A surrounding rock quality detection and grouting method

Abstract

This invention relates to the field of tunnel surrounding rock construction technology, specifically to a method for surrounding rock quality detection and grouting. It includes the following steps: S1, collecting data on the rotational speed of the drilling machine, the air volume, air pressure, and air temperature of the air compressor, and the grouting volume and grouting pressure during grouting; S2, based on the collected data on the rotational speed, air volume, air pressure, and air temperature during drilling at a predetermined location, performing quality detection on the surrounding rock in the drilling area to determine the degree of fracture development; S3, based on the degree of fracture development, predicting the required grouting volume for the drilling using a pre-trained surrounding rock prediction model; S4, obtaining the prediction error based on the actual grouting volume obtained during drilling, comparing the actual grouting volume with the required grouting volume, and correcting the surrounding rock prediction model based on the prediction error.

Description

Technical Field

[0001] This invention relates to the field of tunnel surrounding rock construction technology, specifically to a method for detecting the quality of surrounding rock and grouting. Background Technology

[0002] Surrounding rock refers to the rock mass surrounding an underground cavern, and its properties and characteristics directly affect the stability, safety, and difficulty of construction. Accurate identification of surrounding rock type is crucial in the construction and operation of various underground projects, such as tunnels and mines. Before construction on the surrounding rock, it is necessary to conduct quality testing on the surrounding rock and reinforce it according to the quality test results, so as to avoid safety accidents such as collapse caused by broken and fragile surrounding rock during construction.

[0003] Deep-hole grouting is an underground engineering reinforcement technology aimed at improving the stability of surrounding rock, preventing groundwater leakage, and enhancing rock mechanical properties. It is widely used in tunnels, underground caverns, and foundation pit support projects. The implementation process includes drilling, hole cleaning, grouting, sealing, and curing. Drilling involves selecting a drilling rig to ensure that the hole depth, diameter, and spacing meet geological conditions and design requirements. Hole cleaning removes debris to ensure cleanliness. Grouting involves injecting grout prepared with grout into the deep hole through a grouting pipe. The grouting pressure and speed must be controlled to ensure uniform grout diffusion, forming a reinforced body. After sealing, curing is performed to enhance the reinforcement strength and stability.

[0004] Existing rock grouting methods typically follow a relatively fixed implementation process. First, boreholes are drilled according to the design drawings, using a drilling rig at predetermined locations to ensure the hole depth, diameter, and spacing meet design requirements. After drilling, the holes are cleaned to remove rock powder and debris, ensuring unobstructed grouting channels. Then comes the core grouting stage, where a grouting pump injects the prepared grout into the borehole. During this process, operators rely primarily on experience to control the grouting pressure and rate, striving for uniform diffusion of the grout within the rock strata and filling of fissures. After grouting, the boreholes are sealed, and the reinforced rock is cured for a period until it reaches its design strength.

[0005] However, this approach relies heavily on geological sketches, core samples, or simple tests from a few boreholes to assess the degree of rock fissure development and rock mass integrity before grouting. These methods are either highly subjective or fail to reflect the real-time conditions of the surrounding rock throughout the drilling process, especially at depth, resulting in an inaccurate and incomplete assessment of grouting requirements. Summary of the Invention

[0006] The technical problem solved by this invention is to provide a method for detecting and grouting surrounding rock quality, which can improve the accuracy of crack identification and grouting volume prediction.

[0007] The basic solution provided by this invention is a method for detecting and grouting surrounding rock quality, comprising the following steps: S1. Collect the rotation speed of the bolt drilling machine, the air volume, air pressure and air temperature of the air compressor, and the grouting volume and grouting pressure of the grouting equipment during grouting. S2. Based on the rotary head speed, air volume, air pressure and air temperature collected when the equipment drills at a predetermined drilling location, the quality of the surrounding rock in the drilling area is tested to obtain the degree of fracture development in the surrounding rock. S3. Based on the degree of fracture development in the surrounding rock, predict the required grouting volume for this borehole using a pre-trained surrounding rock prediction model; S4. By obtaining the actual grouting volume during the borehole grouting, the prediction error is obtained based on the actual grouting volume and the required grouting volume, and the surrounding rock prediction model is corrected based on the prediction error.

[0008] Through the coordinated operation of construction equipment and sensing equipment, intelligent closed-loop control of the surrounding rock quality detection and grouting process is achieved. The construction equipment includes anchor bolting machines and grouting machines. The sensing equipment collects data in real time on the drilling head rotation speed, air volume, air pressure, and air temperature, as well as the grouting volume and grouting pressure during grouting. Based on the drilling parameters, the degree of fracture development in the surrounding rock is assessed. Based on the degree of fracture development, the required grouting volume is predicted through a pre-trained model. The model is dynamically corrected by comparing the error between the actual grouting volume and the predicted grouting volume.

[0009] Compared to existing technologies, this approach achieves fully automated management of the entire process of surrounding rock quality detection and grouting reinforcement. Through real-time data acquisition and iterative model optimization, it significantly improves the accuracy of fracture identification and the reliability of grout volume prediction. Compared to traditional construction methods that rely on manual experience, this solution reduces errors from subjective judgment and can quickly adapt to complex and changing geological conditions, thereby effectively avoiding resource waste and safety hazards caused by insufficient or excessive grouting. Simultaneously, the closed-loop control mechanism ensures that the model continuously improves itself during construction, which in the long run can improve construction efficiency, reduce maintenance costs, and enhance the overall stability and safety of the project.

[0010] Furthermore, S2 includes the following steps: S21. Obtain the real-time rotational speed of the rotor. Wind pressure Air volume and wind temperature ; S22. Obtain the reference rotation speed for drilling under intact rock strata of the current borehole surrounding rock type. Reference wind pressure Reference air volume and reference wind temperature Combined with real-time collected rotor speed Wind pressure Air volume and wind temperature Calculate the influence function of rotational speed respectively. Wind pressure influence function Air volume influence function and wind temperature influence function :

[0011]

[0012]

[0013]

[0014] S23. Based on the speed influence function Wind pressure influence function Air volume influence function and wind temperature influence function Calculate fracture development index :

[0015] S24. Based on fracture development indicators Determine the degree of fracture development.

[0016] This method accurately assesses the degree of fracture development in surrounding rock through multi-source data fusion and quantitative analysis. Specifically, real-time acquisition of borehole parameters, including borehole rotation speed, air pressure, air volume, and air temperature, is used. Baseline values ​​are obtained for intact rock strata based on rock type, and the influence functions of rotation speed, air pressure, air volume, and air temperature are calculated. These influence functions are then weighted and fused to obtain a fracture development index C, which ultimately determines the degree of fracture development. Transforming complex, multi-dimensional borehole parameters into a single quantitative index makes the fracture assessment process more objective and scientific. By introducing baseline value comparison and function calculation, this method effectively eliminates environmental interference and highlights the influence of surrounding rock characteristics on parameters. The dynamic adjustment capability of the weighting coefficients enhances the model's adaptability to different rock strata, improving the universality and accuracy of fracture identification. Furthermore, the quantitative index provides a reliable data foundation for subsequent grouting prediction, avoiding the risk of misjudgment caused by reliance on experience in traditional methods, thereby improving the controllability and precision of the entire construction process.

[0017] Furthermore, S2 also includes the following steps: S25. Record the rotational speed of the drill bit in the current interval after each preset drilling distance. Wind pressure Air volume and wind temperature And calculate the fracture development index C; S26. Generate a fracture development map of the surrounding rock based on the fracture development index C of each interval.

[0018] Drilling parameters are recorded in segments according to the preset drilling distance, and the fracture development index C is calculated to generate a fracture development map along the drilling depth. The spatial distribution of fractures in the surrounding rock is visualized to accurately locate vulnerable sections, guide targeted grouting reinforcement, and avoid the risk of local collapse.

[0019] Furthermore, S3 includes the following steps: S31. Based on the borehole length and radius, generate the basic grouting volume:

[0020] Where r is the borehole radius, H is the borehole length, and η is the slurry diffusion coefficient; S32 generates grouting correction parameters for grouting into boreholes based on fracture development index C:

[0021] in Indicates the impact index of fractures. Indicates the grout absorption coefficient of the crack. Indicates the pressure sensitivity coefficient. Indicates the maximum operating grouting pressure; S33. The required grouting volume is obtained by combining the basic grouting volume and the grouting correction volume: .

[0022] The grouting volume prediction is decomposed into two parts: basic grouting volume and fracture-corrected grouting volume. Based on the borehole geometry, including radius and length, and the grout diffusion coefficient, the basic grouting volume is calculated. The corrected grouting volume is calculated based on the fracture development index C, fracture influence index, fracture grout absorption coefficient, pressure sensitivity coefficient, and maximum operating grouting pressure. The final required grouting volume is the sum of the two. This separation of physical processes makes the prediction model more closely match actual engineering needs. The basic grouting volume reflects the basic requirements for borehole filling, while the corrected volume fully considers the enhanced effects of fracture development and grouting pressure on grout absorption. Introducing the pressure sensitivity coefficient accurately captures the grout penetration behavior under high-pressure grouting conditions, thereby improving prediction accuracy. This layered prediction mechanism avoids the biases that may result from a single model, ensures the rationality and reliability of the grouting volume estimation, effectively prevents insufficient or excessive grout, optimizes material utilization efficiency, and reduces construction delays or safety risks caused by inaccurate predictions.

[0023] Furthermore, S4 includes the following steps; S41, used to calculate the prediction error based on the actual grouting volume and the predicted required grouting volume:

[0024] S42. Calculate the crack grout absorption coefficient based on the prediction error. Corrections;

[0025] in The learning rate; Corrected crack grout absorption coefficient .

[0026] Continuous optimization is achieved by dynamically adjusting model parameters based on prediction errors. The error between the actual grouting volume and the predicted required grouting volume is calculated. The grout absorption coefficient of the fracture is corrected based on the error value, learning rate, fracture influence index, pressure sensitivity coefficient, and maximum grouting pressure. The correction amount is directly proportional to the error and inversely proportional to the fracture correction term, while the learning rate controls the adjustment magnitude. This enables incremental learning of the model, allowing it to quickly adapt to the geological characteristics of specific sites. By optimizing only the key parameter, the grout absorption coefficient of the fracture, the stability and convergence of the model are ensured, avoiding instability that may result from over-adjustment. The correction process is based on actual construction data, allowing the model to continuously approximate reality during iterations, significantly improving the accuracy of grouting volume prediction in the long run. This adaptive mechanism reduces dependence on initial model parameters, enhances system robustness, reduces the need for manual intervention, improves the level of construction automation, and provides a solid guarantee for project quality and economy.

[0027] Furthermore, it also includes the following steps: S51. Correlate and store the fracture development index C with the actual grouting volume for each instance to form historical data, and obtain the relationship curve between the fracture development degree C and the grouting volume based on the stored historical data. Attached Figure Description

[0028] Figure 1 This is a schematic flowchart of an embodiment of a surrounding rock quality detection and grouting method according to the present invention. Detailed Implementation

[0029] The following detailed description illustrates the specific implementation method: The basic implementation examples are as follows: Figure 1 As shown: A method for detecting and grouting surrounding rock quality includes the following steps: S1. Collect the rotation speed of the bolt drilling machine, the air volume, air pressure and air temperature of the air compressor, and the grouting volume and grouting pressure of the grouting equipment during grouting. S2. Based on the rotary head speed, air volume, air pressure and air temperature collected when the equipment drills at a predetermined drilling location, the quality of the surrounding rock in the drilling area is tested to obtain the degree of fracture development in the surrounding rock. S3. Based on the degree of fracture development in the surrounding rock, predict the required grouting volume for this borehole using a pre-trained surrounding rock prediction model; S4. By obtaining the actual grouting volume during the borehole grouting, the prediction error is obtained based on the actual grouting volume and the required grouting volume, and the surrounding rock prediction model is corrected based on the prediction error.

[0030] Through the coordinated operation of construction equipment and sensing equipment, intelligent closed-loop control of the surrounding rock quality detection and grouting process is achieved. The construction equipment includes anchor bolting machines and grouting machines. The sensing equipment collects data in real time on the drilling head rotation speed, air volume, air pressure, and air temperature, as well as the grouting volume and grouting pressure during grouting. Based on the drilling parameters, the degree of fracture development in the surrounding rock is assessed. Based on the degree of fracture development, the required grouting volume is predicted through a pre-trained model. The model is dynamically corrected by comparing the error between the actual grouting volume and the predicted grouting volume.

[0031] Compared to existing technologies, this approach achieves fully automated management of the entire process of surrounding rock quality detection and grouting reinforcement. Through real-time data acquisition and iterative model optimization, it significantly improves the accuracy of fracture identification and the reliability of grout volume prediction. Compared to traditional construction methods that rely on manual experience, this solution reduces errors from subjective judgment and can quickly adapt to complex and changing geological conditions, thereby effectively avoiding resource waste and safety hazards caused by insufficient or excessive grouting. Simultaneously, the closed-loop control mechanism ensures that the model continuously improves itself during construction, which in the long run can improve construction efficiency, reduce maintenance costs, and enhance the overall stability and safety of the project.

[0032] S2 includes the following steps: S21. Obtain the real-time rotational speed of the rotor. Wind pressure Air volume and wind temperature ; S22. Obtain the reference rotation speed for drilling under intact rock strata of the current borehole surrounding rock type. Reference wind pressure Reference air volume and reference wind temperature Combined with real-time collected rotor speed Wind pressure Air volume and wind temperature Calculate the influence function of rotational speed respectively. Wind pressure influence function Air volume influence function and wind temperature influence function :

[0033]

[0034]

[0035]

[0036] S23. Based on the speed influence function Wind pressure influence function Air volume influence function and wind temperature influence function Calculate fracture development index :

[0037] S24. Based on fracture development indicators Determine the degree of fracture development.

[0038] This method accurately assesses the degree of fracture development in surrounding rock through multi-source data fusion and quantitative analysis. Specifically, real-time acquisition of borehole parameters, including borehole rotation speed, air pressure, air volume, and air temperature, is used. Baseline values ​​are obtained for intact rock strata based on rock type, and the influence functions of rotation speed, air pressure, air volume, and air temperature are calculated. These influence functions are then weighted and fused to obtain a fracture development index C, which ultimately determines the degree of fracture development. Transforming complex, multi-dimensional borehole parameters into a single quantitative index makes the fracture assessment process more objective and scientific. By introducing baseline value comparison and function calculation, this method effectively eliminates environmental interference and highlights the influence of surrounding rock characteristics on parameters. The dynamic adjustment capability of the weighting coefficients enhances the model's adaptability to different rock strata, improving the universality and accuracy of fracture identification. Furthermore, the quantitative index provides a reliable data foundation for subsequent grouting prediction, avoiding the risk of misjudgment caused by reliance on experience in traditional methods, thereby improving the controllability and precision of the entire construction process.

[0039] S2 further includes the following steps: S25. Record the rotational speed of the drill bit in the current interval after each preset drilling distance. Wind pressure Air volume and wind temperature And calculate the fracture development index C; S26. Generate a fracture development map of the surrounding rock based on the fracture development index C of each interval.

[0040] Drilling parameters are recorded in segments according to the preset drilling distance, and the fracture development index C is calculated to generate a fracture development map along the drilling depth. The spatial distribution of fractures in the surrounding rock is visualized to accurately locate vulnerable sections, guide targeted grouting reinforcement, and avoid the risk of local collapse.

[0041] S3 includes the following steps: S31. Based on the borehole length and radius, generate the basic grouting volume:

[0042] Where r is the borehole radius, H is the borehole length, and η is the slurry diffusion coefficient; S32 generates grouting correction parameters for grouting into boreholes based on fracture development index C:

[0043] in Indicates the impact index of fractures. Indicates the grout absorption coefficient of the crack. Indicates the pressure sensitivity coefficient. Indicates the maximum operating grouting pressure; S33. The required grouting volume is obtained by combining the basic grouting volume and the grouting correction volume: .

[0044] The grouting volume prediction is decomposed into two parts: basic grouting volume and fracture-corrected grouting volume. Based on the borehole geometry, including radius and length, and the grout diffusion coefficient, the basic grouting volume is calculated. The corrected grouting volume is calculated based on the fracture development index C, fracture influence index, fracture grout absorption coefficient, pressure sensitivity coefficient, and maximum operating grouting pressure. The final required grouting volume is the sum of the two. This separation of physical processes makes the prediction model more closely match actual engineering needs. The basic grouting volume reflects the basic requirements for borehole filling, while the corrected volume fully considers the enhanced effects of fracture development and grouting pressure on grout absorption. Introducing the pressure sensitivity coefficient accurately captures the grout penetration behavior under high-pressure grouting conditions, thereby improving prediction accuracy. This layered prediction mechanism avoids the biases that may result from a single model, ensures the rationality and reliability of the grouting volume estimation, effectively prevents insufficient or excessive grout, optimizes material utilization efficiency, and reduces construction delays or safety risks caused by inaccurate predictions.

[0045] S4 includes the following steps; S41, used to calculate the prediction error based on the actual grouting volume and the predicted required grouting volume:

[0046] S42. Calculate the crack grout absorption coefficient based on the prediction error. Corrections;

[0047] in The learning rate; Corrected crack grout absorption coefficient .

[0048] Continuous optimization is achieved by dynamically adjusting model parameters based on prediction errors. The error between the actual grouting volume and the predicted required grouting volume is calculated. The grout absorption coefficient of the fracture is corrected based on the error value, learning rate, fracture influence index, pressure sensitivity coefficient, and maximum grouting pressure. The correction amount is directly proportional to the error and inversely proportional to the fracture correction term, while the learning rate controls the adjustment magnitude. This enables incremental learning of the model, allowing it to quickly adapt to the geological characteristics of specific sites. By optimizing only the key parameter, the grout absorption coefficient of the fracture, the stability and convergence of the model are ensured, avoiding instability that may result from over-adjustment. The correction process is based on actual construction data, allowing the model to continuously approximate reality during iterations, significantly improving the accuracy of grouting volume prediction in the long run. This adaptive mechanism reduces dependence on initial model parameters, enhances system robustness, reduces the need for manual intervention, improves the level of construction automation, and provides a solid guarantee for project quality and economy.

[0049] It also includes the following steps: S51. Correlate and store the fracture development index C with the actual grouting volume for each instance to form historical data, and obtain the relationship curve between the fracture development degree C and the grouting volume based on the stored historical data.

[0050] The above are merely embodiments of the present invention. Commonly known structures and characteristics are not described in detail here. Those skilled in the art are aware of all common technical knowledge in the field prior to the application date or priority date, are aware of all existing technologies in that field, and have the ability to apply conventional experimental methods prior to that date. Those skilled in the art can, under the guidance of this application, improve and implement this solution in combination with their own capabilities. Some typical known structures or methods should not be obstacles for those skilled in the art to implement this application. It should be noted that those skilled in the art can make several modifications and improvements without departing from the structure of the present invention. These should also be considered within the scope of protection of the present invention, and will not affect the effectiveness of the implementation of the present invention or the practicality of the patent. The scope of protection claimed in this application should be determined by the content of its claims, and the specific embodiments described in the specification can be used to interpret the content of the claims.

Claims

1. A method for detecting and grouting surrounding rock quality, characterized in that: Includes the following steps: S1. Collect the rotation speed of the bolt drilling machine, the air volume, air pressure and air temperature of the air compressor, and the grouting volume and grouting pressure of the grouting equipment during grouting. S2. Based on the rotary head speed, air volume, air pressure and air temperature collected when the equipment drills at a predetermined drilling location, the quality of the surrounding rock in the drilling area is tested to obtain the degree of fracture development in the surrounding rock. S3. Based on the degree of fracture development in the surrounding rock, predict the required grouting volume for this borehole using a pre-trained surrounding rock prediction model; S4. By obtaining the actual grouting volume during the borehole grouting, the prediction error is obtained based on the actual grouting volume and the required grouting volume, and the surrounding rock prediction model is corrected based on the prediction error.

2. The method for detecting and grouting surrounding rock quality according to claim 1, characterized in that: S2 includes the following steps: S21. Obtain the real-time rotational speed of the rotor. Wind pressure Air volume and wind temperature ; S22. Obtain the reference rotation speed for drilling under intact rock strata of the current borehole surrounding rock type. Reference wind pressure Reference air volume and reference wind temperature Combined with real-time collected rotor speed Wind pressure Air volume and wind temperature Calculate the influence function of rotational speed respectively. Wind pressure influence function Air volume influence function and wind temperature influence function : S23. Based on the speed influence function Wind pressure influence function Air volume influence function and wind temperature influence function Calculate fracture development index : S24. Based on fracture development indicators Determine the degree of fracture development.

3. The method for detecting and grouting surrounding rock quality according to claim 2, characterized in that: S2 further includes the following steps: S25. Record the rotational speed of the drill bit in the current interval after each preset drilling distance. Wind pressure Air volume and wind temperature And calculate the fracture development index C; S26. Generate a fracture development map of the surrounding rock based on the fracture development index C of each interval.

4. The method for detecting and grouting surrounding rock quality according to claim 3, characterized in that: S3 includes the following steps: S31. Based on the borehole length and radius, generate the basic grouting volume: Where r is the borehole radius, H is the borehole length, and η is the slurry diffusion coefficient; S32 generates grouting correction parameters for grouting into boreholes based on fracture development index C: in Indicates the impact index of fractures. Indicates the grout absorption coefficient of the crack. Indicates the pressure sensitivity coefficient. Indicates the maximum operating grouting pressure; S33, the required grouting volume is obtained from the basic grouting volume and the grouting correction volume: 。 5. The method for detecting and grouting surrounding rock quality according to claim 4, characterized in that: S4 includes the following steps; S41, used to calculate the prediction error based on the actual grouting volume and the predicted required grouting volume: S42. Calculate the crack grout absorption coefficient based on the prediction error. Corrections; in The learning rate; Corrected crack grout absorption coefficient .

6. The method for detecting and grouting surrounding rock quality according to claim 5, characterized in that: It also includes the following steps: S51. Correlate and store the fracture development index C with the actual grouting volume for each time to form historical data, and obtain the relationship curve between fracture development degree C and grouting volume based on the stored historical data.

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