is defined as the ratio of the electric field to the magnetic field in electromagnetic wave propagation, with the unit of Ω, and it is a complex number. The wave impedance of air is the highest, at 377Ω, and the transmission power is the maximum P0; the wave impedance in dry rock is 100-300Ω, and the transmission power is reduced; the wave impedance of rock containing metal minerals or water will be greatly reduced, even to 10-50Ω, and its transmission power is also greatly reduced. According to the correspondence between the transmission power Pi and the wave impedance Zi, wave impedance logging can be performed by the ratio of the power at the transmission point to the transmission power in the air. The wave impedance and DC resistivity here are different physical quantities. By analyzing the travel time difference between the transmitted signal and the received signal, the electromagnetic wave velocity CT is calculated, and the skin depth CT is calculated by the signal amplitude ratio. Specifically, cross-hole radar tomography can effectively reveal the wave impedance, wave velocity and skin depth inside the rock mass, thereby reflecting the density, mineral composition, water content and the integrity of the internal structure of the rock mass.

[0061] The wave velocity of rock represents the speed of electromagnetic wave propagation. It is inversely proportional to the square root of the relative dielectric constant ε of the medium:

[0062]

[0063] Where C is the electromagnetic wave speed in air, which is 0.3m / ns.

[0064] The wave velocity reflects the differences in mineral composition, lithology, density, looseness and water content of rock and soil media. The vast majority of dry rock and soil media on Earth have a relative dielectric constant between 4 and 9, and an electromagnetic wave velocity between 0.1 and 0.15 m / ns. Compared with rock and soil media, the wave velocity of air is the highest, at 0.3 m / ns; the wave velocity of water is the lowest, at 0.033 m / ns. If the wave velocity of the rock and soil medium is lower than 0.1 m / ns, it means that the rock and soil medium is loose and contains water. The greater the amount of water, the lower the electromagnetic wave velocity. If the wave velocity is higher than 0.15 m / ns, it means that the rock and soil is loose and has developed voids or cavities. The more voids there are, the higher the electromagnetic wave velocity.

[0065] Skin depth δ is defined as the distance an electromagnetic wave travels before its amplitude decays to 1 / e of its original value. It characterizes the attenuation characteristics of a medium for electromagnetic wave propagation. A larger skin depth indicates greater penetration and less attenuation, and vice versa. For electromagnetic waves with frequencies above 10 MHz, the skin depth is inversely proportional to the conductivity of the medium and directly proportional to the square root of the dielectric constant, indicating that the skin depth is sensitive to the conductivity of the medium.

[0066]

[0067] The electrical conductivity of rock and soil media varies within a range of several orders of magnitude, resulting in skin depth variations ranging from a few meters to tens of meters. This is beneficial for the resolution of water-bearing bodies, mineralized zones, karst, loose areas, and voids. In the loess-covered area of ​​dry loose layers, the skin depth varies within a range of 3 to 5 meters. The skin depth of rock masses varies within a range of 10 to 20 meters; for water-bearing zones, mineralized zones, clay layers, and highly conductive rock masses, the skin depth may be less than 3 meters. For porous loose layers and voids, the skin depth will be greater than 20 meters.

[0068] S8. Calculate the rock mass joint spacing index within each minimum measurement range;

[0069] S9. Upload the cross-hole radar tomography data to the cloud platform to establish a radar imaging database. The cross-hole radar tomography data includes radar wave velocity CT imaging and radar skin depth CT imaging.

[0070] S0, integrating core 3D image data and cross-hole radar tomography data, establishing a core quality assessment model, evaluating the quality of each core section, and obtaining rock mass quality assessment results;

[0071] S11. Upload the rock mass quality evaluation results to the cloud platform, generate a continuous distribution map of rock mass quality, and perform a three-dimensional visual display.

[0072] The drilling information also includes drilling environmental parameters, including temperature, pressure, and humidity. The three-dimensional scanning technology is lidar scanning technology. The image processing algorithm includes a deep learning algorithm for automatically identifying and extracting geometric features and crack features of the rock core. The mineral composition information is obtained through X-ray fluorescence spectroscopy technology. The structural integrity index includes the continuity, integrity, and degree of fracture of the rock core. The crack density index includes the number of cracks per unit length and the opening degree of the cracks. The core quality assessment model is based on a multi-factor comprehensive evaluation method, comprehensively considering structural integrity, crack density, and mineral composition ratio factors. The rock mass quality continuous distribution map is generated using a data visualization tool on a cloud platform and supports multi-perspective and multi-scale three-dimensional display. The rock mass joint spacing index includes the following steps:

[0073] Data collection: Extract core samples from the borehole and record the joint length of each core section;

[0074] Joint length standardization: Joints longer than 1 cm are recorded as their actual length; joints less than 1 cm but greater than or equal to 0.5 cm are standardized to 1 cm; joints less than 0.5 cm are recorded as "joint-dense areas" and are not included in the joint spacing calculation;

[0075] Joint spacing measurement: Calculate the actual distance between each pair of adjacent joints and calculate the arithmetic mean of the joint spacing:

[0076]

[0077] Where D is the joint spacing index, d i is the distance between each pair of adjacent joints, and n is the number of joint pairs.

[0078] The core of this evaluation method lies in the precise collection and comprehensive analysis of multi-dimensional data. First, high-precision laser scanning technology is used to acquire 3D image data of the drill core. These high-resolution images capture the core's geometric and fracture characteristics in detail, ensuring data accuracy. Next, the system uses advanced image processing algorithms to automatically analyze these 3D image data, extracting information about the core's geometry, fracture characteristics, and mineral composition. Simultaneously, cross-hole radar tomography is used to image fracture zones, fissures, and cavities within the rock mass, further providing detailed structural information. The system then uploads this data to a cloud platform to establish a 3D core image database and a radar imaging database. These databases not only store extensive data on the core and rock mass's internal structure, but also enable centralized data management and sharing through the cloud platform. Through comprehensive analysis of this multi-dimensional data, the system comprehensively understands the rock mass's internal structure and quality characteristics, calculating key parameters such as structural integrity indicators, fracture density, and mineral composition ratios, ensuring the scientific and accurate evaluation results. The multi-factor comprehensive evaluation method comprehensively considers the geometric characteristics, fracture characteristics and mineral composition information of the core, making the evaluation results more comprehensive and accurate, and providing reliable technical support for the scientific evaluation of rock mass quality.

[0079] Example 2:

[0080] Based on the first embodiment, a system for continuously evaluating rock mass quality using drill cores is provided, the system comprising:

[0081] The data acquisition module is used to automatically collect drilling information, core 3D images, and cross-hole radar tomography data;

[0082] The data processing module is used to process and analyze core 3D image data, radar tomography data, mineral composition data, and structural integrity indicators. Core 3D image acquisition is generated through laser scanning point cloud. The specific algorithm is as follows:

[0083]

[0084] Where: d is the distance from the laser to the object, c is the speed of light (about 3×10 8 m / s), t is the round trip time of the laser;

[0085] Radar tomography data is obtained through the following calculation method:

[0086] Reflection time formula:

[0087]

[0088] Where: t r is the arrival time of the reflected signal, d is the depth of the fault inside the rock mass, and c is the propagation speed of the electromagnetic wave in the rock mass.

[0089] Fourier transform formula:

[0090]

[0091] Where: X(f) is the frequency domain signal, x(t) is the time domain signal, and f is the frequency.

[0092] Imaging equation:

[0093]

[0094] Where: δ(x) is the tomographic image of the rock mass, R(t,x i ) is the received radar signal, Δt is the time interval;

[0095] The above formulas and algorithms express the specific processing process of core 3D images and cross-hole radar tomography in the data acquisition module.

[0096] Evaluation model module, used to calculate rock mass quality evaluation results based on a multi-factor comprehensive evaluation method, and to perform model optimization and calibration;

[0097] A data storage module for storing core three-dimensional image data, radar imaging data, quality evaluation results and related parameters;

[0098] Visualization module, used to generate and display continuous distribution maps of rock mass quality, including two-dimensional cloud maps and three-dimensional maps, supporting interactive data display;

[0099] Real-time update module, used to receive new data and update the evaluation results in real time, making dynamic adjustments to maintain the accuracy of the results;

[0100] The user interaction module is used to provide a user interface that allows users to input parameters, view evaluation results, perform data analysis, and export reports;

[0101] Based on the data processing module, the system establishes an evaluation model module and uses a multi-factor comprehensive evaluation approach to calculate rock mass quality assessment results. First, the system comprehensively considers multiple factors, including the core's structural integrity, fracture density, and mineral composition ratio, to ensure comprehensive and accurate assessment results. Through model optimization and calibration, the system continuously adjusts the evaluation model parameters to improve the accuracy and reliability of the results. Cross-hole radar tomography technology plays a key role in this process. By transmitting and receiving radar signals between multiple boreholes, it generates tomographic images of the rock's internal fracture zones and fracture structures. These images provide detailed structural information within the rock mass, enhancing the comprehensiveness and accuracy of the assessment results. The data storage module is responsible for storing 3D core image data, radar imaging data, quality assessment results, and related parameters, ensuring data security and traceability. The visualization module generates and displays continuous rock mass quality distribution maps, including 2D and 3D cloud maps, supporting interactive data display. Users can view, analyze, and export data through an interactive interface, providing a direct understanding of the rock mass quality distribution. The real-time update module ensures the system can receive new data and dynamically adjust to maintain the accuracy of evaluation results. The user interaction module provides a user-friendly interface that supports parameter input, evaluation result viewing, data analysis, and report export, thus achieving full automation and intelligent rock mass quality evaluation. Through the collaborative operation of these modules, the system can efficiently and accurately complete rock mass quality evaluation and display, providing reliable technical support and data basis for engineering project planning and implementation.

[0102] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements and improvements made within the spirit and principles of the application should be included in the scope of protection of the present application.

Claims

1. A method for continuous rock mass quality evaluation using drill cores, characterized in that: The method comprises the following steps: S1. Obtain drilling information, including the hole number, location, inclination, depth, drilling equipment parameters, and drilling speed; S2. Use high-precision laser scanning technology to perform three-dimensional scanning on the core to obtain high-resolution three-dimensional images of the core; S3, uploading the core 3D image data to the cloud platform and establishing a core 3D image database; S4. Automated analysis of the three-dimensional core image using image processing algorithms to extract information on the core's geometric features, fracture characteristics, and mineral composition; S5. Calculate the structural integrity index and fracture density index of the core based on the extracted geometric features and fracture characteristics; S6. Calculate the mineral composition ratio and rock strength index of the rock based on the mineral composition information; S7. Use cross-hole radar tomography technology to image the rock mass between the boreholes to obtain information on the fracture zones, cracks and cavities inside the rock mass; S8. Calculate the rock mass joint spacing index within each minimum measurement range; S9, uploading the cross-hole radar tomography data to the cloud platform and establishing a radar imaging database; S10. Integrate the core 3D image data and cross-hole radar tomography data to establish a core quality assessment model, evaluate the quality of each core section, and obtain the rock mass quality assessment results; S11. Upload the rock mass quality evaluation results to the cloud platform, generate a continuous distribution map of rock mass quality, and perform a three-dimensional visual display.

2. The method for continuous rock mass quality evaluation using drill cores according to claim 1, characterized in that: The drilling information also includes drilling environment parameters, including temperature, pressure and humidity.

3. The method for continuous rock mass quality evaluation using drill cores according to claim 1, characterized in that: The three-dimensional scanning technology is a laser radar scanning technology.

4. The method for continuous rock mass quality evaluation using drill cores according to claim 1, characterized in that: The image processing algorithm includes a deep learning algorithm for automatically identifying and extracting geometric features and fracture features of the rock core.

5. The method for continuous rock mass quality evaluation using drill cores according to claim 1, characterized in that: The mineral composition information is obtained by X-ray fluorescence spectroscopy.

6. The method for continuous rock mass quality evaluation using drill cores according to claim 1, characterized in that: The structural integrity indicators include the continuity, integrity and degree of fracture of the core.

7. The method for continuous rock mass quality evaluation using drill cores according to claim 1, characterized in that: The crack density index includes the number of cracks per unit length and the opening degree of the cracks.

8. The method for continuous rock mass quality evaluation using drill cores according to claim 1, characterized in that: The core quality assessment model is based on a multi-factor comprehensive evaluation method, taking into account factors such as structural integrity, fracture density, and mineral composition ratio. The continuous distribution map of rock mass quality is generated using data visualization tools on a cloud platform and supports multi-view and multi-scale three-dimensional display.

9. The method for continuous rock mass quality evaluation using drill cores according to claim 1, characterized in that: The rock mass joint spacing index comprises the following steps: Data collection: Extract core samples from the borehole and record the joint length of each core section; Joint length standardization: Joints longer than 1 cm are recorded as their actual length; joints less than 1 cm but greater than or equal to 0.5 cm are normalized to 1 cm; joints less than 0.5 cm are recorded as "joint-dense areas" and are not included in the joint spacing calculation. Joint spacing measurement: Calculate the actual distance between each pair of adjacent joints and calculate the arithmetic mean of the joint spacing: Where D is the joint spacing index, d i is the distance between each pair of adjacent joints, and n is the number of joint pairs.

10. A system for continuous rock mass quality evaluation using drill cores, characterized in that: The system includes: Data acquisition module, used to automatically collect drilling information, core 3D images, and cross-hole radar tomography data; Data processing module for processing and analyzing core 3D image data, radar tomography data, mineral composition data and structural integrity indicators; Evaluation model module, used to calculate rock mass quality evaluation results based on a multi-factor comprehensive evaluation method, and to perform model optimization and calibration; A data storage module for storing core three-dimensional image data, radar imaging data, quality evaluation results and related parameters; Visualization module, used to generate and display continuous distribution maps of rock mass quality, including two-dimensional cloud maps and three-dimensional maps, supporting interactive data display; Real-time update module, used to receive new data and update the evaluation results in real time, making dynamic adjustments to maintain the accuracy of the results; The user interaction module is used to provide a user interface, allowing users to input parameters, view evaluation results, perform data analysis and export reports.

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