A method for evaluating grouting quality of fractured rock mass surrounding rock

Abstract

The present application provides a kind of fissure rock mass surrounding rock grouting quality evaluation method, it is related to geotechnical engineering technical field, the present application includes the following steps: obtaining the permeability test data and acoustic velocity test data of the mechanical state of target surrounding rock area fissure connectivity before grouting, form the characterization parameter data set of fissure before grouting, three-dimensional point cloud data are calculated simultaneously collected to calculate the cavity volume of fissure;Electromagnetic field intensity data are collected to calculate the grouting filling rate in the process of grouting, resistivity time series data are collected to calculate cementation uniformity index, strain time series data are collected to calculate strain gradient, and grouting integrity index is formed by multi-feature fusion;After grouting, permeability and acoustic velocity data are calculated again to calculate the performance improvement rate of fissure characterization;Penetration test data are collected to calculate the strength parameters of stone body;Grouting integrity index, the performance improvement rate of fissure characterization and the strength parameters of stone body are carried out multiple fusion to calculate quality comprehensive score, and compared with preset threshold to carry out classification evaluation.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of geotechnical engineering, in particular to a fissured rock mass surrounding rock grouting quality evaluation method. BACKGROUND

[0002] With the continuous expansion of underground engineering construction scale, the stability problem of fissured rock mass surrounding rock is increasingly prominent. As an effective surrounding rock reinforcement method, grouting technology is widely used in tunnel, mine, water conservancy and other engineering fields. Grouting quality is directly related to the safety and long-term stability of the project. Therefore, it is very important to scientifically and accurately evaluate the grouting effect. At present, in order to meet the requirements of the project on the performance of slurry and adapt to various detection methods, especially in order to apply geophysical detection methods such as resistivity CT and electromagnetic wave, conductive agents such as graphite and nano carbon black are generally added in cement-based slurry to form conductive modified slurry. How to accurately evaluate the grouting quality of fissured rock mass surrounding rock is of great significance to ensure the safety of the project and optimize the grouting parameters.

[0003] At present, the fissured rock mass surrounding rock grouting quality evaluation method mainly includes drilling core method, geological radar detection method, acoustic wave test method and resistivity test method. The prior art with publication number CN104866709A discloses a method for evaluating the quality of anchor grouting in underground engineering. The method calculates the improvement rate of drilling core, the improvement rate of internal friction angle, the improvement rate of cohesive force and other parameters before and after grouting, and establishes quantitative evaluation indexes of rock mass strength before and after grouting by using weight analysis method. The prior art with publication number CN104215748A proposes a comprehensive quantitative detection method for grouting reinforcement effect of broken surrounding rock in underground engineering. The method is based on four technical detection methods of surrounding rock drilling core, geological radar detection, drilling peep detection and in-situ drilling surrounding rock strength test, respectively, to obtain parameters such as surrounding rock drilling core improvement rate, broken area reinforcement improvement rate, crack closure improvement rate and strength parameter improvement rate before and after grouting.

[0004] In the aspect of grouting process monitoring, the prior art disclosed in the existing technology with the publication number CN115015251A discloses a visual three-dimensional fissure grouting experiment system and method under multiple acting forces. The system visually simulates the grouting reinforcement process of fissured rock mass under the combined action of ground stress and water pressure through a transparent model, and collects images of the surface of the fissured rock mass model after water injection and grouting, determines the slurry diffusion path in the fissure of the fissured rock mass model, and determines the strain field data inside the fissured rock mass model. However, the existing fissured rock mass surrounding rock grouting quality evaluation method still has the following deficiencies: the traditional evaluation method mainly depends on a single index, such as the permeability coefficient, the acoustic wave velocity, etc., and it is difficult to comprehensively reflect the filling state of the slurry in the fissure, the cementation uniformity and the improvement of the mechanical properties; the existing method mainly adopts a static evaluation mode for comparison before and after grouting, lacks effective utilization of dynamic monitoring data during grouting, and cannot real-time master the diffusion law and filling state of the slurry in the fissure; the evaluation index system is not systematic and standardized, and lacks organic connection between the indexes, and it is difficult to form a scientific and reasonable comprehensive evaluation system; there lacks a quantitative evaluation method for multi-source information fusion, and it is difficult to organically combine various parameters before, during and after grouting, and to perform systematic evaluation; the existing method lacks consideration of the three-dimensional spatial characteristics of the fissured rock mass, and it is difficult to accurately reflect the filling distribution and cementation uniformity of the slurry in the complex fissure network.

[0005] Therefore, it is urgent to establish a fissured rock mass surrounding rock grouting quality evaluation method based on multi-source information fusion, which can comprehensively consider various key parameters before, during and after grouting, and realize whole-process, multi-dimensional and quantitative evaluation of the grouting quality.

[0006] The above information disclosed in the background section is only used to strengthen the understanding of the background of the present disclosure, and therefore it can include information that does not constitute prior art known to those of ordinary skill in the art. SUMMARY

[0007] The purpose of the present application is to provide a fissured rock mass surrounding rock grouting quality evaluation method to solve the problems raised in the background.

[0008] To achieve the above-mentioned purpose, the present application provides the following technical solutions:

[0009] A fissured rock mass surrounding rock grouting quality evaluation method, the specific steps comprising:

[0010] S1: before grouting, obtaining permeability test data and acoustic wave velocity test data for characterizing the fissure connectivity and mechanical state of the target surrounding rock area, forming a characterization parameter data set of the fissure before grouting, and synchronously collecting three-dimensional point cloud data of the area, and calculating the cavity volume of the fissure before grouting through spatial modeling;

[0011] S2: During the grouting process, the electromagnetic field intensity data of the surrounding rock area to be grouted is collected, combined with the three-dimensional point cloud spatial information, and the grout filling distribution data is processed to calculate the grout filling volume and grouting filling rate. The resistivity data set of the target surrounding rock area is collected synchronously, the cementation uniformity index is calculated, and the strain time series data of the target surrounding rock area is collected to process the strain gradient;

[0012] S3: The grouting filling rate, cementation uniformity index and strain gradient are extracted, and a grouting integrity index is formed by a multi-feature fusion algorithm;

[0013] S4: After grouting is completed, the permeability test data and acoustic velocity test data of the target area are obtained again to form the fracture characterization parameter data set after grouting, and the fracture characterization parameter data sets before and after grouting are compared and analyzed to calculate the fracture characterization performance improvement rate;

[0014] S5: The penetration test data of the grouted area is collected, and the strength parameters of the stone body are calculated by analyzing the force and displacement curve and the penetration resistance peak value;

[0015] S6: The grouting integrity index, fracture characterization performance improvement rate and stone body strength parameter are multi-fused, a comprehensive score model is used to calculate the quality comprehensive score of the surrounding rock grouting, and the quality comprehensive score is compared with the preset threshold value. According to the comparison result, the fracture rock surrounding rock grouting quality is graded and evaluated.

[0016] Further, before grouting, permeability test data and acoustic velocity test data are obtained to represent the fracture connectivity and mechanical state of the target surrounding rock area. The permeability test is performed using a gas permeameter: in the target area, a rock section that can represent the entire area fracture is tested using a gas permeameter. The rock body between two packers is isolated to a length , cross-sectional area of the test section, sulfur hexafluoride gas is injected into the rock body, and the volume flow rate of the sulfur hexafluoride gas required to maintain the set pressure in the test section is stably injected. In the test system, a mass flow controller or precision flowmeter is used to accurately control and measure the gas flow value. The downstream gas concentration decay curve is monitored:

[0017] ;

[0018] wherein, is the permeability coefficient of the target surrounding rock area, is the atmospheric pressure, is the gas flow, is the gas dynamic viscosity, is the test section length, is the test section cross-sectional area, is the inlet absolute pressure, is the outlet absolute pressure; the ultrasonic flaw detector is used to test the acoustic wave velocity of the same rock mass region:

[0019] ;

[0020] wherein, is the longitudinal wave velocity of the target surrounding rock region, is the propagation path length, is the longitudinal wave propagation time, the permeability coefficient of the surrounding rock region and the longitudinal wave velocity form a data set of crack characterization parameters before grouting; a three-dimensional laser scanner is used to collect three-dimensional point cloud data of the region, the point cloud is registered by ICP algorithm and a three-dimensional crack network model is constructed, and the crack cavity volume before grouting is calculated .

[0021] Further, in the grouting process, the electromagnetic field intensity data of the surrounding rock region to be grouted is collected, and combined with the three-dimensional point cloud spatial information, the grout filling distribution data is processed, and the grout filling volume and grouting filling rate are calculated : electromagnetic sensors are arranged in advance, electromagnetic sensor arrays are arranged, conductive modified grout is injected into the fractured rock mass, electromagnetic field intensity data of the region is collected during grouting, and grout filling distribution cloud chart in the crack is generated after grouting is completed: through the least squares based electromagnetic inversion algorithm, the three-dimensional resistivity distribution of grout in the crack is reconstructed, the filling distribution cloud chart is generated, the grout filling volume is obtained, and the grouting filling rate is calculated accordingly; then, the grout filling volume value is divided by the total volume of the crack cavity before grouting obtained by three-dimensional laser scanning and modeling, and finally the quotient obtained is multiplied by one hundred percent, that is, the grouting filling rate is obtained;

[0022] The resistivity data set of the target surrounding rock region is collected synchronously, and in the grouting process, the transmitting and receiving electrode pairs are automatically cycled to switch at equal time intervals, and the resistivity time series data set inside the rock mass is collected to calculate the cementation uniformity index ; in the grouting process, the data set reflecting the change of resistivity inside the rock mass is obtained by cyclic measurement of the electrode array; the average value of all resistivity measurement values in a specific evaluation region is calculated , and at the same time, the standard deviation of the fluctuation of these resistivity values around the average value is calculated ; the cementation uniformity index is obtained by subtracting the ratio of the standard deviation to the average value from 1 ;

[0023] Strain time series data of the target surrounding rock region are collected simultaneously; before the grouting process, distributed optical fiber sensors are arranged along the strike of the crack, strain data are collected during the grouting process, and strain gradient is obtained by processing in the continuous collection mode triggered at equal time intervals

[0024] ;

[0025] wherein, is a strain gradient, is a first a strain difference between adjacent sensors, is a distance between the pair of sensors, is a number of sensor pairs.

[0026] Further, the grouting filling rate, the cementation uniformity index and the strain gradient are extracted for feature extraction, and a grouting integrity index is obtained through a multi-feature fusion algorithm:

[0027] ;

[0028] wherein, is a grouting integrity index, is a critical strain gradient threshold, is a weight coefficient, satisfying and are in the interval .

[0029] Further, after grouting is completed, the permeability test data and the acoustic wave velocity test data of the target area are obtained again to form a representation parameter data set of the fracture after grouting, and the representation parameter data sets of the fractures before and after grouting are compared and analyzed to calculate a fracture representation performance improvement rate:

[0030] ;

[0031] wherein, is a fracture representation performance improvement rate, is a permeability coefficient of the target surrounding rock area before grouting, is a permeability coefficient of the target surrounding rock area after grouting, is a longitudinal wave velocity of the target surrounding rock area before grouting, is a longitudinal wave velocity of the target surrounding rock area after grouting, and are weight coefficients, satisfying , and are in the interval .

[0032] Further, the penetration test data of the area after grouting is collected: the stone body area formed after grouting is randomly selected for micro-damage penetration testing to obtain the stone body strength, the micro-damage penetration test is performed, the hydraulic servo control penetration instrument is used, the multi-point penetration test is performed in the area where the grouting filling rate is greater than or equal to a preset filling threshold and the cementation uniformity index is greater than or equal to a preset uniformity threshold, the force-displacement curve and the penetration resistance peak value are analyzed, and the stone body strength parameters are calculated:

[0033] ;

[0034] wherein, is a stone body strength parameter, is a first point pouring peak force, is a probe cross-sectional area, is a test point number.

[0035] Further, the grouting integrity index, the fracture characterization performance improvement rate and the stone body strength parameter are fused, a comprehensive score model is used to calculate a quality comprehensive score of the surrounding rock grouting, the quality comprehensive score is compared with a preset threshold value, and the surrounding rock grouting quality is evaluated according to the comparison result:

[0036] ;

[0037] wherein, is a surrounding rock grouting quality comprehensive score, is a performance function of the stone body strength, and are weight coefficients, satisfy , and are all in interval.

[0038] Further, the surrounding rock grouting quality comprehensive score is compared with the preset threshold value, and the grouting quality to be evaluated is evaluated according to the comparison result; the specific logic for comparing the surrounding rock grouting quality comprehensive score with the preset threshold value is: if , it is indicated that the surrounding rock grouting quality of the fractured rock mass is good, and the grouting effect is very ideal; if , it is indicated that the surrounding rock grouting quality of the fractured rock mass is at a medium level, and the grouting effect is better; if , it is indicated that the surrounding rock grouting quality of the fractured rock mass is poor, the grouting effect is not ideal, there is a serious quality problem, and the engineering requirement cannot be met; in the formula, wherein, is a surrounding rock grouting quality comprehensive score, is a preset quality evaluation threshold

[0039] Compared with the prior art, the beneficial effects of the present application are: through multi-source data fusion technology, comprehensive physical, acoustic, electromagnetic, mechanical and other multi-dimensional information is integrated to realize comprehensive evaluation of grouting quality, overcoming the limitations of traditional single index evaluation method; through real-time monitoring of slurry distribution, cementation uniformity and strain change during grouting, dynamic monitoring of grouting state is realized, and timely feedback of grouting effect is realized; the multi-source data is converted into quantitative scoring index by using mathematical model, so that the evaluation result is more objective and reliable; the method is suitable for various geotechnical engineering scenes such as tunnels, mines, water conservancy and the like, and has strong engineering applicability. Experiments show that, compared with the traditional single index evaluation method, the evaluation method proposed by the present application can improve the grouting quality evaluation accuracy by about 30%, reduce the engineering rework rate caused by inaccurate grouting quality evaluation by about 25%, and significantly improve the engineering construction efficiency and safety. BRIEF DESCRIPTION OF DRAWINGS

[0040] Figure 1 is a whole method flowchart of the present application;

[0041] Figure 2 is a strain experiment data graph of the present application. DETAILED DESCRIPTION

[0042] In order to make the purpose, technical scheme and advantages of the present application more clear and obvious, the present application is further described in detail below in combination with specific embodiments.

[0043] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the present application should be understood as the usual meaning understood by those skilled in the art to which the present application belongs. The "first", "second" and similar words used in the present application do not represent any order, quantity or importance, but are only used to distinguish different components. "Include" or "contain" and similar words mean that the elements or objects before the word cover the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connected" or "connected" and similar words are not limited to physical or mechanical connection, but can include electrical connection, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to represent relative positional relationship, when the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0044] Embodiment:

[0045] Please refer to Figure 1 , the present application provides a technical scheme:

[0046] A fissure rock mass surrounding rock grouting quality evaluation method, the specific steps include:

[0047] S1: Before grouting, obtain permeability test data and acoustic wave velocity test data for characterizing the connectivity and mechanical state of the target surrounding rock area, form a set of pre-grouting crack characterization parameter data, and simultaneously collect three-dimensional point cloud data of the area, and calculate the pre-grouting crack cavity volume through spatial modeling;

[0048] In this embodiment, a section of fractured surrounding rock is grouted; the grouting quality is evaluated throughout the process by using the method of the application, before grouting, permeability test data and acoustic wave velocity test data for characterizing the connectivity and mechanical state of the target surrounding rock area are obtained; the permeability test is performed using a gas permeameter: based on the preliminary geological record and drilling core analysis of the target area, the lithology and fracture development profile of the target surrounding rock area are preliminarily mastered, and the rock mass section representing the fractures of the entire area is selected, and the gas permeameter is used for testing, the drill hole is isolated by installing a plugging device in the drill hole, and a section of cylindrical area is isolated by the plugging device , the cross-sectional area test section The test equipment injects sulfur hexafluoride gas into the isolated test section through a pipeline; this inlet is the "upstream", and at the other end of the test section, another pipeline is used to discharge the gas and monitor its concentration; this outlet monitoring point is the "downstream", and the gas concentration decay curve is monitored at the downstream:

[0049] ;

[0050] wherein, is the permeability coefficient of the target surrounding rock area, is the atmospheric pressure, is the gas flow, is the dynamic viscosity of the gas, is the test section length, is the test section cross-sectional area, is the inlet absolute pressure, is the outlet absolute pressure; the connectivity and openness of the fracture network in the rock mass are quantitatively evaluated. The permeability coefficient directly reflects the difficulty of fluid flow in the rock mass, The greater the value, the greater the water permeability of the rock mass, and there may be a risk of leakage, one of the main purposes of grouting is to plug the cracks and reduce the permeability. Only by measuring before grouting and measuring after grouting can there be a comparative significance, so as to calculate the performance improvement rate, and an ultrasonic flaw detector is used to test the acoustic wave velocity of the same rock mass area:

[0051] ;

[0052] wherein, The longitudinal wave velocity of the target surrounding rock area, The propagation path length, The longitudinal wave propagation time, the permeability coefficient of the surrounding rock area and the longitudinal wave velocity form a parameter data set for the characterization of the pre-grouting fissure; a three-dimensional laser scanner is used to collect three-dimensional point cloud data of the area, the point cloud is registered by ICP algorithm and a three-dimensional fissure network model is constructed, and the pre-grouting fissure cavity volume is calculated; the longitudinal wave velocity of the target surrounding rock area is measured to indirectly evaluate the mechanical properties and fissure density of the rock mass, the speed of sound wave propagation in a solid is directly related to the density and elastic constant of the medium, The higher the value, the more complete and dense the rock mass, the better the mechanical properties; on the contrary, The low value indicates that the rock mass is broken and the fissure is developed; after grouting, the slurry fills the fissure, making the rock mass more "complete" and the sound wave propagation path more unobstructed, so the wave velocity will increase. Comparing and before and after grouting is an important indicator for evaluating the grouting reinforcement effect.

[0053] S2: In the grouting process, the electromagnetic field intensity data of the surrounding rock area of the area to be grouted are collected, and the slurry filling distribution data are processed in combination with the three-dimensional point cloud spatial information, and the slurry filling volume and grouting filling rate are calculated, the resistivity data set of the target surrounding rock area is collected synchronously, the cementation uniformity index is calculated, and the strain time series data of the target surrounding rock area are collected synchronously, and the strain gradient is processed;

[0054] In this embodiment, the electromagnetic field intensity data of the surrounding rock area of the area to be grouted are collected, and the slurry filling distribution data are processed in combination with the three-dimensional point cloud spatial information, and the slurry filling volume and grouting filling rate are calculated: electromagnetic sensors are arranged in advance, electromagnetic sensor arrays are arranged, conductive modified slurry is injected into the fissured rock mass, electromagnetic field intensity data of the area are collected during the grouting process, and a filling distribution cloud chart of the slurry in the fissure is generated after the grouting is completed: the three-dimensional resistivity distribution of the slurry in the fissure is reconstructed by the least squares-based electromagnetic inversion algorithm, the filling distribution cloud chart is generated, the slurry filling volume is obtained, and the grouting filling rate is calculated accordingly; then, the slurry filling volume value is divided by the total volume of the pre-grouting fissure cavity obtained by three-dimensional laser scanning and modeling , and finally the obtained quotient is multiplied by one hundred percent, that is, the grouting filling rate is obtained;

[0055] ;

[0056] Among them, is the grouting filling rate, is the slurry filling volume, is the pre-grouting fissure cavity volume, and the grouting filling rate is obtained; The greater the value, the higher the filling rate, and vice versa. The filling rate is the most direct and core indicator of the integrity of the grouting operation. A low filling rate means that there are unfilled areas, which will become weak points of leakage and strength. , , The resistivity data set of the target surrounding rock area is collected synchronously. In the grouting process, the transmitting and receiving electrode pairs are automatically switched at equal time intervals to collect the resistivity time series data set inside the rock mass to calculate the cementation uniformity index During grouting, the electrode array is cycled to measure and obtain a data set reflecting the change in internal resistivity of the rock mass. The average value of all resistivity measurements in a specific evaluation area is calculated At the same time, the standard deviation of the fluctuation of these resistivity values around the average value is calculated Subtracting the ratio of the standard deviation to the average value from 1 gives the cementation uniformity index ;

[0057] The resistivity data set of the target surrounding rock area is collected synchronously. In the grouting process, the transmitting and receiving electrode pairs are automatically switched at equal time intervals to collect the resistivity time series data set inside the rock mass to calculate the cementation uniformity index,

[0058] ;

[0059] wherein, is the cementation uniformity index, is the standard deviation of the grout resistivity in the fracture area, is the average value of the resistivity in the area; This measures the degree of dispersion of the resistivity data. The greater the dispersion, the greater the difference in resistivity values at different points, with some areas having good conductivity and dense grout, and some areas having poor conductivity, water, or air bubbles, i.e., the more uneven it is. is used to normalize the standard deviation, as the size of the dispersion itself needs to be compared with the average level to be meaningful; CUI aims to evaluate the uniformity of grout distribution in the fracture and the uniformity of the solidification quality of the grout. Uneven filling may result in: local water-cement ratio too high, low strength, presence of air bubbles or voids, and grout stratification and segregation; is the coefficient of variation, which is a dimensionless statistical quantity that measures relative dispersion. The greater the coefficient of variation, the more uneven it is, and the smaller the CUI value. When the coefficient of variation is 0, the CUI reaches a maximum value of 1. This makes CUI one of the intuitive indicators of grouting operation integrity; in this embodiment, , , therefore ;

[0060] At the same time, the strain time series data of the target surrounding rock area is collected; in this embodiment, before the grouting process, the distributed optical fiber sensor is arranged along the fissure trend, the strain data is collected during the grouting process, the continuous collection mode triggered at equal time intervals is adopted, the time interval is 30 seconds, and the strain gradient is obtained by processing:

[0061]

[0062] Wherein, is the strain gradient, is the first The strain difference between adjacent sensors, is the distance between the sensor pair, is the number of sensor pairs; the sensor pair is a calculation unit composed of two adjacent optical fiber sensing points virtually divided for calculating the strain gradient, and the disturbance and potential damage of the grouting pressure to the surrounding rock are monitored. The higher the grouting pressure is not the better, and the overhigh pressure may crack the originally intact rock mass and produce new fissures; The strain change per unit length, that is, the definition of the gradient. Its absolute value represents the degree of change, and it does not matter whether it is compression or stretching; the average strain gradient in the whole monitoring area is obtained by summing and averaging, and is used to evaluate the degree of overall disturbance of the grouting process to the rock mass. The larger the SG value means that the strain changes sharply in a very short distance, which usually occurs at the crack tip or the defect edge, and is the sign of micro-crack initiation and expansion. Therefore, SG is an important safety warning index; in this embodiment, the distributed optical fiber sensor is arranged with 19 measuring points, forming 18 adjacent sensor pairs. The experimental data are as follows:

[0063] Table 1: Strain experimental data table:

[0064]

[0065] That is, according to the formula, the average strain gradient , refer to Figure 2 , clearly show the spatial variation law of the strain gradient in the surrounding rock during the grouting process, and help to identify the section strain change sharply. The strain gradient absolute values of the midpoint 0.7m, 0.9m, 1.1m, 2.3m, 2.5m corresponding to the sensor pair numbers 4, 5, 6, 12, 13 are 75 , 90 , 75 , 100 , 90 ​, these peak points are likely to be the tip of the original crack, the intersection of different cracks or the interface of lithology change. At these sites, stress is easy to concentrate, grouting pressure will preferentially force the slurry into or produce greater wedge action on the rock mass; high strain gradient is a sign of micro-crack initiation and expansion. This means that the grouting pressure may be opening the original micro-cracks, and even new micro-damage may be produced. Although the highest value 100 in this grouting does not exceed the critical threshold value 120 set in the example, indicating that the process is within the controllable range, but it is very close to the limit;

[0066] S3: Feature extraction is performed on the grouting filling rate, cementation uniformity index and strain gradient, and a grouting integrity index is formed through a multi-feature fusion algorithm;

[0067] In this example: the grouting filling rate, cementation uniformity index and strain gradient are extracted, and the grouting integrity index is obtained through a multi-feature fusion algorithm:

[0068] ;

[0069] wherein, is the grouting integrity index, is the critical strain gradient threshold, is the weight coefficient, satisfying and are in the interval , the grouting integrity index fuses the three features of different dimensions extracted in S2 , , into a single comprehensive index to evaluate the pros and cons of the "grouting process" as a whole. It reflects the overall quality of grouting operation; and are positive contributions to the grouting effect, the larger the value, the higher the value; is the strain gradient compared with its critical threshold, which is converted into a dimensionless ratio, which makes the third term of the formula can be added or subtracted with the first two terms. The negative contribution of cost or risk to the grouting effect; in this example, the weight , is calculated to be 0.666.

[0070] S4: After grouting is completed, the permeability test data and acoustic velocity test data of the target area are obtained again, the grouting fracture characterization parameter data set is formed, and the grouting fracture characterization parameter data sets before and after grouting are compared and analyzed, and the fracture characterization performance improvement rate is calculated;

[0071] In this embodiment, after grouting is completed, the permeability test data and the acoustic wave speed test data of the target area are obtained again to form a set of grouting post-fracture characterization parameter data, and the grouting pre-and post-fracture characterization parameter data sets are compared and analyzed to calculate the fracture characterization performance improvement rate:

[0072] ;

[0073] wherein, is the fracture characterization performance improvement rate, is the permeability coefficient of the target surrounding rock area before grouting, is the permeability coefficient of the target surrounding rock area after grouting, is the longitudinal wave speed of the target surrounding rock area before grouting, is the longitudinal wave speed of the target surrounding rock area after grouting, and is a weight coefficient, satisfying , and is in the interval of .

[0074] GII evaluates the process, while evaluates the result, directly quantifies the performance improvement brought by grouting from the perspective of macroscopic physical properties of rock mass, and is a manifestation of the final effect of grouting; the relative ratio of permeability coefficient reduction after grouting. The greater the value, the better the plugging effect; the relative ratio of wave speed improvement after grouting. The greater the value, the more obvious the rock mass integrity enhancement effect. The weight allows the focus to be adjusted according to the engineering target. For example, for reservoir dam anti-seepage grouting, 0.7 can be set; for tunnel reinforcement grouting, 0.7 can be set.

[0075] In this embodiment, the test section length , the borehole diameter is 100 mm, the cross-sectional area is , the atmospheric pressure is , the gas dynamic viscosity is , the actual gas flow is , the inlet pressure is , the outlet pressure is , so ; the ultrasonic flaw detector is used to test the acoustic wave speed of the same rock mass area: the propagation path length is , the actual propagation time is , and the longitudinal wave speed is calculated ; after grouting, the permeability and acoustic wave speed are retested at the same position, , ; the weight , , and the fracture characterization performance improvement rate is .

[0076] S5: Collect the penetration test data of the grouting area after grouting, calculate the strength parameters of the stone body by analyzing the force-displacement curve and the peak value of the penetration resistance;

[0077] In this embodiment, the stone body region formed after grouting is randomly selected for micro-damage penetration testing to obtain the stone body strength. The hydraulic servo control penetration instrument is used for penetration testing. In the area where the grouting filling rate is greater than or equal to the preset filling threshold, and the cementation uniformity index is greater than or equal to the preset uniformity threshold, in this embodiment, the preset filling threshold is 95%, and the preset uniformity threshold is 0.85; multi-point penetration testing is performed, and the stone body strength parameters are calculated by analyzing the force-displacement curve and the peak value of the penetration resistance:

[0078]

[0079] wherein, is the stone body strength parameter, is the peak force of the first point penetration, is the probe cross-sectional area, is the number of test points. The traditional grouting quality evaluation method (such as inspection hole coring) can directly obtain the strength, but it is a local and destructive method, and the cost is high and the representativeness is limited. There is a certain uncertainty in relying only on non-destructive indicators such as acoustic wave velocity to indirectly infer the strength. The introduction of the stone body strength parameter is aimed at directly verifying the mechanical properties of the grouting area by a micro-damage, in-situ and rapid testing method, providing the most direct strength evidence for comprehensive evaluation, making up for the shortcomings of pure non-destructive inference, and avoiding the destructive and high cost of full drilling of rock cores; a portable, microcomputer-controlled electronic penetration instrument is used. The instrument is equipped with a small and hard probe. On the surface of the rock mass after grouting and reinforcement, select multiple representative test points, operate the penetration instrument, and press the probe into the surface of the rock to be tested at a constant rate. The instrument records the resistance value in real time during the entire penetration process;

[0080] In this embodiment: after 72 hours of grouting solidification, a hydraulic servo penetration instrument model HYZ-100 is used, penetration testing is performed at 3 points in the grouting area, the penetration rate is controlled at 0.5 mm / s, and the force-displacement curve is recorded; the peak force of each test point is extracted, and the stone body strength parameter is calculated.

[0081] S6: The grouting integrity index, the fracture characterization performance improvement rate and the stone body strength parameter are fused, the comprehensive score of the quality of the surrounding rock grouting is calculated by using a comprehensive score model, the quality comprehensive score is compared with the preset threshold, and the surrounding rock grouting quality of the fractured rock mass is evaluated according to the comparison result.

[0082] ​In the embodiment, the grouting integrity index, the fracture characterization performance improvement rate and the stone body strength parameter are fused, the quality comprehensive score of the surrounding rock grouting is calculated by using a comprehensive score model, the quality comprehensive score is compared with a preset threshold value, and the surrounding rock grouting quality of the fractured rock mass is evaluated according to the comparison result.

[0083] ;

[0084] Among them, is the quality comprehensive score of the surrounding rock grouting, is a performance function of the stone body strength, is a lower limit value of the stone body strength, is a target value of the stone body strength, and are weight coefficients, satisfying , and are all in the interval of .

[0085] The quality comprehensive score of the surrounding rock grouting is fused for final decision. The indexes reflecting the process , the index reflecting the performance improvement of the rock mass and the index reflecting the material strength are integrated into a total score in the percentage system, and an intuitive and qualitative quality level is given accordingly; The theoretical value range of the index may be negative if the disturbance is large, while the indexes and are positive numbers. Direct addition is not coordinated, is a linear transformation that maps the value range of to the interval [0, 1].

[0086] In the embodiment, , , , according to the above steps, the experimental data obtained by the surrounding rock grouting reinforcement operation .

[0087] In the embodiment, the quality comprehensive score of the surrounding rock grouting of the fractured rock mass is compared with a preset threshold value, and the grouting quality to be evaluated is evaluated according to the comparison result; the specific logic for comparing the quality comprehensive score of the surrounding rock grouting of the fractured rock mass with the preset threshold value is as follows: if , it indicates that the surrounding rock grouting quality of the fractured rock mass is good, and the grouting effect is very ideal; if , it indicates that the surrounding rock grouting quality of the fractured rock mass is at a medium level, and the grouting effect is better; if , it indicates that the surrounding rock grouting quality of the fractured rock mass is poor, the grouting effect is not ideal, there is a serious quality problem, and it cannot meet the engineering requirements; in the formula, A comprehensive quality score of the surrounding rock grouting is obtained, The preset quality evaluation threshold value is obtained.

[0088] The design idea of the technical solution is: data is obtained from multiple dimensions such as geometry, hydraulics, mechanics, and electrical properties; a mathematical model of multi-index weighted fusion is used to combine process monitoring and result testing; complex engineering quality problems are converted into a calculable and objective quantitative score; and finally, scientific and accurate quality evaluation and grading are realized.

[0089] In the embodiment, the preset threshold value is , , Therefore, the quality level is: medium. The above formulas are dimensionless values for calculation, the formula is obtained by software simulation of the latest real situation based on collected data, and the preset parameters in the formula are set by a person skilled in the art according to the actual situation.

[0090] The above embodiments can be realized wholly or partially by software, hardware, firmware, or any other combination. When realized by software, the above embodiments can be realized in the form of a computer program product wholly or partially. Those skilled in the art can realize that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be realized by electronic hardware or a combination of computer software and electronic hardware. Whether the functions are realized by hardware or software methods depends on the specific application and design constraints of the technical solution.

[0091] The units described as separate components can or can not be physically separated, and the components shown as units can or can not be physical units, which can be located in one place or distributed on multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.

[0092] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto, and any person skilled in the art can easily think of changes or replacements within the technical range disclosed in the present application, which should be covered within the protection scope of the present application.

Claims

1. A method for evaluating the quality of grouting of surrounding rock of a fractured rock mass, characterized in that, The specific steps include: S1: Before grouting, obtain permeability test data and acoustic wave velocity test data for characterizing the connectivity and mechanical state of the target surrounding rock area, form a pre-grouting fracture characterization parameter dataset, and simultaneously collect three-dimensional point cloud data of the area, and calculate the pre-grouting fracture cavity volume through spatial modeling; S2: During the grouting process, collect electromagnetic field intensity data of the surrounding rock area to be grouted, and combine with three-dimensional point cloud spatial information to obtain grout filling distribution data, and calculate the grout filling volume and grouting filling rate, simultaneously collect the resistivity dataset of the target surrounding rock area, calculate the cementation uniformity index, and simultaneously collect the strain time series data of the target surrounding rock area, and process the strain gradient; S3: Feature extraction is performed on the grouting filling rate, cementation uniformity index and strain gradient, and a multi-feature fusion algorithm is used to form a grouting integrity index; S4: After grouting is completed, the permeability test data and acoustic wave velocity test data of the target area are obtained again, a post-grouting fracture characterization parameter dataset is formed, and the pre- and post-grouting fracture characterization parameter datasets are compared and analyzed to calculate the fracture characterization performance improvement rate; S5: Collect the penetration test data of the area after grouting, analyze the force and displacement curve and the penetration resistance peak value, and calculate the stone body strength parameter; S6: Multi-element fusion is performed on the grouting integrity index, fracture characterization performance improvement rate and stone body strength parameter, a comprehensive score model is used to calculate the quality comprehensive score of the surrounding rock grouting, the quality comprehensive score is compared with the preset threshold value, and the fracture rock mass surrounding rock grouting quality is classified and evaluated according to the comparison result.

2. The method according to claim 1, characterized in that: Before grouting, permeability test data and acoustic wave velocity test data are obtained for characterizing the connectivity and mechanical state of the target surrounding rock area; permeability test is performed using a gas pressure permeameter: In the target area, a section of rock mass that can represent the entire area fracture is tested by using a gas pressure permeameter. The rock mass between two packers installed in the borehole is isolated to a length of test section , cross-sectional area , and sulfur hexafluoride gas is injected into the rock mass, and the gas concentration decay curve is monitored downstream: ； wherein, K is the permeability coefficient of the target surrounding rock area, P is the atmospheric pressure, Q is the gas flow rate, μ is the dynamic viscosity of the gas, L is the length of the test section, A is the cross-sectional area of the test section, P is the absolute pressure at the inlet, P is the absolute pressure at the outlet; and using an ultrasonic flaw detector to test the acoustic wave velocity of the same rock mass area: ； wherein, is the longitudinal wave velocity of the target surrounding rock area, is the propagation path length, is the longitudinal wave propagation time, and the permeability coefficient of the surrounding rock area and the longitudinal wave velocity form a data set of crack characterization parameters before grouting; a three-dimensional laser scanner is used to collect three-dimensional point cloud data of the area, the point cloud is registered by an ICP algorithm, and a three-dimensional crack network model is constructed, and the crack cavity volume before grouting is calculated .

3. The method according to claim 1, characterized in that: In the grouting process, the electromagnetic field intensity data of the surrounding rock area of the area to be grouted is collected, combined with the three-dimensional point cloud space information, the grout filling distribution data is processed, and the grout filling volume is calculated and grouting filling rate : Pre-dispose electromagnetic sensors, dispose electromagnetic sensor array, inject conductive modified grout into fractured rock mass, collect electromagnetic field intensity data in the area during grouting, generate grout filling distribution nephogram in the fracture after grouting is completed: through least squares based electromagnetic inversion algorithm, reconstruct three-dimensional resistivity distribution of grout in the fracture, generate filling distribution nephogram, obtain grout filling volume, and calculate grouting filling rate according to the grout filling volume; then, divide the grout filling volume value by the total volume of the fracture cavity before grouting obtained by three-dimensional laser scanning and modeling, finally, multiply the quotient obtained by one hundred percent, and the grouting filling rate is obtained; Synchronously collect the resistivity data set of the target surrounding rock area, and in the grouting process, the transmitting and receiving electrode pairs are automatically switched at equal time intervals to collect the resistivity time series data set inside the rock mass to calculate the cementation uniformity index ; in the grouting process, the data set reflecting the change of the resistivity inside the rock mass is obtained through the electrode array cycle measurement; the average value of all resistivity measurement values in a specific evaluation area is calculated , and at the same time, the standard deviation of the fluctuation of these resistivity values around the average value is calculated ; the result obtained by subtracting the ratio of the standard deviation to the average value from 1 is the cementation uniformity index ; Strain time series data of the target surrounding rock area are simultaneously collected; Before the grouting process, distributed optical fiber sensors are arranged along the fracture strike, strain data are collected during the grouting process, a continuous collection mode with equal time intervals is adopted, and the strain gradient is processed: ； wherein, is a strain gradient, is a first is a difference in strain between adjacent sensors, is a distance between the pair of sensors, is a number of pairs of sensors.

4. The fissure rock mass surrounding rock grouting quality evaluation method according to claim 1 or 3, characterized in that: Feature extraction is performed on the grouting filling rate, cementation uniformity index and strain gradient, and a multi-feature fusion algorithm is used to obtain the grouting integrity index: ； wherein, is a grouting integrity index, is a critical strain gradient threshold, is a weight coefficient, satisfying and are both in interval.

5. The method according to claim 2, characterized in that: After grouting is completed, the permeability test data and acoustic wave velocity test data of the target area are obtained again, a post-grouting fracture characterization parameter dataset is formed, and the pre- and post-grouting fracture characterization parameter datasets are compared and analyzed to calculate the fracture characterization performance improvement rate: ； wherein, is a fissure characterization performance improvement rate, is a target surrounding rock region permeability coefficient before grouting, is a target surrounding rock region permeability coefficient after grouting, is a target surrounding rock region P-wave velocity before grouting, is a target surrounding rock region P-wave velocity after grouting, and is a weight coefficient, satisfying , and is in an interval of .

6. The fissure rock mass surrounding rock grouting quality evaluation method according to claim 1, characterized in that: Penetration test data of the area after grouting are collected: test points are randomly selected in the stone body area formed after grouting for micro-damage penetration test to obtain the stone body strength, micro-damage penetration test is performed, a hydraulic servo control penetration instrument is used to perform multi-point penetration test in the area where the grouting filling rate is greater than or equal to the preset filling threshold value and the cementation uniformity index is greater than or equal to the preset uniformity threshold value, the force-displacement curve and the penetration resistance peak value are analyzed, and the stone body strength parameter is calculated: ； wherein, is the stone body strength parameter, is the first is the point infusion peak force, is the probe cross-sectional area, is the number of test points.

7. The fissure rock mass surrounding rock grouting quality evaluation method according to claim 1, characterized in that: The grouting integrity index, the fracture characterization performance improvement rate and the stone body strength parameter are fused, a comprehensive score model is used to calculate the quality comprehensive score of the surrounding rock grouting, the quality comprehensive score is compared with a preset threshold, and the surrounding rock grouting quality is evaluated according to the comparison result: ； wherein, is the comprehensive score of the quality of the surrounding rock grouting, is the performance function of the strength of the stone body, and is the weight coefficient, satisfying , and, are all in the interval .

8. The method according to claim 7, characterized in that: The fissure rock surrounding rock grouting quality comprehensive score is compared with a preset threshold value, and the grouting quality to be evaluated is evaluated according to the comparison result. If the fissure rock surrounding rock grouting quality comprehensive score is greater than the preset threshold value, it indicates that the fissure rock surrounding rock grouting quality is good, and the grouting effect is very ideal. If the fissure rock surrounding rock grouting quality comprehensive score is less than the preset threshold value, it indicates that the fissure rock surrounding rock grouting quality is at a medium level, and the grouting effect is better. If the fissure rock surrounding rock grouting quality comprehensive score is less than the preset threshold value, it indicates that the fissure rock surrounding rock grouting quality is poor, the grouting effect is not ideal, and there is a serious quality problem, which cannot meet the engineering requirements. is the surrounding rock grouting quality comprehensive score, is the preset quality evaluation threshold value.

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