Method for measuring and evaluating the cracking range of engineering surrounding rock based on dynamic response

Abstract

The present application relates to geotechnical engineering detection technical field, provide a kind of engineering surrounding rock crack damage range evaluation method based on dynamic response, comprising: target engineering is carried out geological condition analysis and dynamic detection analysis, determine detection scheme;According to detection scheme, acoustic wave test system is laid out;Through acoustic wave test system, sound wave acquisition data is monitored and obtained in measuring hole;According to sound wave acquisition data, preliminary analysis and calculation wave velocity-depth relationship curve;Based on wave velocity-depth relationship curve, using dynamic determination model analyzes and judges crack damage range boundary;According to crack damage range boundary, crack damage range is supported design;The supporting effect is verified, and dynamic determination model is optimized and updated by backtracking analysis.This application realizes the dynamic response evaluation of engineering surrounding rock crack damage range, according to the actual situation of engineering, the measuring point is laid out, improves the flexibility of detection scheme, so that more comprehensive and accurate detection and support, provides more reliable safety guarantee for engineering implementation.

Description

Technical Field

[0001] This invention relates to the field of geotechnical engineering detection technology, and in particular to a method for evaluating the extent of cracks in surrounding rock in engineering based on dynamic response. Background Technology

[0002] As underground engineering projects in my country's transportation, water conservancy, and energy sectors develop towards deeper and more complex geological conditions, the safety and stability of tunnels and underground caverns during construction and operation face severe challenges. Under the influence of excavation unloading, stress redistribution, and external disturbances, the surrounding rock can develop and expand micro-cracks, potentially evolving into macroscopic fractures, thus affecting the safety of the support structure and even triggering disasters such as collapses. Therefore, accurately and in real-time determining the extent of cracks (fractures and damage) in the surrounding rock is crucial for scientifically evaluating its stability, optimizing support parameters, and ensuring construction safety. The extent of rock cracks, also known as the loosened zone, refers to the area around the cavern where rock fractures develop and mechanical properties significantly deteriorate due to stress redistribution and construction disturbances after underground engineering excavation. Accurate determination of its extent is a key basis for underground engineering support design.

[0003] Currently, commonly used methods for detecting the extent of surrounding rock fractures in engineering mainly rely on single or combined technologies such as acoustic testing, borehole photography, and ground-penetrating radar. These methods are largely based on static engineering types and cross-sectional shapes, which not only fail to address the dynamic uncertainties of underground engineering, potentially leading to blind spots or insufficient support in critical risk areas and posing safety hazards, but also have many limitations in practice. For example, the rigid layout of measuring points lacks adaptability to different engineering scenarios such as subway sections, highway tunnels, railway tunnels, and underground chambers, easily resulting in blind spots when monitoring complex situations; the judgment criteria are singular, lacking dynamic adjustment mechanisms for different geological conditions, making it difficult to guarantee the accuracy and consistency of judgment results under different geological conditions; verification methods are insufficient, lacking effective in-situ verification methods to check the results, making it difficult to guarantee the reliability of the detection results; and the correlation between detection and support design is weak, with design parameters needing to be more targeted. Therefore, a new method for assessing the extent of surrounding rock fractures in engineering is urgently needed to at least solve some of the above problems. Summary of the Invention

[0004] The purpose of this invention is to provide a dynamic response-based method for evaluating the extent of cracks in the surrounding rock of an engineering project. This method enables dynamic response evaluation of the extent of cracks in the surrounding rock, allows for the layout of measuring points according to the actual conditions of the project, improves the flexibility of the detection scheme, and enables more comprehensive and accurate detection and support, thus providing a more reliable safety guarantee for the implementation of the project.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a method for evaluating the extent of crack damage in engineering surrounding rock based on dynamic response, comprising: Geological condition analysis and dynamic detection analysis were conducted for the target project to determine the detection plan; The acoustic wave testing system was deployed according to the detection plan; Acoustic wave data is acquired by monitoring and collecting data in the test hole using an acoustic wave testing system. Preliminary analysis and calculations were performed based on the acoustic wave acquisition data to determine the wave velocity-depth relationship curve; A dynamic judgment model is used to analyze and determine the boundary of the crack damage range based on the wave velocity-depth relationship curve. The support design for the cracked area is based on the boundary of the cracked area; The support effect was verified, and the dynamic judgment model was optimized and updated through backtracking analysis.

[0006] Preferably, geological condition analysis and dynamic detection analysis are conducted for the target project, including: To obtain engineering design data and geological survey reports for the target project, and to determine the project type, cross-sectional shape, cross-sectional dimensions and surrounding rock grade; Based on the project type, cross-sectional shape, cross-sectional dimensions, and surrounding rock grade, an initial static analysis is conducted using a parametric measuring point layout system to calculate benchmark parameters and determine the benchmark scheme. The benchmark parameters include the number of measuring holes and the drilling depth. A dynamic response mechanism is adopted to dynamically adjust the project based on real-time data during the implementation process, resulting in a dynamic adjustment plan. The detection scheme is obtained by fusing the dynamic adjustment scheme with the baseline parameters.

[0007] Preferably, the initial static analysis based on a parametric measuring point layout system, according to the project type, cross-sectional shape, cross-sectional dimensions, and surrounding rock grade, includes: Based on the project type, cross-sectional shape and cross-sectional dimensions, cross-sectional identification and analysis are performed, and the initial number of boreholes is calculated according to the cross-sectional identification results. Based on the surrounding rock grade and cross-sectional dimensions, and according to the elastoplastic theory and surrounding rock strength criteria, through... The drilling depth was obtained through analysis and calculation, where, This is the initial drilling depth. , This is an empirical coefficient. To correct the constant, For the tunnel span, These are the basic quality indicators for the surrounding rock.

[0008] Preferably, when calculating the initial number of boreholes based on the cross-section identification results, different initial borehole number calculation formulas are used for different types of cross-sections for analysis and calculation. The types of cross-sections include: single-hole single-line cross-section, single-hole multi-line large cross-section, and double single-hole single-line parallel cross-section.

[0009] Preferably, a dynamic response mechanism is adopted to dynamically adjust based on real-time data information during the implementation of the target project, including: Construction monitoring is conducted based on the benchmark scheme, and geological forecast data and construction monitoring data during the construction process are acquired through advanced geological forecasting systems and sensor networks. Based on the analysis of geological forecast data, it is determined whether there is a geological anomaly. If there is a geological anomaly, geological parameter analysis is performed on the geological forecast data. Based on the results of the geological parameter analysis, the adjustment amount of the number of boreholes and the borehole depth for the next excavation cycle is calculated to obtain the first dynamic analysis result. Based on the analysis of construction monitoring data, it is determined whether the disturbance exceeds the limit. If the disturbance exceeds the limit, the disturbance parameter analysis is performed on the construction monitoring data, and the adjustment amount of the number of measuring holes is calculated based on the disturbance parameter analysis results to obtain the second dynamic analysis result. A dynamic adjustment scheme is obtained by combining the results of the first and second dynamic analyses.

[0010] Preferably, when monitoring and collecting data in the test hole using the acoustic wave testing system, a step-by-step method is used to collect data at the test point in the test hole. At each test point, data is collected according to a preset interval between groups to obtain a data set of the test point. The data set of the test point is then verified. When the data verification is successful, the next test point is collected.

[0011] Preferably, preliminary analysis and calculation are performed based on the acoustic wave acquisition data, including: The acoustic wave acquisition data is processed to determine the acquisition depth data and acoustic wave acquisition data. The time-difference method was used to calculate the sound wave velocity at each measuring point based on the sound wave acquisition data. The wave velocity data is filtered, and the acquired depth data is calibrated. Curve fitting was performed on the filtered wave velocity data and the depth data after depth calibration to obtain the wave velocity-depth relationship curve.

[0012] Preferably, a dynamic judgment model is used to analyze and determine the boundary of the crack damage range based on the wave velocity-depth relationship curve, including: Quantitative parameter analysis is performed based on the wave velocity-depth relationship curve, where the quantitative parameters include: wave velocity gradient, wave velocity variation coefficient, and relative wave velocity increase. Based on the surrounding rock grade, the corresponding judgment method is used to analyze and determine the quantitative parameters to identify the boundary of the loosened zone. By comprehensively comparing and verifying the boundary of the loosened zone with the corresponding depth data, the final boundary of the crack range is determined.

[0013] Preferably, the support design for the cracked area is based on the cracked area boundary, including: The extent and thickness of the crack are determined based on the boundary of the crack area. Based on the thickness of the cracked area Determine the length of the anchor bolt ,in, To measure the thickness of the loose ring, The length of the anchorage section. For safety reserve length; Based on the thickness of the cracked area and the influence coefficient of the surrounding rock level, the following will be used... Determine the thickness of the spray layer ,in, To measure the thickness of the loose ring, The influence coefficient of the surrounding rock grade; Based on the fracture range and thickness combined with the surrounding rock grade adjustment coefficient, Determine the spacing of the steel arch frames , Basic spacing, This is the adjustment coefficient for the surrounding rock grade. To measure the thickness of the loose ring; The type of support is determined based on the thickness of the cracked area.

[0014] Preferably, when verifying the support effect and optimizing and updating the dynamic judgment model through backtracking analysis, a monitoring system is deployed on the support structure after the support structure is implemented according to the support design. The monitoring system identifies anomalies according to the monitoring cycle and frequency, and issues multi-level early warnings based on the anomaly identification results. At the same time, the dynamic judgment model is optimized and updated through backtracking analysis based on the multi-level early warning situation. When a level 2 or higher early warning is triggered, the abnormal section is identified, the cause of the abnormal section is analyzed, and the dynamic judgment model is optimized and adjusted based on the cause of the abnormal section.

[0015] The present invention has achieved the following beneficial effects: This invention analyzes geological conditions and conducts dynamic detection analysis for the target project, enabling the deployment of measuring points based on the actual conditions of the project. This improves the adaptability of the method for assessing the extent of rock fracture, allowing for more comprehensive and accurate support, ensuring the construction safety of the target project. Furthermore, the use of an acoustic testing system can promptly capture changes in underground engineering, avoiding the failure of static detection methods in dynamic environments. This effectively addresses the dynamic uncertainties of underground engineering, avoids detection blind spots, and improves the targeting and coverage of detection. The dynamic judgment model used to analyze and determine the boundary of the fracture extent overcomes the limitations of traditional methods, which rely on single judgment standards and are difficult to adapt to different geological conditions. The judgment standard can be dynamically adjusted according to the actual rock mass wave velocity distribution, improving the accuracy and consistency of judgment results under different geological conditions. In addition, by designing support for the fracture extent, the boundary of the fracture extent is directly and quantitatively linked to the support design, providing precise data support for the design of support parameters. This enables on-demand support, avoiding the risks of insufficient support and preventing waste caused by over-support, thus improving the scientific, targeted, and economical nature of support design. Meanwhile, by verifying the support effect and optimizing and updating the dynamic judgment model through backtracking analysis, the assessment of the range of cracks in the surrounding rock of the project has achieved a closed loop of detection, design, verification and optimization. This not only ensures the reliability of the support effect, but also enables the dynamic judgment model to be continuously optimized according to the actual engineering situation, thereby improving the accuracy and adaptability of the assessment method for the range of cracks in the surrounding rock of the project.

[0016] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the application.

[0017] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0018] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings: Figure 1 This is a schematic diagram illustrating the steps of the method for evaluating the extent of cracks in the surrounding rock of an engineering project as described in this invention. Figure 2 This is a flowchart illustrating step one of the engineering surrounding rock fracture range assessment methods described in this invention. Figure 3 This is a specific example diagram of a single-hole single-line cross-section in the engineering surrounding rock fracture range assessment method described in this invention; Figure 4This is an example diagram of a single-hole multi-line large cross-section in the engineering surrounding rock fracture range assessment method described in this invention; Figure 5 This is an example diagram of the parallel cross-section of two single-hole single-line in the engineering surrounding rock fracture range assessment method described in this invention; Figure 6 This is an example diagram of the wave velocity-depth relationship curve in the engineering surrounding rock fracture range assessment method described in this invention. Detailed Implementation

[0019] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0020] like Figure 1 As shown, this embodiment of the invention provides a method for evaluating the extent of crack damage in engineering surrounding rock based on dynamic response, including: Step 1: Conduct geological condition analysis and dynamic detection analysis for the target project to determine the detection plan.

[0021] In this step, the target project can be a subway tunnel, a highway tunnel, or other tunnel construction projects.

[0022] Step 2: Deploy the acoustic wave testing system according to the detection plan.

[0023] In this step, the acoustic testing system includes: a single-transmitter, dual-receiver acoustic probe, a high-pressure water injection system, an airbag pressurization system, and a signal acquisition unit. The single-transmitter, dual-receiver acoustic probe has a transmission frequency of 50kHz and a receiver spacing of 200mm. The high-pressure water injection system has a maximum operating pressure of 1.0MPa and an adjustable flow rate of 0-10L / min. The airbag pressurization system has an operating pressure range of 0-0.5MPa and an accuracy of ±0.02MPa. The signal acquisition unit has a sampling frequency of 1MHz and a 16-bit AD conversion accuracy.

[0024] The deployment of the acoustic testing system according to the detection plan includes: determining the test holes and installing and coupling the acoustic testing system through drilling; during the drilling process, constructing test holes according to the hole positions, depths, and angles specified in the detection plan; and using a combination of high-pressure air and water to clean the holes. The hole diameter is controlled within [specific parameters]. Diamond drill bits are used to ensure smooth hole walls. When using a combination of high-pressure air and water to clean the drill hole, high-pressure air (pressure) is used. ) and water (pressure) Jointly clean the borehole for at least 5 minutes to ensure the borehole wall is clean and free of rock powder accumulation. After drilling, conduct a quality inspection of the borehole. Use a borehole depth gauge to measure the depth, with an error not exceeding ±5cm; use a borehole wall inspection instrument to check the integrity of the borehole wall, ensuring no collapse or diameter reduction. During the installation and coupling of the acoustic wave testing system, pre-process the dual-receiver acoustic probe, check the integrity of all probe components, and measure the insulation resistance of the transmitting / receiving transducers, requiring a resistance greater than [value missing]. The dual-receiver acoustic probe is slowly inserted into the bottom of the hole using a fiberglass pusher rod with depth markings, with the pushing speed controlled at [speed not specified]. Once the dual-receiver acoustic probe reaches the bottom of the measuring hole, the high-pressure water injection system is activated to inject clean water into the measuring hole as a coupling agent, with an initial pressure of... Slowly rising to work pressure The water injection process continues for 3-5 minutes until a steady flow of clear water overflows from the orifice. Record the total water volume injected and calculate the water replacement rate within the orifice, which must be greater than 95%. Then, inflate the dual-receiver acoustic probe's airbag using the airbag pressurization system. Each pressure holding period lasts 1 minute, ultimately maintaining the working pressure at [value missing]. The pressure holding time is no less than 5 minutes, and the airbag pressure fluctuation is monitored in real time to ensure coupling stability, so that the dual acoustic wave probes fit tightly against the hole wall of the measuring hole.

[0025] Step 3: Use the acoustic wave testing system to monitor and collect data in the test hole to obtain acoustic wave acquisition data.

[0026] In this step, when monitoring and collecting data in the test hole using the acoustic wave testing system, the acoustic wave test is performed point by point towards the hole opening, starting from the bottom of the hole and proceeding at fixed step intervals of 20 cm. At each test point, the acoustic wave transmitter generates a frequency of... Pulse width The ultrasonic pulses are emitted at a voltage of 500V. The receiver uses dual-channel synchronous acquisition, with a sampling frequency set to... Record the arrival time of the first wave.

[0027] Step 4: Perform preliminary analysis and calculation based on the acoustic wave acquisition data to determine the wave velocity-depth relationship curve.

[0028] In this step, the preliminary analysis and calculation usually refers to the calculation of the sound wave velocity. The wave velocity-depth relationship curve is the basic basis for determining the boundary of the loosened zone, and its typical morphology is characterized by a three-segment feature: Section I (loosening zone): The shallow area near the borehole (tunnel face) has relatively low wave velocity values ​​and large fluctuations, reflecting the rock mass state affected by excavation disturbance and the development of fissures; Section II (Transition Zone): As the depth increases, the wave velocity shows a significant upward trend, reflecting the transition of the rock mass from a disturbed state to a pristine state. Section III (Original Rock Zone): In deeper areas, the wave velocity reaches a higher value and tends to stabilize, with a small fluctuation range, representing intact original rock that has not been significantly affected by excavation.

[0029] Step 5: Based on the wave velocity-depth relationship curve, use a dynamic judgment model to analyze and determine the boundary of the crack damage range.

[0030] In this step, the dynamic judgment model analyzes and judges based on the real-time changes of the wave velocity-depth relationship curve. The wave velocity-depth relationship curve is used as the input of the dynamic judgment model. The loosened area is identified through identification and analysis, and the boundary of the crack range is obtained based on the range of the loosened area. The boundary of the crack range is then output as the result of the dynamic judgment model.

[0031] Step 6: Design support for the damaged area based on the boundary of the damaged area.

[0032] This step involves support design, which includes: anchor bolt length, steel arch spacing, and support type.

[0033] Step 7: Verify the support effect and optimize and update the dynamic judgment model through backtracking analysis.

[0034] In this step, the support structure is implemented according to the support design after the support design is completed, and the support effect of the support structure is verified after the support structure is completed.

[0035] The aforementioned technical solution enables dynamic response assessment of the fracture range of the surrounding rock in engineering projects. Measuring points are strategically placed according to the actual conditions of the project, improving the flexibility of the detection scheme and allowing for more comprehensive and accurate detection and support, thus providing a more reliable safety guarantee for project implementation. Through geological condition analysis and dynamic detection analysis of the target project, measuring points are strategically placed based on the actual conditions of the project, enhancing the adaptability of the surrounding rock fracture range assessment method. This allows for more comprehensive and accurate support, ensuring the construction safety of the target project. Furthermore, the use of an acoustic testing system can promptly capture changes in underground engineering, avoiding the failure of static detection methods in dynamic environments. This effectively addresses the dynamic uncertainties of underground engineering, avoids detection blind spots, and improves the targeting and coverage of detection. Moreover, the use of a dynamic judgment model to analyze and determine the fracture range boundary overcomes the limitations of traditional methods, which rely on single judgment standards and are difficult to adapt to different geological conditions. This allows the judgment standards to be dynamically adjusted according to the actual rock mass wave velocity distribution, improving the accuracy and consistency of the judgment results under different geological conditions. Furthermore, by designing support for the fractured area, the boundary of the fractured area is directly and quantitatively linked to the support design. This provides precise data support for the design of support parameters, enabling on-demand support. This avoids the risks of insufficient support and prevents waste caused by over-support, improving the scientific rigor, relevance, and economy of the support design. Simultaneously, by verifying the support effect and optimizing the dynamic judgment model through backtracking analysis, a closed loop of detection, design, verification, and optimization is achieved in the assessment of fractured areas in engineering surrounding rock. This not only ensures the reliability of the support effect but also allows the dynamic judgment model to be continuously optimized based on actual engineering conditions, improving the accuracy and adaptability of the method for assessing fractured areas in engineering surrounding rock.

[0036] In one embodiment provided by the present invention, such as Figure 2 As shown, geological condition analysis and dynamic detection analysis are conducted for the target project, including: To obtain engineering design data and geological survey reports for the target project, and to determine the project type, cross-sectional shape, cross-sectional dimensions and surrounding rock grade.

[0037] Specifically, when obtaining engineering design data and geological survey reports for a target project, these can be directly retrieved from the engineering management system.

[0038] Based on the project type, cross-sectional shape, cross-sectional dimensions, and surrounding rock grade, an initial static analysis is conducted using a parametric measuring point layout system to calculate benchmark parameters and determine the benchmark scheme. Benchmark parameters include the number of measuring holes and the drilling depth.

[0039] The initial static analysis based on a parametric measuring point layout system, according to the project type, cross-sectional shape, cross-sectional dimensions, and surrounding rock grade, includes: Cross-section identification and analysis are performed based on the project type, cross-section shape, and cross-section dimensions. The initial number of boreholes is then calculated based on the cross-section identification results.

[0040] When performing cross-section identification analysis based on project type, cross-section shape, and cross-section size, cross-section features are identified, and the type of cross-section is determined based on these features.

[0041] In this step, when calculating the initial number of boreholes based on the cross-section identification results, different initial borehole number calculation formulas are used for different types of cross-sections for analysis and calculation. The types of cross-sections include: single-hole single-line cross-section, single-hole multi-line large cross-section, and double single-hole single-line parallel cross-section.

[0042] Furthermore, such as Figure 3 As shown, single-tunnel single-line cross-sections include: shield tunnel circular cross-sections, cut-and-cover horseshoe-shaped cross-sections, and cut-and-cover arch-top straight-wall cross-sections. During the initial borehole number analysis and calculation for single-tunnel single-line cross-sections, further identification and analysis are performed. When the target project is a shield tunnel circular cross-section within a single-tunnel single-line cross-section, through... The number of test holes was calculated, among which, This represents the initial number of boreholes. It is a rounding function. The diameter of the opening. This is a correction factor for the construction method; here, Based on the stress distribution theory of circular tunnels, arranging 0.5 measuring holes per meter of diameter ensures that the circumferential monitoring density meets basic requirements. Rounding up ensures the number of boreholes is an integer and provides appropriate monitoring redundancy. Construction method correction factor. This is derived by considering the differences in the degree of disturbance to the surrounding rock caused by different construction methods. For example, when using the shield tunneling method, the disturbance to the surrounding rock is relatively small, and the construction method correction factor is usually taken as 1. When the target project is a horseshoe-shaped cross-section in a single-tunnel, single-line section, it is obtained through... The number of test holes was calculated, among which, This represents the initial number of boreholes. It is a rounding function. For the tunnel span, Here, the cross-sectional shape correction factor is... Based on the cross-sectional shape, a horseshoe-shaped cross-section causes significant disturbance to the surrounding rock during blasting excavation, requiring increased monitoring density. The construction method correction factor is typically set to 2. When the target project is a single-tunnel, single-line cross-section with a cut-and-cover arched straight wall, [the following is used]... The number of test holes was calculated, among which, This represents the initial number of boreholes. It is a rounding function. The length of the arch is the arc length of the vault. The height of the straight wall. Here, the correction factor for the arch foot area is... This refers to the number of measuring holes at the top of the arch. This refers to the number of boreholes in the straight wall and the correction factor for the arch foot area. This is because stress concentration at the arch foot should be addressed by denser spacing, typically with a value ranging from 1 to 2.

[0043] like Figure 4 As shown, when the target project is a single-tunnel, multi-line, large-section project, through... The number of test holes was calculated, among which, This represents the initial number of boreholes. It is a rounding function. For the tunnel span, This refers to the large cross-sectional shape correction factor; here, the large cross-sectional shape correction factor... The value is determined based on the cross-sectional shape and is usually in the range of 2-3.

[0044] like Figure 5 As shown, when the target project is a parallel cross-section of two single-tunnel tunnels and one track, through... The number of test holes was calculated, among which, This represents the initial number of boreholes. It is a rounding function. The diameter of the left-side opening. The diameter of the opening on the right side. This is the construction method correction factor for the left-side opening. This is the construction method correction coefficient for the right-side opening; here, the number of measuring holes on the middle rock wall is determined according to the width of the rock wall and the surrounding rock grade, usually 2 to 3.

[0045] Based on the surrounding rock grade and cross-sectional dimensions, and according to the elastoplastic theory and surrounding rock strength criteria, through... The drilling depth was obtained through analysis and calculation, where, This is the initial drilling depth. , This is an empirical coefficient. To correct the constant, For the tunnel span, These are the basic quality indicators of the surrounding rock. Here, the basic quality indicators of the surrounding rock are... and tunnel span The [BQ] value is adopted from the "Engineering Rock Mass Classification Standard" (GB / T 50218); This reflects the impact of tunnel span on the extent of the loosening zone; the larger the span, the deeper the potential loosening zone. This reflects the controlling effect of surrounding rock quality on the development of the loosened zone; the better the surrounding rock quality, the smaller the loosened area. (Correction constant) This is a safety margin, which is adjusted appropriately according to engineering conditions. Under normal circumstances, it is taken as 0.5m. If it is an important project or a project with complex geological conditions, it is taken as 0.6m. If it is an underwater tunnel or a project with special risks, it is taken as 0.8m, thereby ensuring the reliability of the detection.

[0046] Furthermore, the empirical coefficient , The empirical coefficients are determined based on burial depth, geostress conditions, rock mass integrity, and the degree of development of structural planes. The value ranges from 0.04 to 0.06, and should be adjusted appropriately according to the burial depth and ground stress conditions. For example, in shallow tunnels (tunnels where the ratio of vertical wall height to tunnel span is less than 2), A value of 0.04 is used for medium-deep buried tunnels (tunnels where the ratio of vertical wall height to tunnel span is greater than or equal to 2 and less than or equal to 4). The value is 0.05; for deeply buried tunnels (tunnels where the ratio of vertical wall height to tunnel span is greater than 4), The value is 0.06. (Empirical coefficient) The value ranges from 0.006 to 0.01, and should be adjusted appropriately based on the integrity of the rock mass and the degree of development of structural planes. For example, for intact rock masses with a rock quality index greater than 75%, A value of 0.006 indicates a relatively intact rock mass with a rock quality index greater than 50% and less than or equal to 75%. A value of 0.008 indicates a fractured rock mass with a rock quality index not exceeding 50%. The value is 0.01.

[0047] A dynamic response mechanism is adopted to make dynamic adjustments based on real-time data information during the implementation of the target project, resulting in a dynamic adjustment plan.

[0048] Among them, a dynamic response mechanism is adopted to dynamically adjust based on real-time data information during the implementation of the target project, including: Construction monitoring is conducted based on a benchmark scheme, and geological forecasting data and construction monitoring data are acquired during the construction process through an advanced geological forecasting system and sensor network.

[0049] In this step, construction monitoring based on the benchmark scheme involves performing geological and construction monitoring on the target project's construction process using the number of boreholes specified in the benchmark scheme, thereby obtaining geological prediction data and construction monitoring data. The geological prediction data is retrieved from an advanced geological prediction system through real-time linkage with such systems. Examples of advanced geological prediction systems include TSP (Thunderbolt Spinning Point) and ground-penetrating radar.

[0050] Based on the analysis of geological forecast data, it is determined whether there is a geological anomaly. If there is a geological anomaly, geological parameter analysis is performed on the geological forecast data. Based on the results of the geological parameter analysis, the adjustment amount of the number of boreholes and the borehole depth for the next excavation cycle is calculated to obtain the first dynamic analysis result.

[0051] In this step, when analyzing geological forecast data to determine whether there is a geological anomaly, the data packet of geological forecast data transmitted by the advanced geological forecast system is acquired, the data packet is parsed, and key geological parameters are extracted from the parsed data. Based on these key geological parameters, the geological anomaly is determined. These key geological parameters include: joint density within a specific distance in front of the tunnel face, rock integrity index, estimated water content, and the surrounding rock lateral pressure coefficient λ, etc. To determine whether there is a geological anomaly, the analysis shows whether the joint density within a specific distance in front of the tunnel face has increased dramatically. When a dramatic increase occurs, for example, a growth rate greater than 60%, a geological anomaly is indicated. In this case, the adjustment amount for the number of boreholes is 2. Meanwhile, the drilling depth is adjusted by increasing it by 15%, that is: The analysis checks whether the joint density within a specific distance in front of the tunnel face exceeds a first threshold. If the joint density within this distance exceeds the first threshold, or if a water-rich signal is detected based on the estimated water content, the number of boreholes is adjusted to 3. Meanwhile, the drilling depth is adjusted by an increase of 20%, that is: ,in, This is the adjustment amount for the drilling depth. The initial drilling depth is defined here. The first threshold is the analytical judgment boundary value for joint density within a specific distance in front of the tunnel face, for example: 20 joints / m. Analyzing the relationship between the surrounding rock lateral pressure coefficient and the second threshold, when the surrounding rock lateral pressure coefficient is less than the second threshold, based on the secondary stress field theory, tensile stress zones are prone to appear at the arch crown and arch bottom. Measuring points should be added to the baseline of measuring point arrangement in these areas. In this case, the adjustment amount for the number of measuring holes is an increase of 40%, i.e.: ,in, This is an adjustment amount for the number of measuring holes. For the initial number of boreholes, when the lateral pressure coefficient of the surrounding rock exceeds the second threshold, the maximum tangential compressive stress and the plastic zone are significantly concentrated in the sidewall. Therefore, the borehole depth should be increased from the baseline borehole depth in the sidewall region. In this case, the adjustment amount for the borehole depth is an increase of 20%, i.e.: ,in, This is the adjustment amount for the drilling depth. The initial borehole depth is defined here. The second threshold refers to the analytical judgment threshold of the surrounding rock lateral pressure coefficient, for example, 1 / 3. When geological anomalies occur, the adjustment amounts for the number of boreholes and the borehole depth are determined. The first dynamic analysis result is the adjustment amounts for the number of boreholes and the borehole depth. When geological anomalies occur, there are no adjustment amounts for the number of boreholes and the borehole depth. The first dynamic analysis result is that no adjustment of the number of boreholes and the borehole depth is needed. Therefore, in the next excavation cycle, the adjustment amounts for the number of boreholes and the borehole depth are combined to optimize construction monitoring.

[0052] Based on the analysis of construction monitoring data, it is determined whether the disturbance exceeds the limit. If the disturbance exceeds the limit, the disturbance parameter analysis is performed on the construction monitoring data, and the adjustment amount of the number of measuring holes is calculated based on the disturbance parameter analysis results to obtain the second dynamic analysis result.

[0053] In this step, when analyzing construction monitoring data to determine whether the disturbance exceeds the limit, the intensity of the construction disturbance is analyzed based on the construction monitoring data, key disturbance parameters are extracted, and it is determined whether the disturbance is within the expected range based on the key disturbance parameters. If not, the benchmark coefficient is dynamically adjusted. For example, in the blasting excavation section, when the measured vibration velocity is greater than... At that time, the construction method correction factor is dynamically adjusted upwards, increasing the construction method correction factor. Therefore, the adjustment amount for the number of measuring holes is determined as follows: ,in, This is a correction factor for the construction method. The adjustment amount is between 0 and 1, for example, 0.25. Key disturbance parameters include, for example, peak blasting vibration velocity (PPV). When the disturbance exceeds the limit, a supplementary measurement mechanism for the current section is triggered to determine the adjustment amount for the number of boreholes. This allows for optimization of construction monitoring during subsequent monitoring sessions, based on the adjusted number of boreholes. The second dynamic analysis result at this point is the adjustment amount for the number of boreholes. When the disturbance does not exceed the limit, the second dynamic analysis result indicates that no adjustment to the number of boreholes or the borehole depth is required.

[0054] A dynamic adjustment scheme is obtained by combining the results of the first and second dynamic analyses.

[0055] In this step, when combining the results of the first and second dynamic analyses, if both the first and second dynamic analyses indicate that no adjustment to the number of boreholes or drilling depth is needed, then the dynamic adjustment scheme is to eliminate the need for adjustment to the number of boreholes or drilling depth. , If the first dynamic analysis result is an adjustment to the number of boreholes and the drilling depth, and the second dynamic analysis result is that no adjustment to the number of boreholes and the drilling depth is required, the dynamic adjustment scheme is the adjustment to the number of boreholes and the drilling depth from the first dynamic analysis result. If the first dynamic analysis result is that no adjustment to the number of boreholes and the drilling depth is required, and the second dynamic analysis result is an adjustment to the number of boreholes, the dynamic adjustment scheme is the adjustment to the number of boreholes from the second dynamic analysis result. If the first dynamic analysis result is an adjustment to the number of boreholes and the drilling depth, and the second dynamic analysis result is an adjustment to the number of boreholes, the dynamic adjustment scheme is the sum of the adjustment to the number of boreholes from the first dynamic analysis result and the adjustment to the number of boreholes from the second dynamic analysis result, plus the adjustment to the drilling depth from the first dynamic analysis result.

[0056] The detection scheme is obtained by fusing the dynamic adjustment scheme with the baseline parameters.

[0057] In this process, when fusing the dynamic adjustment scheme with the benchmark parameters to obtain the detection scheme, the number of boreholes and the borehole depth obtained from the initial static analysis are fused with the corresponding adjustment amounts. Obtain the final number of test holes. ,in, This represents the initial number of test holes. The adjustment amount for the number of measuring holes is obtained by... To the final drilling depth , This is the initial drilling depth. The adjustment amount is used to determine the borehole depth, and then a detection scheme is obtained based on the final number of boreholes and the final borehole depth.

[0058] The aforementioned technical solution enables dynamic analysis of the detection scheme, allowing for dynamic adjustments based on the actual conditions of the target project. This enhances the flexibility of the detection scheme, enabling more comprehensive and accurate monitoring regardless of the engineering scenario, thus providing a guarantee for the assessment of the extent of rock fissures in the project's surrounding rock. Employing a dynamic response mechanism based on real-time data improves flexibility and adaptability, allowing for timely detection of anomalies during construction and prompt adjustments to the detection scheme based on the construction progress. This avoids delays in the assessment of the extent of fissures and ensures that the assessment results accurately reflect the actual situation of rock fissures in the project's surrounding rock. Furthermore, different analysis and calculations for different cross-sectional types adapt to various situations, enabling accurate analysis and calculations for different cross-sectional types. This improves the versatility of the method for assessing the extent of rock fissures in the project's surrounding rock and ensures the accuracy of the analysis and calculation of the number of boreholes and borehole depth.

[0059] In one embodiment of the present invention, when monitoring and collecting data in a test hole using an acoustic testing system, a step-by-step method is used to collect data at test points in the test hole. At each test point, data is collected according to a preset interval between groups to obtain a test point data set. The test point data set is then verified. If the data verification is successful, the next test point is collected.

[0060] When using a step-by-step method to collect data at measurement points in the borehole, acoustic wave tests are performed point by point towards the borehole opening at a fixed step distance. Data is collected at each measurement point according to a preset interval, for example, a fixed step distance of 20cm and a preset interval of 2s. When collecting data at one measurement point, a set of acoustic wave data is acquired every 2s. After acquiring at least 3 sets of valid acoustic wave data, the system moves 20cm at the fixed step distance to the next measurement point for data collection. The dwell time at each measurement point is no less than 30 seconds to ensure system stability.

[0061] After obtaining the data set at each measuring point, the data is immediately verified. If the data verification fails, it is re-collected in a timely manner to ensure that there are no missing measuring points, verify the accuracy of the depth marking, and the cumulative error does not exceed ±2cm.

[0062] When verifying the data set of the measurement point, the acoustic wave data is analyzed. The signal-to-noise ratio of the first acoustic wave data is determined, and the data dispersion of the acoustic wave data at the same measurement point is analyzed. If the signal-to-noise ratio of the first wave is lower than 20dB or the data dispersion of the acoustic wave data at the same measurement point is greater than 5%, the data verification fails, and acoustic wave acquisition is repeated for that measurement point.

[0063] The aforementioned technical solution employs a step-by-step approach to precisely control the acquisition position during borehole sampling, avoiding the positional ambiguity issues that may arise from traditional continuous sampling. This ensures that the data from each sampling point accurately reflects the acoustic characteristics at that location, while also preventing data omissions. This guarantees that data is collected from every key location within the borehole, providing more comprehensive data support for subsequent analysis. Furthermore, acquiring data at preset intervals not only improves data acquisition efficiency and captures changes in acoustic waves at different time points, allowing for timely detection of potential crack development, but also ensures data quality, reduces unnecessary data redundancy, and avoids collecting excessive duplicate data, thereby saving storage space and processing time. In addition, data verification ensures data quality, guaranteeing the accuracy and reliability of subsequent analysis data and preventing misjudgments due to erroneous data, thus improving the accuracy of the method for assessing the extent of cracks in the surrounding rock.

[0064] In one embodiment of the present invention, preliminary analysis and calculation based on acoustic wave acquisition data includes: The acoustic wave acquisition data is processed to determine the acquisition depth data and acoustic wave acquisition data.

[0065] In this step, when processing the acoustic wave acquisition data, the acoustic wave acquisition data is classified and sorted, invalid or redundant information is removed, and the data of each measurement point recorded by the acoustic wave acquisition system is sorted into two columns to provide a clear and accurate data foundation for subsequent analysis.

[0066] The time difference method is used to calculate the sound wave velocity at each measuring point based on the sound wave acquisition data.

[0067] In this step, when calculating the sound wave velocity at each measuring point using the time-difference method based on the sound wave acquisition data, by... Analysis and calculation yielded the measurement points sound wave speed ,in, The distance between the two receiving transducers. , These represent the arrival times of the first wave for the two receivers.

[0068] The wave velocity data is filtered, and the acquired depth data is calibrated.

[0069] In this step, when filtering the wave velocity data, a moving average filter is applied, for example, a 5-point moving average filter. A Hamming window is used as the window function to eliminate random errors. When calibrating the acquired depth data, the cumulative error of the depth markers is checked (it should not exceed ±2cm) to ensure the accuracy of the depth data.

[0070] Curve fitting was performed on the filtered wave velocity data and the depth data after depth calibration to obtain the wave velocity-depth relationship curve.

[0071] In this step, when performing curve fitting based on the filtered wave velocity data and the depth-calibrated acquisition depth data, wave velocity is used as the abscissa and depth as the ordinate. The filtered wave velocity data and the depth-calibrated acquisition depth data are treated as scatter points, and the scatter points are connected by straight lines or smooth curves to obtain the wave velocity-depth relationship curve. Then, the wave velocity-depth relationship curve chart is formatted, with axis labels and titles added, along with grid lines for easier data reading. Furthermore, the chart also performs a three-segment feature analysis and annotation based on morphology, resulting in... Figure 6The wave velocity-depth relationship curve shown is characterized by three segments: Segment I (loosened zone), which refers to the shallow area near the borehole opening (tunnel face), where the wave velocity value is relatively low and fluctuates greatly, reflecting the rock mass state affected by excavation and with developed fissures; Segment II (transition zone), where the wave velocity shows a significant upward trend with increasing depth, reflecting the transition of the rock mass from a disturbed state to a pristine state; and Segment III (pristine rock zone), where the wave velocity reaches a higher value and tends to stabilize at deeper depths, with a small fluctuation range, representing intact pristine rock that has not been significantly affected by excavation.

[0072] The aforementioned technical solution provides a clear and accurate data foundation for subsequent analysis through data processing, avoiding misjudgments caused by data chaos and ensuring the reliability of the analysis results. Furthermore, filtering the wave velocity data removes noise and outliers, reducing data fluctuations caused by measurement errors and environmental interference, resulting in smoother and more stable wave velocity data, thus improving data quality and usability. Simultaneously, depth calibration of the acquired depth data ensures its accuracy, correcting deviations caused by equipment errors and measurement methods in actual measurements. This makes the depth data more consistent with actual geological conditions, providing more accurate data support for subsequent curve fitting and analysis, improving the accuracy of the wave velocity-depth relationship curve, and thus more accurately reflecting the changing patterns of the surrounding rock fracture range. The time-of-flight method is used to calculate the sound wave velocity at each measuring point based on the acquired sound wave data. By accurately measuring the time difference of sound wave propagation in different media, the propagation speed of sound waves in the surrounding rock can be accurately calculated, effectively reflecting the physical properties and fracture state of the surrounding rock, providing key parameters for subsequent analysis. By performing curve fitting based on filtered wave velocity data and depth-calibrated acquisition depth data, discrete wave velocity and depth data are transformed into a continuous curve, which more intuitively shows the trend of wave velocity change with depth. This helps to identify typical characteristic areas of the fracture range and provides a strong basis for accurately determining the boundary of the fracture range.

[0073] In one embodiment of the present invention, a dynamic judgment model is used to analyze and determine the boundary of the crack damage range based on the wave velocity-depth relationship curve, including: Quantitative parameter analysis is performed based on the wave velocity-depth relationship curve, where the quantitative parameters include: wave velocity gradient, wave velocity coefficient of variation, and relative increase in wave velocity.

[0074] In this step, when performing quantitative parameter analysis based on the wave velocity-depth relationship curve, the central difference method is used to calculate the wave velocity gradient. The wave velocity gradient at the measuring point was obtained through analysis and calculation, where, The wave velocity gradient at the measuring point, For fixed step size, For the first Depth of each measuring point For the first Wave velocity at each measuring point For the first Depth of each measuring point For the first The wave velocity at each measuring point was calculated using the sliding window method. The wave velocity variation coefficient at the measuring point is analyzed and calculated, where, For the first The wave velocity variation coefficient at the depth of each measuring point For the first Standard deviation of wave velocity within a 1m range before and after the depth of each measuring point For the first The average wave velocity within the depth range corresponding to each measuring point. (Through...) The relative increase in wave speed is calculated, where, For the first The increase in the average wave velocity at each measuring point relative to the range within 1 meter in front. For the first Wave velocity at each measuring point For the first The average wave velocity within a 1m range in front of each measuring point at its depth.

[0075] Based on the surrounding rock grade, the corresponding judgment method is used to analyze and determine the quantitative parameters to identify the boundary of the loosened zone.

[0076] In this step, different judgment criteria are used for different surrounding rock grades. When using quantitative parameter analysis based on the corresponding judgment method according to the surrounding rock grade, for grades I-III, the relative wave velocity increase threshold method is used. Specifically, the wave velocity-depth relationship curve is identified, a clearly rising segment is determined, and the relative wave velocity increase at each measuring point within that segment is calculated. When the relative wave velocity increase at two consecutive measuring points exceeds 25%, and the subsequent wave velocity remains stable or continues to increase, the depth of the first measuring point meeting the condition is determined as the boundary of the loosened zone. When the surrounding rock grade is IV, the wave velocity gradient extreme value method is used. Specifically, the wave velocity gradient value at each measuring point is calculated based on the wave velocity-depth relationship curve, and the peak value of the wave velocity gradient is identified. When the gradient value exceeds 300 m / s / m, the wave velocity stability after the peak value is verified. If the wave velocity variation coefficient of at least three subsequent measuring points is less than 0.15, the depth corresponding to the gradient peak value is determined as the boundary of the loosened zone. When the surrounding rock grade is V-VI, the wave velocity stability criterion is used for judgment. Specifically, the wave velocity variation coefficient of each measuring point is calculated based on the wave velocity-depth relationship curve. When the wave velocity variation coefficient drops from greater than 0.20 to less than 0.15 and remains stable, if this stable state is maintained within a depth range of at least 1m, the depth point where the wave velocity variation coefficient first drops below 0.15 is determined as the boundary of the loosened zone.

[0077] By comprehensively comparing and verifying the boundary of the loosened zone with the corresponding depth data, the final boundary of the crack range is determined.

[0078] In this step, when comprehensively analyzing the loosened zone boundary combined with depth data, the waveform quality at the determined depth is checked, requiring a clear first wave and a signal-to-noise ratio greater than 20dB. The rationality of the wave velocity value at this depth is verified, and it should match the mechanical properties of the surrounding rock. For important projects, a conservative principle is adopted; when different determination methods yield significantly different results, the larger value is taken as the final boundary depth. When verifying the loosened zone boundary combined with depth data, the depth of the crack range at each location is logically compared with the theoretical expectation based on the on-site lateral pressure coefficient λ. For example, if the determined crack range of the sidewall is much smaller than that of the arch when the λ value is large, this result contradicts the laws of mechanics. This result is marked and emphasized for verification when verifying the support effect.

[0079] The aforementioned technical solution employs quantitative analysis, incorporating parameters such as wave velocity gradient, wave velocity variation coefficient, and relative wave velocity increase to provide a detailed analysis of the wave velocity-depth relationship curve. This allows for a more comprehensive and accurate reflection of the characteristics of the surrounding rock fracture range. By using corresponding judgment methods based on the surrounding rock grade and analyzing these quantitative parameters, personalized analysis can be performed for different geological conditions and engineering characteristics. This ensures accurate determination of the fracture range boundary under various geological conditions, avoiding the inapplicability of a single judgment standard under different geological conditions and improving the accuracy and reliability of the judgment results. Furthermore, by comprehensively comparing and verifying the loosened zone boundary with corresponding depth data, the accuracy of the fracture range boundary can be further confirmed, ensuring that the determination of the fracture range boundary conforms to both the wave velocity variation law and the actual geological depth, thereby improving the reliability and consistency of the judgment results.

[0080] In one embodiment of the present invention, support design for the cracked area based on the cracked area boundary includes: The extent of the crack and its thickness are determined based on the boundary of the crack area.

[0081] Based on the thickness of the cracked area Determine the length of the anchor bolt ,in, To measure the thickness of the loose ring, The length of the anchorage section. For safety reserve length.

[0082] In this step, the length of the anchorage section Generally, a safety margin length of 2-3 meters is used. Generally, 0.5-1.0m is used.

[0083] Based on the thickness of the cracked area and the influence coefficient of the surrounding rock level, the following will be used... Determine the thickness of the spray layer ,in, To measure the thickness of the loose ring, This represents the influence coefficient of the surrounding rock grade.

[0084] In this step, the influence coefficient of the surrounding rock grade... The value is related to the surrounding rock grade, for grades I-III surrounding rock: =0.15; Class IV surrounding rock: = 0.18; Class V-VI surrounding rock: = 0.2, actual measured thickness of loose ring It is usually no more than 300mm.

[0085] Based on the fracture range and thickness combined with the surrounding rock grade adjustment coefficient, Determine the spacing of the steel arch frames , Basic spacing, This is the adjustment coefficient for the surrounding rock grade. This is the actual measured thickness of the loosened ring.

[0086] In this step, the base spacing The surrounding rock grade adjustment coefficient is determined based on the tunnel span. When the surrounding rock is of grade I-III, take When taking Class IV surrounding rock When taking V-VI grade surrounding rock, take .

[0087] The type of support is determined based on the thickness of the cracked area.

[0088] In this step, when determining the support type based on the thickness of the cracked area, the support type is determined according to the following thickness-support type comparison table: The above technical solutions ensure that the anchor bolts are effectively anchored in stable rock mass by determining the bolt length, and further improve the safety of the support by using a safety reserve length. Determining the shotcrete thickness allows for adjustment of the shotcrete thickness according to different surrounding rock conditions, ensuring that the shotcrete effectively covers the cracked area and prevents further deterioration of the surrounding rock. Determining the steel arch spacing allows for dynamic adjustment of the steel arch spacing according to the stability of the surrounding rock, ensuring the overall stability of the support structure and avoiding instability caused by excessive spacing. Determining the support type ensures that the support measures meet safety requirements without excessively wasting resources, minimizing economic costs while ensuring safety.

[0089] In one embodiment of the present invention, when verifying the support effect and optimizing and updating the dynamic judgment model through backtracking analysis, a monitoring system is deployed on the support structure after the support structure is implemented according to the support design. The monitoring system identifies anomalies according to the monitoring cycle and frequency, and issues multi-level warnings based on the anomaly identification results. At the same time, the dynamic judgment model is optimized and updated through backtracking analysis based on the multi-level warnings. When a level 2 or higher warning is triggered, the abnormal section is identified, the cause of the abnormal section is analyzed, and the dynamic judgment model is optimized and adjusted based on the cause of the abnormal section.

[0090] The monitoring system includes, but is not limited to: convergence monitoring points around the tunnel (using convergence meters or total stations for automatic monitoring), deep displacement inclinometers, anchor bolt axial force gauges, concrete strain gauges, and contact pressure cells. The monitoring cycle and frequency are dynamic; for example, the initial monitoring frequency is higher (e.g., 1-2 times per day), gradually decreasing as the surrounding rock deformation stabilizes (e.g., once per week) until the deformation is completely stable. Multi-level early warnings are categorized into Level 1, Level 2, and Level 3 warnings based on the level of alert. Level 1 warnings require close monitoring, Level 2 warnings require vigilance, and Level 3 warnings require immediate action. When the monitoring system identifies anomalies according to the monitoring cycle and frequency, and issues multi-level early warnings based on the anomaly identification results, the system acquires monitoring data and compares it with early warning thresholds. A Level 1 early warning is triggered when the measured displacement rate consistently exceeds the theoretical value, or the cumulative displacement reaches 80% of the predicted value. A Level 2 early warning is triggered when the cumulative displacement exceeds 110% of the predicted value, or the displacement rate fails to converge for an extended period (e.g., no significant attenuation for 7 consecutive days). A Level 3 early warning is triggered when the cumulative displacement exceeds 130% of the predicted value, or obvious signs of damage such as cracking of the support structure or yielding of anchor bolts appear. Simultaneously, the monitoring data is automatically entered into a central database. Once a Level II or higher warning is triggered, the affected section is marked as "abnormal support response," the abnormal section is identified, and model optimization feedback is immediately initiated. The dynamic judgment model is optimized and updated through backtracking analysis. A causal analysis is performed on the abnormal section, retrieving all original data, including: original acoustic waveforms, wave velocity-depth relationship curves, borehole camera images, ground-penetrating radar profiles, and the entire judgment process record (such as extreme points of wave velocity gradients, points of variation coefficient changes, etc.). Based on the original data, hypotheses are made to propose possible causes for the anomaly, including: the actual damage area is greater than the detected judgment value. When the anchor bolt anchorage section is insufficient or the support strength is inadequate, the extent of crack damage is underestimated; when the actual mechanical parameters of the surrounding rock (such as internal friction angle and cohesion) are worse than the values ​​in the survey report, resulting in greater deformation under the same support, the rock mass parameters are misjudged; there are unforeseen external disturbances, such as the influence of nearby construction or dynamic changes in groundwater. When optimizing and adjusting the dynamic judgment model based on the causes of abnormal sections, the associated steps in the dynamic judgment model are determined according to the possible causes of the anomalies, and the parameters of the associated steps are optimized, so that the optimized parameters are applied to the subsequent dynamic judgment model analysis to determine the boundary of the crack damage range.

[0091] Furthermore, when verifying the support effect, verification holes were added next to the monitoring and control system. Verification was then conducted using borehole photography or comparative acoustic testing based on the verification holes and the measured holes. Consistency analysis and calculations were performed based on the verification data collected from the verification holes and measured holes. ; in, These are values ​​calculated for consistency analysis. For verification data acquisition based on verification holes, This is for verification data collected based on borehole measurements. Verification is successful when CI ≥ 0.85; if CI < 0.85, the cause needs to be analyzed and additional measurements performed.

[0092] The aforementioned technical solution utilizes a monitoring system to identify anomalies and provide multi-level early warnings according to monitoring cycles and frequencies. This enables real-time monitoring of the stability of the support structure and timely identification of abnormalities, ensuring the safety of the support structure during construction and operation. Furthermore, it can issue different levels of early warning signals based on the severity of the anomalies, allowing construction or management personnel to take timely and appropriate measures, improving the timeliness and effectiveness of risk response and avoiding misjudgments or neglect due to a single early warning signal. In addition, by optimizing and updating the dynamic judgment model through retrospective analysis, a continuously improving closed-loop system is formed. This allows the dynamic judgment model to more accurately reflect changes in actual geological conditions and the extent of cracking, improving the model's predictive ability and reliability. It also fundamentally solves the systemic bias problem that may exist in traditional methods due to the lack of feedback, greatly enhancing the safety margin and long-term reliability of the project, forming a complete "detection-design-construction-monitoring-feedback-optimization" technical closed loop.

[0093] Those skilled in the art should understand that the terms "first" and "second" in this invention merely refer to different application stages.

[0094] Other embodiments of this disclosure will readily occur to those skilled in the art upon consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not disclosed herein. The specification and examples are to be considered exemplary only, and the true scope and spirit of this disclosure are indicated by the following claims.

[0095] It should be understood that this disclosure is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this disclosure is limited only by the appended claims.

Claims

1. A method for evaluating the extent of crack damage in engineering surrounding rock based on dynamic response, characterized in that, include: Geological condition analysis and dynamic detection analysis were conducted for the target project to determine the detection plan; The acoustic wave testing system was deployed according to the detection plan; Acoustic wave data is acquired by monitoring and collecting data in the test hole using an acoustic wave testing system. Preliminary analysis and calculations were performed based on the acoustic wave acquisition data to determine the wave velocity-depth relationship curve; A dynamic judgment model is used to analyze and determine the boundary of the crack damage range based on the wave velocity-depth relationship curve. The support design for the cracked area is based on the boundary of the cracked area; The support effect was verified, and the dynamic judgment model was optimized and updated through backtracking analysis.

2. The method for evaluating the extent of crack damage in surrounding rock in engineering projects according to claim 1, characterized in that, Geological condition analysis and dynamic detection analysis were conducted for the target project, including: To obtain engineering design data and geological survey reports for the target project, and to determine the project type, cross-sectional shape, cross-sectional dimensions and surrounding rock grade; Based on the project type, cross-sectional shape, cross-sectional dimensions, and surrounding rock grade, an initial static analysis is conducted using a parametric measuring point layout system to calculate benchmark parameters and determine the benchmark scheme. The benchmark parameters include the number of measuring holes and the drilling depth. A dynamic response mechanism is adopted to dynamically adjust the project based on real-time data during the implementation process, resulting in a dynamic adjustment plan. The detection scheme is obtained by fusing the dynamic adjustment scheme with the baseline parameters.

3. The method for evaluating the extent of crack damage in surrounding rock in engineering projects according to claim 2, characterized in that, An initial static analysis based on a parametric measuring point layout system is conducted according to the project type, cross-sectional shape, cross-sectional dimensions, and surrounding rock grade, including: Based on the project type, cross-sectional shape and cross-sectional dimensions, cross-sectional identification and analysis are performed, and the initial number of boreholes is calculated according to the cross-sectional identification results. Based on the surrounding rock grade and cross-sectional dimensions, and according to the elastoplastic theory and surrounding rock strength criteria, through... The drilling depth was obtained through analysis and calculation, where, This is the initial drilling depth. , This is an empirical coefficient. To correct the constant, For the tunnel span, These are the basic quality indicators for the surrounding rock.

4. The method for evaluating the extent of crack damage in surrounding rock in engineering projects according to claim 3, characterized in that, When calculating the initial number of boreholes based on the cross-section identification results, different initial borehole number calculation formulas are used for different types of cross-sections. The types of cross-sections include: single-hole single-line cross-section, single-hole multi-line large cross-section, and double single-hole single-line parallel cross-section.

5. The method for evaluating the extent of crack damage in surrounding rock in engineering projects according to claim 2, characterized in that, A dynamic response mechanism is adopted to make dynamic adjustments based on real-time data information during the implementation of the target project, including: Construction monitoring is conducted based on the benchmark scheme, and geological forecast data and construction monitoring data during the construction process are acquired through advanced geological forecasting systems and sensor networks. Based on the analysis of geological forecast data, it is determined whether there is a geological anomaly. If there is a geological anomaly, geological parameter analysis is performed on the geological forecast data. Based on the results of the geological parameter analysis, the adjustment amount of the number of boreholes and the borehole depth for the next excavation cycle is calculated to obtain the first dynamic analysis result. Based on the analysis of construction monitoring data, it is determined whether the disturbance exceeds the limit. If the disturbance exceeds the limit, the disturbance parameter analysis is performed on the construction monitoring data, and the adjustment amount of the number of measuring holes is calculated based on the disturbance parameter analysis results to obtain the second dynamic analysis result. A dynamic adjustment scheme is obtained by combining the results of the first and second dynamic analyses.

6. The method for evaluating the extent of crack damage in surrounding rock in engineering projects according to claim 1, characterized in that, When monitoring and collecting data in the test hole using the acoustic wave testing system, a step-by-step method is used to collect data at the test point. At each test point, data is collected according to a preset interval between groups to obtain a data set of the test point. The data set of the test point is then verified. If the data verification is successful, the next test point is then collected.

7. The method for evaluating the extent of crack damage in surrounding rock in engineering projects according to claim 6, characterized in that, Preliminary analysis and calculations are performed based on the acoustic wave acquisition data, including: The acoustic wave acquisition data is processed to determine the acquisition depth data and acoustic wave acquisition data. The time-difference method was used to calculate the sound wave velocity at each measuring point based on the sound wave acquisition data. The wave velocity data is filtered, and the acquired depth data is calibrated. Curve fitting was performed on the filtered wave velocity data and the depth data after depth calibration to obtain the wave velocity-depth relationship curve.

8. The method for evaluating the extent of crack damage in surrounding rock in engineering projects according to claim 1, characterized in that, A dynamic judgment model based on the wave velocity-depth relationship curve is used to analyze and determine the boundary of the crack damage range, including: Quantitative parameter analysis is performed based on the wave velocity-depth relationship curve, where the quantitative parameters include: wave velocity gradient, wave velocity variation coefficient, and relative wave velocity increase. Based on the surrounding rock grade, the corresponding judgment method is used to analyze and determine the quantitative parameters to identify the boundary of the loosened zone. By comprehensively comparing and verifying the boundary of the loosened zone with the corresponding depth data, the final boundary of the crack range is determined.

9. The method for evaluating the extent of crack damage in surrounding rock in engineering projects according to claim 1, characterized in that, The support design for the cracked area is based on the boundary of the cracked area, including: The extent and thickness of the crack are determined based on the boundary of the crack area. Based on the thickness of the cracked area Determine the length of the anchor bolt ,in, To measure the thickness of the loose ring, The length of the anchorage section. For safety reserve length; Based on the thickness of the cracked area and the influence coefficient of the surrounding rock level, the following will be used... Determine the thickness of the spray layer ,in, To measure the thickness of the loose ring, The influence coefficient of the surrounding rock grade; Based on the fracture range and thickness combined with the surrounding rock grade adjustment coefficient, Determine the spacing of the steel arch frames , Basic spacing, This is the adjustment coefficient for the surrounding rock grade. To measure the thickness of the loose ring; The type of support is determined based on the thickness of the cracked area.

10. The method for evaluating the extent of crack damage in surrounding rock in engineering projects according to claim 1, characterized in that, To verify the support effect and optimize and update the dynamic judgment model through backtracking analysis, a monitoring system is deployed on the support structure after the support structure is implemented according to the support design. The monitoring system identifies anomalies according to the monitoring cycle and frequency, and issues multi-level early warnings based on the anomaly identification results. At the same time, the dynamic judgment model is optimized and updated through backtracking analysis based on the multi-level early warning situation. When a level 2 or higher early warning is triggered, the abnormal section is identified, the cause of the abnormal section is analyzed, and the dynamic judgment model is optimized and adjusted based on the cause of the abnormal section.

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