Strip mine inclined roadway detection and evaluation method and system and fluorescent mixed spraying device

Abstract

The invention discloses a strip mine inclined roadway detection evaluation method and system and a fluorescent mixed spraying device. The method comprises the following steps: respectively executing fluorescent substance injection and optical observation in at least two drill holes on a target exploration line, and judging the space connectivity of a roadway cavity between the drill holes according to an observation result; for the roadway sections judged to be communicated, roadway section area data, perpendicular to the direction of the exploration line, at all the drilling positions are obtained; and based on the section area data, calculating a quantitative index representing the change degree of a section form, and according to a comparison result of the quantitative index and a preset threshold value, adaptively selecting a corresponding volume calculation model to calculate the volume of the roadway cavity. According to the method, space connectivity rapid qualification based on fluorescence and adaptive volume accurate calculation based on morphological variation coefficients are combined, and the problems of high exploration cost and low calculation accuracy in a traditional method are solved through a one-time integrated technical process.

Description

Technical Field

[0001] This invention relates to the field of geotechnical engineering technology, and in particular to a method, system and fluorescent spraying device for detecting and evaluating inclined roadways in open-pit mines. Background Technology

[0002] In mining areas transitioning from underground to open-pit mining, unknown or concealed inclined and irregular goaf roadways pose a long-standing and significant safety hazard. These roadways are characterized by their hidden spatial location, irregular three-dimensional shape, variable cross-sectional extension, and frequent collapse deformation. Accurate detection and quantitative evaluation of these roadways are a recognized technical challenge in the industry. Currently, the industry primarily relies on a combination of drilling and geophysical exploration for exploration. However, geophysical methods have limitations such as high ambiguity and susceptibility to interference from complex geological conditions. While traditional drilling methods are intuitive, capturing irregular inclined spaces often requires deploying numerous densely drilled boreholes for profile scanning, and then estimating the total volume by simplifying the cavities between adjacent profiles into regular geometric shapes such as trapezoids or cones. This traditional "drilling density + geometric simplification" approach, when faced with highly irregular inclined roadways (such as those with severe local collapses), forcibly applies a fixed geometric model for volume integration, leading to significant deviations between the calculated results and the actual spatial volume. This fails to meet the accuracy requirements of engineering remediation, and the dense drilling also results in long exploration cycles and high costs. Summary of the Invention

[0003] The present invention aims to at least partially solve one of the technical problems in the related art.

[0004] Therefore, embodiments of the present invention propose a method, system, and fluorescent spraying device for detecting and evaluating inclined roadways in open-pit mines, providing a systematic solution for the detection and evaluation of inclined roadways in open-pit mines that integrates rapid qualitative analysis, accurate quantitative analysis, intelligent adaptation, and economic efficiency, thereby improving upon the shortcomings of traditional technologies.

[0005] The open-pit mine inclined roadway detection and evaluation method of this invention includes: S1. Perform fluorescent material injection and optical observation in at least two boreholes along the target exploration line, and determine the spatial connectivity of the tunnel cavity between boreholes based on the observation results. S2. For roadway sections that are determined to be connected, obtain the roadway profile area data perpendicular to the exploration line at each borehole location. S3. Based on the cross-sectional area data, calculate a quantitative index characterizing the degree of change in cross-sectional shape. Based on the comparison result between the quantitative index and a preset threshold, adaptively select the corresponding volume calculation model to calculate the volume of the tunnel cavity.

[0006] In some embodiments, in step S1, the fluorescent material ejection and optical observation process includes: Fluorescent material is sprayed in one borehole using a fluorescent mixing sprayer, and borehole television is used to observe the process in at least one adjacent borehole. The presence or absence of fluorescence diffusion is used to qualitatively determine whether the tunnel cavity is connected.

[0007] In some embodiments, in step S2, the tunnel profile area data is obtained by a three-dimensional laser scanner lowered into the borehole.

[0008] In some embodiments, in step S3, the quantitative index is the cross-sectional area variation coefficient λ, which is calculated by: calculating the ratio of the standard deviation σ of all cross-sectional areas to the arithmetic mean S, i.e. λ = σ / S; The preset threshold is an empirical value used to distinguish the regularity and irregularity of the tunnel morphology; when λ is less than the preset threshold, the first volume calculation model is selected, and when λ is greater than or equal to the preset threshold, the second volume calculation model is selected, wherein the preset threshold is 0.3.

[0009] In some embodiments, the first volume calculation model is a standard model based on the integration of adjacent cross-sectional areas and their spacing, and the calculation formula of the standard model is:

[0010] Where V is the calculated volume, L is the total spacing between sections, n is the number of sections, and Si is the area of ​​the i-th section.

[0011] In some embodiments, the second volume calculation model is a fractal calculation model that introduces a morphological correction function to handle irregular cavities, and the basic form of the fractal calculation model is as follows:

[0012] Wherein, F(x, y, λ) is a fractal correction function related to the profile position coordinates and the coefficient of variation λ.

[0013] The open-pit mine inclined roadway detection and evaluation system of this invention is used to implement the method described in any of the above embodiments.

[0014] The open-pit mine inclined roadway detection and evaluation system of this invention includes: A fluorescence detection module, which is used to perform the fluorescence connectivity detection step of S1; A three-dimensional data acquisition module, which is used to perform the three-dimensional morphological data acquisition step of S2; The data processing and calculation module is configured to perform the adaptive volume calculation step of S3.

[0015] In some embodiments, the fluorescence detection module includes a fluorescence mixing device and a borehole television observation device, and the three-dimensional data acquisition module includes a three-dimensional laser scanning device.

[0016] The fluorescent mixing spraying device of this invention is used in the system described in any of the above embodiments.

[0017] The fluorescent mixing spraying device of this invention includes a drill bit body and a component integrated on the drill bit body: A material storage and mixing section for storing and mixing fluorescent materials; A pressurization drive unit, connected to the material storage and mixing unit, is used to provide injection power; A controllable spraying section is connected to the material storage and mixing section for directional spraying of the mixed fluorescent material.

[0018] In some embodiments, the material storage and mixing section includes a fluorescent storage tank and a water-powder mixing chamber connected thereto; The pressurization drive unit includes a water supply unit and an air supply pressurization unit that are respectively connected to the water-powder mixing chamber through a water pipe and an air pipe; The controllable spraying section includes a nozzle and a controllable rotating bend. One end of the nozzle is connected to the water-powder mixing chamber, and the side wall of the nozzle is provided with multiple spray holes. The other end of the nozzle is connected to the controllable rotating bend.

[0019] In summary, the method in this embodiment of the invention overcomes the problems of high cost and low accuracy of the traditional "intensified drilling + geometric simplification" mode by using three steps: qualitative scanning with fluorescence detection, high-precision three-dimensional data acquisition, and adaptive volume calculation based on the coefficient of variation λ. This reduces the volume calculation error from about 25% in the traditional method to less than 5%.

[0020] This method is materialized into three functional modules: detection, acquisition, and calculation. This achieves standardization, integration, and intelligence of the detection process, optimizes resource allocation, shortens the overall exploration cycle by about 30%, reduces costs by more than 40%, and ensures the objectivity and repeatability of the results.

[0021] By using a fluorescent mixed-jet drill bit as the transmitter of the detection module, and through a structural design of dry storage and wet spraying, pneumatic pressurization, and controllable rotation, the downhole tracer achieves wide-area, directional, and reliable dispersion, significantly expanding the effective detection range of a single hole, reducing the number of exploration boreholes, and improving the success rate of connectivity determination. Attached Figure Description

[0022] Figure 1 This is a schematic diagram of fluorescence diffusion simulation according to an embodiment of the present invention.

[0023] Figure 2 This is a schematic diagram of the fluorescent mixing spraying device according to an embodiment of the present invention.

[0024] Figure label: 10 - Inclined roadway; 101 - Undeformed roadway; 102 - Compressed and deformed roadway; 103 - Locally collapsed roadway; 104 - Fluorescent diffusion zone; 11-Exploration line; 12-Borehole; 20-Drill bit body; 201-Fluorescent storage tank; 202-Water-powder mixing chamber; 203-Water guide pipe; 204-Air guide pipe; 205-Nozzle; 2051-Particle nozzle; 206-Controllable rotating bend pipe; 207-Fixed air pressure valve. Detailed Implementation

[0025] Embodiments of the present invention are described in detail below, examples of which are illustrated in the accompanying drawings. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain the present invention, and should not be construed as limiting the present invention.

[0026] The following describes, with reference to the accompanying drawings, the detection and evaluation method, system, and fluorescent spraying device for inclined roadways 10 in open-pit mines according to embodiments of the present invention.

[0027] The detection and evaluation method for inclined roadways 10 in open-pit mines according to this invention includes: S1. Fluorescent connectivity detection steps: In at least two boreholes 12 on the target exploration line 11, fluorescent material injection and optical observation are performed respectively, and the spatial connectivity of the tunnel cavity between the boreholes 12 is determined based on the observation results.

[0028] S2. Three-dimensional morphological data acquisition steps: For roadway sections that are determined to be connected, obtain the roadway profile area data at each borehole 12 location perpendicular to the exploration line 11.

[0029] S3. Adaptive volume calculation step: Based on the profile area data, calculate the quantitative index characterizing the degree of profile morphological change. Based on the comparison result between the quantitative index and the preset threshold, adaptively select the corresponding volume calculation model to calculate the volume of the tunnel cavity.

[0030] The detection and evaluation method for inclined roadways 10 in open-pit mines of this invention creatively adopts a strategy of "step-by-step treatment and system integration" to address the two core defects of the traditional technical route of "intensified drilling + geometric simplification" (low cost and accuracy, poor model adaptability).

[0031] First, the fluorescence detection technology in step S1 enables rapid qualitative assessment of tunnel connectivity at a low cost, resolving the initial judgment issue of "whether intensified exploration is needed" and reducing the need for blindly deploying verification boreholes 12. Next, in key sections confirming connectivity, high-precision three-dimensional data acquisition is performed in step S2, providing accurate input for subsequent quantitative analysis. Finally, step S3 abandons the traditional approach of forcibly applying a single fixed geometric model to all tunnel morphologies, instead adopting a diagnostic-adaptive intelligent computing principle.

[0032] The core of the adaptive volume calculation in step S3 lies in the introduction of morphological diagnostic indicators (quantitative indicators) and the dynamic algorithm selection mechanism linked to them.

[0033] First, calculate the coefficient of variation (λ) of the series of profile area data obtained in step S2. The λ value is an objective, dimensionless statistical quantity that accurately quantifies the degree of irregularity in the shape of the tunnel along exploration line 11. The smaller the λ value, the more similar the size and shape of each profile, and the more regular and uniform the tunnel shape; the larger the λ value, the more significant the differences between the profiles, and the more likely there is severe local expansion, contraction or collapse in the tunnel, resulting in a highly irregular shape.

[0034] A preset, engineering-validated threshold (e.g., λ=0.3) is used. The system automatically performs diagnostics based on a comparison between the λ value and the threshold. When λ < the threshold, the system diagnoses the roadway segment as being in a regular or slightly deformed state. At this time, the first volume calculation model (standard model) is activated. This model is essentially an integral formula that takes into account slight morphological changes. It is computationally efficient and can guarantee sufficient accuracy when the shape is relatively regular, avoiding the neglect of slight changes by traditional methods (such as the simple trapezoidal method).

[0035] When λ ≥ the threshold, the system diagnoses the tunnel segment as highly irregular or severely collapsed. At this point, the traditional regular geometric model is severely distorted. The system then adaptively switches to a second volume calculation model (fractal correction model). This model, by introducing a fractal correction function related to λ, can better simulate and fit the nonlinearity and complexity of spatial morphology during drastic changes, thereby significantly improving the volume estimation accuracy of irregular cavities.

[0036] According to the above rules, the system may use different calculation models for different sections of the roadway (corresponding to different λ values), and finally synthesize the volumes of each segment to obtain the total volume. This segmented diagnosis and adaptive calculation mode is the fundamental principle for achieving high-precision calculation in this method.

[0037] In actual engineering verification, for the same concealed inclined tunnel 10 (actual volume 895 m³) that had passed excavation verification, the traditional trapezoidal accumulation method for borehole 12 profiles yielded a result of 1120 m³, with an error as high as approximately 23.5%. However, by applying the method of this invention, the system automatically identified regular segments (λ < 0.3) and irregular collapse segments (λ ≥ 0.3), and performed calculations using the standard model and fractal model respectively, resulting in a final volume of 856 m³, with an error of less than 4.4%. This fully demonstrates that the adaptive calculation model based on morphological quantification indicators of this invention can effectively overcome the systematic bias of traditional fixed geometric models when dealing with irregular shapes, improving the volume calculation accuracy by an order of magnitude and meeting the needs of high-precision engineering management.

[0038] The method of this invention, through rapid fluorescence connectivity detection in step S1, can effectively determine the tunnel extension range and key connectivity points, thereby optimizing the borehole layout scheme. In the same verification project mentioned above, compared with the original plan for fully dense drilling, the method of this invention reduced four unnecessary boreholes 12, saving approximately 35% of direct drilling costs. Simultaneously, by reducing repetitive operations such as drilling, hole washing, and instrument deployment, the overall exploration cycle is shortened by approximately 30%, effectively solving the problem of high costs and long cycles caused by the reliance on dense borehole layout in traditional methods.

[0039] The quantitative diagnosis-adaptive calculation framework proposed in this invention does not rely on the operator's personal experience to subjectively judge the roadway morphology and select models. Instead, it drives decision-making through objective data (λ value), making the method universally adaptable to various roadway morphologies, ranging from regular to extremely irregular. Simultaneously, the process is easily programmed for automation, improving the intelligence level of the evaluation work and the consistency of results. The method has a clear principle, and the required equipment (fluorescence detection, 3D scanning, and calculation software) can be modularly integrated, demonstrating good engineering operability and industry promotion value.

[0040] In some embodiments, the fluorescent material spraying and optical observation process in step S1 includes: Fluorescent material is sprayed using a fluorescent mixing device in one borehole 12, and observation is performed using a borehole 12 television in at least one adjacent borehole 12. The presence or absence of fluorescence diffusion is used to qualitatively determine whether the tunnel cavity is connected.

[0041] The specific implementation of step S1 (fluorescence connectivity detection) is based on an engineering method of tracer delivery and optical remote identification, which is used to solve the technical problem that the spatial connectivity of inclined roadway 10 is difficult to verify directly.

[0042] At least one emission point (jet borehole 12) and one or more receiving points (observation borehole 12) are spatially configured. At the emission point, a specially prepared fluorescent substance (tracer) is injected and dispersed into the tunnel cavity in the form of a gas-liquid two-phase flow using a dedicated fluorescent mixing and spraying device under high pressure. The transport and diffusion behavior of the fluorescent substance within the cavity is directly controlled by the cavity's spatial structure.

[0043] If the cavities below the two boreholes 12 are interconnected, the fluorescent material will migrate from the emission point to the vicinity of the receiving point under the influence of airflow, gravity, and diffusion. At this time, the borehole 12 television (downhole optical imaging device) deployed at the receiving point can capture the visible light of a specific wavelength emitted by the fluorescent material. If the cavities are not interconnected or are densely blocked, the fluorescent material cannot reach the receiving point, and the borehole 12 television will not detect the fluorescent signal. This active emission-remote detection model transforms the problem of invisible spatial connectivity into a physical signal problem that can be directly detected by optical equipment.

[0044] Traditional drilling to verify connectivity requires drilling through two suspected points separately, which is costly and difficult to accurately target inclined paths. The method in this invention utilizes the tunnel itself as a transmission channel. The fluorescent material is a powder or solution that can diffuse with the weak airflow within the tunnel or on its own, making it particularly suitable for coal mine tunnel environments where gas seepage or temperature differences may cause air convection.

[0045] Even if the tunnel is narrow due to compression and deformation, or if there are localized collapses and deposits, fluorescent substances still have a high probability of migrating and being observed as long as there are gaps that allow air and fine particles to pass through. The observations from borehole 12 television are based on a binary judgment of the presence or absence of a light signal, rather than a precise measurement of the tunnel morphology. Therefore, the signal strength requirements are relatively low, and the anti-interference ability is strong, making it particularly suitable for qualitative judgments in dim, complex, and unstructured underground cavity environments.

[0046] Compared to blindly drilling more boreholes 12 to verify connectivity (each borehole 12 is costly), or using a high-precision but limited-range 3D laser scanner to scan each borehole 12 independently before data stitching and reasoning, the method of this invention only requires a small number of boreholes 12 to be deployed at key suspected points. Through a single fluorescence injection and real-time observation in adjacent boreholes, a clear connectivity conclusion can be obtained within a few hours to a day. This reduces the uncertainty in the early stages of exploration and provides a key decision-making basis for whether to conduct further intensified scanning and where to focus scanning. It can reduce unnecessary verification boreholes 12 by up to 25%.

[0047] Geophysical methods (such as resistivity and seismic methods) for determining cavity connectivity can be subject to signal anomalies caused by various factors, including water inflow, lithological changes, and fracture zones, leading to multiple interpretations. The method described in this invention introduces a highly specific exogenous tracer (fluorescent substance). Its observation directly and uniquely indicates the transport path of the material (along with its carrier air / water), thus eliminating interference from other geological factors and providing intuitive and conclusive evidence for connectivity, thereby improving the reliability of the detection results.

[0048] Step S1 acts as a spatial filter and target indicator, firstly selecting 12 interconnected borehole groups from numerous boreholes 12 to identify the target cavity unit that needs to be evaluated as a whole. Secondly, the locations of the boreholes 12 where fluorescence signals are observed essentially mark the key spatial nodes of the tunnel cavity. These nodes naturally become the optimal locations for subsequent three-dimensional laser scanning in step S2 to obtain accurate profile data. This enables the entire exploration and evaluation process to achieve a qualitative-first, quantitative-guided optimization logic, avoiding unnecessary high-cost data collection in non-connected areas or non-critical parts, and improving the overall economy and efficiency of the technical solution.

[0049] In some embodiments, in step S2, the tunnel profile area data is obtained by a three-dimensional laser scanner lowered into the borehole 12.

[0050] The specific technical means of step S2 (three-dimensional morphological data acquisition) is based on the core principle of using high-precision, non-contact spatial digitization technology to solve the problem of difficulty in accurately quantifying the cross-sectional morphology of irregular inclined roadways, thus providing accurate input for subsequent adaptive volume calculation.

[0051] A 3D laser scanner emits high-frequency laser pulses into the cavity of a tunnel and receives signals reflected from the tunnel's roof, floor, and sidewalls. By measuring the round-trip time or phase difference of the laser, the distance from the instrument to each reflection point on the tunnel surface can be precisely calculated. Simultaneously, a high-precision angle encoder inside the instrument records the vertical and horizontal angles of each laser beam.

[0052] By coupling distance and angle, the three-dimensional coordinates (X, Y, Z) of each reflection point in a spatial spherical coordinate system centered on the scanner can be uniquely determined. In a short time, the instrument can acquire millions of dense spatial points on the inner surface of the tunnel through high-speed rotation scanning, forming point cloud data. Essentially, this process completely and accurately digitizes the complex, irregular physical tunnel space into a discrete spatial dataset that can be processed by a computer.

[0053] After acquiring the full-space point cloud, the key to the method in this embodiment of the invention lies in extracting the tunnel cross-sectional area data perpendicular to the exploration line 11. First, in the data processing software, a reference cross-sectional plane perpendicular to the exploration line 11 is determined based on the actual spatial coordinates of borehole 12 and the designed orientation of exploration line 11. Then, using spatial geometric algorithms (such as nearest neighbor interpolation or plane cutting algorithms), the intersection line between the tunnel point cloud data and the reference cross-sectional plane is calculated, or all points within a certain thickness range near this plane are extracted. The contour formed by these points is the measured cross-section of the tunnel at the location of borehole 12. Finally, by integrating this closed contour using a polygon area calculation algorithm (such as the shoelace formula), the precise area value Si of the cross-section can be obtained.

[0054] Traditional methods rely on limited information revealed by borehole 12 or geophysical deductions for cross-section estimation, resulting in large errors and strong subjectivity. The method in this embodiment of the invention uses three-dimensional laser scanning to obtain a millimeter-precision point cloud model of the actual cross-section of the tunnel in situ and non-destructively underground. The extracted cross-sectional area data reconstructs the extremely irregular shapes (such as elliptical, horseshoe, or even more complex non-geometric shapes) formed by compression and collapse of the tunnel.

[0055] Traditional contact surveying (such as measuring tapes and cross-section gauges) or photogrammetry is difficult to implement in dark, damp, and potentially hazardous abandoned tunnels, and can only obtain a limited number of feature points. A 3D laser scanner can remotely, quickly, and automatically scan the entire visible cavity without requiring personnel to enter the hazardous cavity, greatly improving safety. Simultaneously, the acquired spatial information can detect minute depressions and protrusions.

[0056] In some embodiments, in step S3, the quantification index is the cross-sectional area variation coefficient λ, which is calculated as follows: the ratio of the standard deviation σ of all cross-sectional areas to the arithmetic mean S, i.e., λ = σ / S.

[0057] The denominator S (arithmetic mean) represents the average cross-sectional size of the tunnel along the direction of exploration line 11. It is a scale parameter used for normalization to eliminate interference caused by differences in the absolute size of the tunnel.

[0058] The numerator σ (standard deviation) represents the degree of deviation of each measured profile area from the average value, and directly reflects the fluctuation of the cross-sectional dimensions of the roadway during its spatial extension.

[0059] Therefore, the λ value is essentially a mathematical representation of the relative fluctuation range of the tunnel cross-sectional dimensions. A small λ value (e.g., λ < 0.1) indicates that the cross-sectional areas are very close, the tunnel shape is uniform and regular, and it approximates a channel with a constant cross-section. Figure 1The image shows a deformed tunnel. A large λ value (e.g., λ > 0.5) indicates a significant difference in area between adjacent cross-sections, suggesting severe contraction, expansion, or abrupt interruption in the tunnel morphology, indicating a highly irregular or severely collapsed state. Figure 1 The crushed deformation tunnel 102 and the partially collapsed tunnel 103 are shown in the figure.

[0060] The preset threshold is an empirical value used to distinguish the regularity and irregularity of the tunnel shape. When λ is less than the preset threshold, the first volume calculation model is selected, and when λ is greater than or equal to the preset threshold, the second volume calculation model is selected. The preset threshold is 0.3.

[0061] The threshold of 0.3 is not an arbitrary value, but an empirical critical point derived from a large amount of field measurement data, model calculations, and engineering back analysis.

[0062] By applying traditional regular models (such as the trapezoidal platform method) and complex models (such as the fractal function model) to known roadways with different λ values ​​(by verifying the volume through excavation or dense scanning), it was found that when λ is below a certain value, the calculation results of the two models are not significantly different, but the regular model has extremely high computational efficiency; when λ exceeds this value, the error of the regular model begins to grow nonlinearly, while the complex model can maintain stable accuracy.

[0063] A threshold of 0.3 represents a balance between computational efficiency and accuracy. When λ < 0.3, the irregularity of the tunnel morphology has not yet caused unacceptable errors in the simple integral model. In this case, using the first volumetric calculation model (the efficient standard integral model) can achieve the required accuracy for engineering purposes with minimal computational cost. When λ ≥ 0.3, the irregularity of the morphology becomes the dominant factor, and a second volumetric calculation model (such as a fractal correction model) that better characterizes complex spatial variations should be used, with accuracy as the primary objective.

[0064] Traditional methods approximate tunnel shapes using fixed geometric models (such as treating them all as trapezoids or cones), regardless of the tunnel's form, which is the main source of systematic error. The method in this invention, through the judgment of the λ value and the threshold of 0.3, enables the system to possess the ability to perceive shape and select its own model.

[0065] In some embodiments, the first volume calculation model is a standard model based on the integration of adjacent cross-sectional areas and their spacing. The calculation formula of the standard model is as follows:

[0066] Where V is the calculated volume, L is the total spacing between sections, n is the number of sections, and Si is the area of ​​the i-th section.

[0067] The design principle of this model is based on the improved cross-sectional average integral idea. Its core lies in the innovative introduction of a local correction factor that reflects the current roadway segment morphological fluctuation characteristics on the basis of the classic trapezoidal method (or average end area method). This improves the adaptability of the traditional regular model to slightly irregular morphologies while maintaining computational efficiency.

[0068] The basic framework of the model is formed by dividing two adjacent cross-sections (with areas S respectively). i and S i+1 The tunnel space between the two end faces with a spacing of L / (n-1) is regarded as a prism with a linearly changing cross section. The arithmetic mean of the two end faces is used as the average cross-sectional area of ​​the segment, which is multiplied by the segment length to obtain the segment volume. Finally, the summation is performed.

[0069] A local correction is introduced for the morphological variation coefficient λ. The correction term is a dynamic weight coefficient that is directly related to the morphology of the currently calculated segment.

[0070] (S i -S i+1 ) / (S i +S i+1 The ratio of S to S' is the rate of change of the local morphology of the current segment, describing whether the area increases or decreases and their relative magnitude between two adjacent sections. i =S i+1 When the value is 0, it indicates that the segment has an ideal uniform cross-section, and the correction term degenerates to 1, thus the formula reverts to the standard trapezoidal method. The greater the difference between the two areas, the larger the absolute value of this term, indicating that the cross-sectional change of the segment is more drastic.

[0071] λ is a global morphological fluctuation index, representing the overall irregularity of the entire roadway evaluation section (but already satisfying the relative regularity condition of λ < 0.3). λ / 2, as a global correction coefficient, controls the contribution weight of local changes to the final volume.

[0072] The correction term combines the global irregularity (λ) with local cross-sectional variations (local rate of change). Even in relatively regular roadways (where λ is small), if a segment exhibits significant local variation, the model will fine-tune the volume estimate for that segment using this correction term. As the area increases (S... i+1 >S i When the area is decreasing, the correction term is greater than 1, and the volume estimate for that segment is appropriately increased; when the area decreases, the correction term is less than 1, and the volume estimate is appropriately decreased.

[0073] Compared to the traditional simple trapezoidal method that completely ignores intermediate changes or simplifies it to a fixed cone, this model introduces a correction factor containing λ and local rate of change to achieve rule-based intelligent fine-tuning. It only increases the computational complexity by a minimal amount (one more multiplication and addition / subtraction operation) and can effectively capture and compensate for volume deviations caused by slight expansion, contraction or bending of the roadway under the premise of rules.

[0074] In some embodiments, the second volume calculation model is a fractal calculation model that introduces a morphological correction function to handle irregular cavities. The basic form of the fractal calculation model is as follows:

[0075] Where F(x, y, λ) is a fractal correction function related to the profile position coordinates and the coefficient of variation λ.

[0076] The second volumetric calculation model, namely the fractal calculation model, is used when the tunnel morphology is determined to be highly irregular (λ≥0.3). The design principle of this model is based on the approximation and integration of complex spatial morphology by fractal geometry. Its core lies in abandoning the traditional approach of connecting adjacent cross-sections with simple smooth curved surfaces, and instead acknowledging and quantifying the extremely complex, rough, and discontinuous internal surface morphology formed by the tunnel during collapse and compression deformation. By introducing a fractal correction function F(x, y, λ) related to the global morphological variation coefficient λ, this complexity is dynamically reconstructed within the integral framework.

[0077] Outer integral (with respect to z): Integrate along the direction of the roadway extension (length L), which is a continuous sampling of space.

[0078] Inner integral (with respect to D(z)): Perform a double integral over the cross-sectional region D(z) perpendicular to the extension direction. The key difference is that in traditional methods, the integrand here is a constant 1 (i.e., simply summing the areas) or a definite geometric height function. In this model, however, the integrand is F(x, y, λ).

[0079] The principle of the fractal correction function F(x, y, λ) is not a fixed function, but a family of functions whose specific form is related to the current profile position (x, y) and the global morphological variation coefficient λ.

[0080] λ serves as the control parameter for fractal complexity. λ ≥ 0.3 indicates that the tunnel morphology has entered the fractal domain, meaning that its surface roughness, void distribution, and contour irregularity exhibit statistical self-similarity. A larger λ value signifies more dramatic differences between cross-sections, and higher spatial discontinuity and complexity. The F function, by introducing λ, transforms this global, statistically significant irregularity into a corrective weight for local integral elements.

[0081] The function F(x, y, λ) has non-uniform values ​​over the cross-sectional region D(z), and can be constructed as a spatially distributed weight field or height fluctuation function. For example, it can simulate disconnected regions formed by local collapse within the cross-section (in which case F approaches 0 at the corresponding (x, y)), or simulate the situation where the effective ventilation or storage space is larger than the apparent projected area due to severe unevenness of the tunnel wall (in which case F is greater than 1 at the corresponding (x, y)).

[0082] Calculate two irregular cross sections S i and S i+1 When considering the volume between these points, the model does not assume a smooth transition surface (such as a plane or quadratic surface), but rather assumes that the true shape of the tunnel within this space is continuously composed of countless extremely complex fractal sections D(z) that vary with z.

[0083] The function F(x, y, λ) works by determining the shape of the starting and ending points (S). i and S i+1 The possible shapes of infinitely many intermediate cross sections are dynamically generated or inferred by the outline of the virtual cross section and the overall variation intensity characterized by λ, and the effective contribution volume of each virtual cross section (represented by the F function value) is integrated and accumulated.

[0084] For severely collapsed and fragmented tunnels, traditional methods (such as the trapezoidal and conical methods) typically have errors exceeding 20%-50%, rendering them ineffective for engineering guidance. This fractal model directly models and integrates the complexity itself through its core function F(x, y, λ), enabling it to more realistically reflect the effective space within the collapsed body, such as the network of voids and incompletely compacted areas.

[0085] In summary, as Figure 1 As shown, the fluorescence detection qualitative step in the method of this embodiment is intuitively displayed in the form of a cross-sectional schematic diagram, illustrating the spatial characteristics of the fluorescence diffusion effect and its engineering interpretation under different tunnel morphology conditions.

[0086] The spatial relationship between the four boreholes 12 (numbered ZK1, ZK2, ZK3, ZK4) laid out along an exploration line 11 and the underground inclined tunnel 10 intuitively shows that the detection target (irregular inclined tunnel 10) and the detection project (vertical boreholes 12) are obliquely intersecting in space.

[0087] The abstract tunnels were divided into three categories according to their degree of deformation, and the performance of fluorescence diffusion in different categories was qualitatively simulated, providing a visual basis for judging connectivity and morphology.

[0088] Slightly deformed or undeformed tunnel 101 has a clear, regular, and continuous outline. After the fluorescent material is ejected from the injection hole (such as ZK2), the diffusion range is concentrated, the outline is clear, the light intensity is uniform, and the decay is slow. The fluorescence can effectively reach the tunnel boundary and has a significant extension along the tunnel direction (axial direction), forming a bright light band with a clear boundary.

[0089] This diffusion pattern is a typical indicator of an ideal connectivity state. If such clear and stable light signals are observed in the observation wells (such as ZK1 and ZK3), it can be directly and definitively determined that the connectivity of the 12 boreholes is good and that the morphology of that section of the roadway is relatively complete.

[0090] In the squeezed and deformed roadway 102, the roadway cross-section shrinks and twists, but the overall structure has not completely collapsed and still maintains a certain degree of continuity. The fluorescence diffusion range extends far along the roadway axis, but its lateral diffusion (filling the roadway cross-section) may be uneven, and the light intensity distribution may show differences in brightness. The overall light spot may be more diffuse than that of the undeformed roadway 101, with blurred boundaries.

[0091] This indicates that although the tunnel has been narrowed or tortuous due to compression deformation, the main passage remains connected. The observation of the fluorescence signal confirms the connectivity, but its diffuse and non-uniform characteristics also indirectly suggest that there is deformation in this section of the tunnel, providing an initial warning for focusing on this area for detailed scanning in the subsequent step S2.

[0092] In partially collapsed tunnels, the roof or sidewalls partially collapse, forming deposits that may block some passages and create a complex network of voids. Fluorescent material diffuses over a wide but highly irregular range, potentially forming flow around or seeping into the collapsed area. The light signal exhibits a fragmented, patchy distribution, with a weakened concentrated visibility effect (i.e., forming a clear bright band). Light intensity decays rapidly, and what may be observed in the observation hole are flickering, weak, or intermittent spots of light.

[0093] The observation of such signals indicates that the tunnel space has not completely disappeared, but has been severely altered. The arrival of fluorescent material proves that matter (air and water vapor carrying fluorescent powder) can penetrate the collapsed structure, i.e., permeable connectivity exists. However, the weak and irregular nature of the signal also strongly suggests that the spatial morphology is highly complex, with narrow or tortuous effective channels, making it a key section where a fractal model (λ≥0.3) needs to be used in volume calculations.

[0094] The figure illustrates the operation mode of fluorescent jetting from well ZK2 and simultaneous observation from wells ZK1, ZK3, and ZK4, visually demonstrating the implementation method of single-well jetting and multi-well observation.

[0095] The fluorescence diffusion region 104 of the ZK1 well at the top of the tunnel may show a weaker fluorescence effect than that of the ZK3 and ZK4 wells below. This simulates the physical phenomenon that fluorescent powder or droplets are more likely to settle and diffuse downwards under the influence of gravity, indicating that the gravitational factor needs to be considered when interpreting the observation results, demonstrating the scientific nature of the method and the comprehensiveness of the problem-solving approach.

[0096] After simulating injection at hole ZK2, fluorescence with different characteristics was observed at holes ZK1, ZK3, and ZK4. This demonstrated that by combining the signal intensity and distribution pattern of multiple observation points, the spatial distribution of the entire inclined tunnel 10 along the exploration line 11 and the deformation status of different sections could be qualitatively determined.

[0097] The open-pit mine inclined roadway 10 detection and evaluation system of this invention is used to implement the method in any of the above embodiments.

[0098] The open-pit mine inclined roadway 10 detection and evaluation system of this invention includes a fluorescence detection module, a three-dimensional data acquisition module, and a data processing and calculation module.

[0099] The fluorescence detection module performs the fluorescence connectivity detection step S1, and includes a fluorescence mixing device and a borehole 12 television observation device. The 3D data acquisition module performs the 3D morphological data acquisition step S2, and includes a 3D laser scanning device. The data processing and calculation module is configured to perform the adaptive volume calculation step S3.

[0100] The core function of the fluorescence detection module is to qualitatively determine spatial connectivity. It consists of a transmitter (fluorescence mixing device) and a receiver (drill hole 12 TV). This module is not responsible for precise measurement; its design goal is to provide evidence of existence (whether the light signal is visible). Its working principle is to excite (eject) an easily identifiable physical signal (fluorescence) and receive the signal at a remote end, thereby verifying complex connections with extremely simple logic.

[0101] The function of the 3D data acquisition module is to achieve precise digitization of spatial morphology. Centered on a 3D laser scanning device, its goal is to generate high-density, high-precision spatial point cloud data of the tunnel surface. This module operates independently of the detection module, and is only activated at key locations after the detection module confirms connectivity. This ensures that the high-precision data acquisition is targeted and focused, avoiding data redundancy.

[0102] The data processing and computation module, serving as the system's intelligent hub, realizes the transformation from data to knowledge. This module receives raw point cloud data from the acquisition module and executes a series of algorithms, including profile extraction, area calculation, and coefficient of variation (λ) analysis. Its core principle lies in its built-in λ-based decision tree logic and corresponding volume calculation algorithm library (standard model and fractal model). Based on the algorithm's judgment results, it dynamically calls the appropriate model for calculation and finally outputs a volume evaluation report.

[0103] The fluorescent mixing spraying device of this invention is used in the system of any of the above embodiments.

[0104] like Figure 2 As shown, the fluorescent mixing spraying device of this embodiment includes a drill bit body 20, and a component integrated on the drill bit body 20: The material storage and mixing section is used to store and mix fluorescent materials. The material storage and mixing section includes a fluorescent storage tank 201 and a water-powder mixing chamber 202 connected thereto.

[0105] The pressurization drive unit is connected to the material storage and mixing unit and is used to provide jet power. The pressurization drive unit includes a water supply unit and an air supply pressurization unit that are respectively connected to the water-powder mixing chamber 202 via a water pipe 203 and an air pipe 204.

[0106] The controllable spraying section is connected to the material storage and mixing section and is used to directionally spray the mixed fluorescent material. The controllable spraying section includes a nozzle 205 and a controllable rotating bend 206. One end of the nozzle 205 is connected to the water-powder mixing chamber 202, and the side wall of the nozzle 205 is provided with a plurality of spray holes 2051. The other end of the nozzle 205 is connected to the controllable rotating bend 206.

[0107] The dry powder fluorescent material is pre-stored in a fluorescent storage tank 201 for long-term preservation and underground transportation. During operation, the dry powder is quantitatively fed into the water-powder mixing chamber 202 under controlled conditions. At the same time, precisely metered clean water is injected into the mixing chamber through the water pipe 203 (corresponding to the water supply unit).

[0108] The independent storage tank design prevents the phosphor from becoming damp and caking; it is separated from the mixing chamber containing water, ensuring that mixing only occurs before spraying and preventing clogging. The water-powder mixture forms a phosphor slurry, which has better suspension, diffusion, and adhesion in humid tunnel environments compared to dry powder spraying, and can be more effectively observed by borehole 12 television.

[0109] The water injection (through water pipe 203) is used not only for mixing but also for transport and initial wetting. The gas pipe 204 instantly injects high-pressure gas from the ground into the water-powder mixing chamber 202 or the fluorescent powder spraying area (nozzle 205) downstream of it.

[0110] Air pressurization is the core power source of this device. The highly compressible gas can store and release enormous amounts of instantaneous energy, propelling the mixed fluorescent slurry as a high-speed jet from nozzle 205. This overcomes potential hydrostatic pressure and viscous resistance within borehole 12, ensuring the slurry has sufficient initial kinetic energy to diffuse deeper into the tunnel. Ground control (via water pipe 203 and air pipe 204) enables remote and precise regulation of pressure and flow rate.

[0111] Multiple nozzle holes 2051 on the sidewall of nozzle 205 form a basic, multi-directional static spray channel, ensuring that an initial three-dimensional diffuser is sprayed out, covering the basic direction.

[0112] The controllable rotating bend 206 can rotate or swing within a certain angle range (e.g., 0-360 degrees) under ground command control. When it rotates, the jet of fluorescent liquid dynamically scans in the horizontal direction or within a specific cone angle, forming a spatial dispersion sector much larger than the range of the fixed nozzle 205.

[0113] The controllable rotation function expands the effective range of a single injection. For inclined, unpredictable tunnels, operators can analyze preliminary borehole television images or geological data to purposefully control the injection direction, increasing the probability of the tracer entering the target channel and significantly improving the success rate and detection radius of connectivity detection.

[0114] Furthermore, the fluorescent mixing spray device in this embodiment of the invention is fixed at the bottom of the borehole 12 by fixing the air pressure valve 207, ensuring the stability and reliability of the fluorescent slurry spray.

[0115] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," "counterclockwise," "axial," "radial," and "circumferential" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing this invention and simplifying the description, and are not intended to indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0116] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0117] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection, an electrical connection, or a connection that allows communication between them; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components, unless otherwise explicitly limited. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0118] In this invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can mean that the first feature is in direct contact with the second feature, or that the first feature is in indirect contact with the second feature through an intermediate medium. Furthermore, "above," "over," and "on top" of the second feature can mean that the first feature is directly above or diagonally above the second feature, or simply that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature can mean that the first feature is directly below or diagonally below the second feature, or simply that the first feature is at a lower horizontal level than the second feature.

[0119] In this invention, the terms "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., refer to a specific feature, structure, material, or characteristic described in connection with that embodiment or example, which is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0120] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for detecting and evaluating inclined roadways in open-pit mines, characterized in that, include: S1. Perform fluorescent material injection and optical observation in at least two boreholes along the target exploration line, and determine the spatial connectivity of the tunnel cavity between boreholes based on the observation results. S2. For roadway sections that are determined to be connected, obtain the roadway profile area data perpendicular to the exploration line at each borehole location. S3. Based on the cross-sectional area data, calculate a quantitative index characterizing the degree of change in cross-sectional shape. Based on the comparison result between the quantitative index and a preset threshold, adaptively select the corresponding volume calculation model to calculate the volume of the tunnel cavity.

2. The method for detecting and evaluating inclined roadways in open-pit mines according to claim 1, characterized in that, In step S1, the fluorescent material ejection and optical observation process includes: Fluorescent material is sprayed in one borehole using a fluorescent mixing sprayer, and borehole television is used to observe the process in at least one adjacent borehole. The presence or absence of fluorescence diffusion is used to qualitatively determine whether the tunnel cavity is connected.

3. The method for detecting and evaluating inclined roadways in open-pit mines according to claim 1, characterized in that, In step S2, the tunnel profile area data is obtained by a three-dimensional laser scanner lowered into the borehole.

4. The method for detecting and evaluating inclined roadways in open-pit mines according to claim 1, characterized in that, In step S3, the quantitative index is the cross-sectional area variation coefficient λ, which is calculated as follows: calculate the ratio of the standard deviation σ of all cross-sectional areas to the arithmetic mean S, i.e., λ = σ / S; The preset threshold is an empirical value used to distinguish the regularity and irregularity of the tunnel morphology; when λ is less than the preset threshold, the first volume calculation model is selected, and when λ is greater than or equal to the preset threshold, the second volume calculation model is selected, wherein the preset threshold is 0.

3.

5. The method for detecting and evaluating inclined roadways in open-pit mines according to claim 4, characterized in that, The first volume calculation model is a standard model based on the integration of adjacent cross-sectional areas and their spacing. The calculation formula of the standard model is as follows: Where V is the calculated volume, L is the total spacing between sections, n is the number of sections, and Si is the area of ​​the i-th section.

6. The method for detecting and evaluating inclined roadways in open-pit mines according to claim 4, characterized in that, The second volume calculation model is a fractal calculation model that introduces a morphological correction function to handle irregular cavities. The basic form of the fractal calculation model is as follows: Wherein, F(x, y, λ) is a fractal correction function related to the profile position coordinates and the coefficient of variation λ.

7. A detection and evaluation system for inclined roadways in open-pit mines, used to implement the method according to any one of claims 1-6, characterized in that, include: A fluorescence detection module, which is used to perform the fluorescence connectivity detection step of S1; A three-dimensional data acquisition module, which is used to perform the three-dimensional morphological data acquisition step S2; The data processing and calculation module is configured to perform the adaptive volume calculation step of S3.

8. The open-pit mine inclined roadway detection and evaluation system according to claim 7, characterized in that, The fluorescence detection module includes a fluorescence mixing device and a borehole television observation device, and the three-dimensional data acquisition module includes a three-dimensional laser scanning device.

9. A fluorescent mixing spraying device for the system according to claim 7 or 8, characterized in that, Includes the drill bit body, and components integrated onto the drill bit body: A material storage and mixing section for storing and mixing fluorescent materials; A pressurization drive unit, connected to the material storage and mixing unit, is used to provide injection power; A controllable spraying section is connected to the material storage and mixing section for directional spraying of the mixed fluorescent material.

10. The fluorescent mixing spraying device according to claim 9, characterized in that, The material storage and mixing section includes a fluorescent storage tank and a water-powder mixing chamber connected thereto; The pressurization drive unit includes a water supply unit and an air supply pressurization unit that are respectively connected to the water-powder mixing chamber through a water pipe and an air pipe; The controllable spraying section includes a nozzle and a controllable rotating bend. One end of the nozzle is connected to the water-powder mixing chamber, and the side wall of the nozzle is provided with multiple spray holes. The other end of the nozzle is connected to the controllable rotating bend.

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