Rock mass quality evaluation method and evaluation device based on TBM tunneling surrounding rock microseismic monitoring

Abstract

The application relates to a rock mass quality evaluation method and device based on TBM tunneling surrounding rock microseismic monitoring, wherein the method comprises the following steps: collecting microseismic signals generated by rock mass rupture in full-face tunnel boring machine (TBM) tunneling; processing the microseismic signals to obtain mechanical wave signals meeting preset conditions; extracting at least one rock mass wave velocity parameter according to the mechanical wave signals, analyzing rock strength and rock mass integrity information according to the at least one rock mass wave velocity parameter, and generating a rock mass quality evaluation index according to the rock strength and rock mass integrity information. Thus, the problems in the prior art that the rock mass quality evaluation method can only obtain local point data, the coverage range is limited, it is difficult to comprehensively reflect the overall state of the rock mass in front of the tunneling, the detection period is long, and it is difficult to reflect the dynamic change of the surrounding rock in real time are solved.

Description

Technical Field

[0001] This application relates to the field of rock mass quality evaluation technology, and in particular to a rock mass quality evaluation method and device based on microseismic monitoring of surrounding rock during TBM (Tunnel Boring Machine) tunneling. Background Technology

[0002] TBM (Transmission Machine) technology is widely used in tunnel and underground engineering construction due to its high efficiency and safety. The stability of the surrounding rock during TBM tunneling is directly related to the safety and economy of the project.

[0003] In related technologies, the evaluation of rock mass quality mainly relies on borehole sampling and laboratory testing. Rock core samples are obtained by drilling at predetermined points and transported to the laboratory for a series of physical and mechanical tests to evaluate parameters such as compressive strength, tensile strength, and elastic modulus, thereby determining the quality grade of the rock mass.

[0004] However, in related technologies, drilling and sampling can only obtain local point data with limited spatial coverage, making it difficult to fully reflect the overall state of the rock mass ahead of the tunnel. Furthermore, it usually takes a certain amount of time from sampling to laboratory testing, which cannot meet the real-time decision-making needs of TBM rapid tunneling and urgently needs to be improved. Summary of the Invention

[0005] This application provides a rock mass quality evaluation method and device based on microseismic monitoring of surrounding rock during TBM tunneling, in order to solve the technical problems in related technologies, such as long evaluation cycle, limited spatial coverage, inability to capture subtle changes, and difficulty in reflecting dynamic changes of surrounding rock in real time.

[0006] The first aspect of this application provides a rock mass quality evaluation method based on microseismic monitoring of surrounding rock during TBM tunneling, comprising the following steps: acquiring microseismic signals generated by rock fracturing during full-face TBM tunneling; processing the microseismic signals to obtain mechanical wave signals that meet preset conditions; extracting at least one rock mass wave velocity parameter based on the mechanical wave signal, and analyzing rock strength and rock mass integrity information based on the at least one rock mass wave velocity parameter, and generating rock mass quality evaluation indicators based on the rock strength and rock mass integrity information.

[0007] By using the above technical means, microseismic signals generated by rock fracturing during TBM tunneling are collected. After processing, the rock strength and rock mass integrity information are comprehensively analyzed to generate rock mass quality evaluation indicators. This allows for real-time and continuous monitoring of the rock mass condition, comprehensively reflecting the overall condition of the surrounding rock and providing timely and accurate data support for the construction process.

[0008] Optionally, in one embodiment of this application, processing the micro-vibration signal to obtain a mechanical wave signal that meets preset conditions includes: performing wavelet processing and local gain amplification processing on the micro-vibration signal to obtain a processed micro-vibration signal; and extracting the arrival time information of the P-wave from the micro-vibration signal to generate the mechanical wave signal that meets the preset conditions.

[0009] By using the above technical means, P-wave arrival information can be extracted from microseismic signals, which can promptly issue early warnings when abnormal stress concentration or fracture trends occur in the rock mass. This enables real-time perception and dynamic tracking of the surrounding rock condition, providing strong technical support for rock mass stability assessment and risk prevention during TBM tunneling.

[0010] Optionally, in one embodiment of this application, the step of extracting at least one rock mass wave velocity parameter based on the mechanical wave signal includes: analyzing the propagation time and propagation path of the microseismic signal based on the mechanical wave signal; and calculating the rock mass wave velocity of the at least one rock mass wave velocity parameter based on the propagation time and the propagation path.

[0011] Using the above technical means, the rock mass wave velocity of at least one rock mass wave velocity parameter is calculated based on the propagation time and path of the microseismic signal. Therefore, the embodiments of this application, through the accurate acquisition and calculation of wave velocity parameters, can provide basic data support for subsequent rock mass strength analysis, integrity assessment, and quality grading.

[0012] Optionally, in one embodiment of this application, the formula for calculating the rock mass wave velocity can be:

[0013]

[0014] Among them, V p L is the equivalent average P-wave velocity of the rock mass in the monitoring section; L is the length of the monitoring section; t is the time it takes for the signal to propagate in the monitoring section; i is the number of segments with different wave velocities within the monitoring section; L i V is the length of the i-th segment within the monitored segment range; ai The actual average wave velocity of the i-th segment within the monitoring range.

[0015] By using the above technical means, the equivalent average P-wave velocity of the rock mass in the monitoring section can be calculated, which can obtain comprehensive wave velocity information within the entire monitoring section, cover more rock mass areas, and monitor the rock mass condition in real time during the tunneling process. At the same time, wave velocity measurement can provide more reliable data support, accurately reflect the mechanical properties, integrity and potential geological problems of the rock mass, and help to more scientifically assess the rock mass quality, improve the safety of the construction process and the accuracy of decision-making.

[0016] Optionally, in one embodiment of this application, generating a rock mass quality evaluation index based on the rock strength and rock mass integrity information includes: calculating a rock mass quality evaluation index value based on the rock strength and rock mass integrity information; and matching the rock mass quality level with the rock mass quality evaluation index to determine the rock mass quality evaluation index.

[0017] By using the above technical means, rock mass quality evaluation index values ​​can be calculated based on rock strength and rock mass integrity information, thereby determining the rock mass quality evaluation index. This can greatly improve the standardization and accuracy of rock mass quality evaluation, and quantitatively calculate the rock mass quality evaluation index values, making the evaluation results more objective and avoiding errors caused by subjective judgment. This provides more accurate and clear rock mass quality data support for TBM tunneling construction, effectively improving the scientific nature of construction decisions and the safety and efficiency of the construction process.

[0018] A second aspect of this application provides a rock mass quality evaluation device based on microseismic monitoring of surrounding rock during TBM tunneling, comprising: an acquisition module for acquiring microseismic signals generated by rock fracturing during full-face tunnel boring machine (TBM) tunneling; a processing module for processing the microseismic signals to obtain mechanical wave signals that meet preset conditions; and an evaluation module for extracting at least one rock mass wave velocity parameter based on the mechanical wave signal, analyzing rock strength and rock mass integrity information based on the at least one rock mass wave velocity parameter, and generating rock mass quality evaluation indicators based on the rock strength and rock mass integrity information.

[0019] By using the above technical means, microseismic signals generated by rock fracturing during TBM tunneling are collected. After processing, the rock strength and rock mass integrity information are comprehensively analyzed to generate rock mass quality evaluation indicators. This allows for real-time and continuous monitoring of the rock mass condition, comprehensively reflecting the overall condition of the surrounding rock and providing timely and accurate data support for the construction process.

[0020] Optionally, in one embodiment of this application, the processing module includes: a processing unit, used to perform wavelet processing and local gain amplification processing on the microseismic signal to obtain a processed microseismic signal; and a generation unit, used to extract the arrival time information of the P-wave based on the microseismic signal to generate the mechanical wave signal under the preset conditions.

[0021] By using the above technical means, P-wave arrival information can be extracted from microseismic signals, which can promptly issue early warnings when abnormal stress concentration or fracture trends occur in the rock mass. This enables real-time perception and dynamic tracking of the surrounding rock condition, providing strong technical support for rock mass stability assessment and risk prevention during TBM tunneling.

[0022] Optionally, in one embodiment of this application, the evaluation module includes: an analysis unit for analyzing the propagation time and propagation path of the microseismic signal based on the mechanical wave signal; and a first calculation unit for calculating the rock mass wave velocity of the at least one rock mass wave velocity parameter based on the propagation time and the propagation path.

[0023] Using the above techniques, the rock mass wave velocity of at least one parameter can be calculated based on the propagation time and path of the microseismic signal. Therefore, accurate acquisition and calculation of the wave velocity parameter can provide fundamental data support for subsequent rock mass strength analysis, integrity assessment, and quality classification.

[0024] Optionally, in one embodiment of this application, the formula for calculating the rock mass wave velocity is:

[0025]

[0026] Among them, V p L is the equivalent average P-wave velocity of the rock mass in the monitoring section; L is the length of the monitoring section; t is the time it takes for the signal to propagate in the monitoring section; i is the number of segments with different wave velocities within the monitoring section; L i V is the length of the i-th segment within the monitored segment range; ai The actual average wave velocity of the i-th segment within the monitoring range.

[0027] By using the above technical means, the equivalent average P-wave velocity of the rock mass in the monitoring section can be calculated, which can obtain comprehensive wave velocity information within the entire monitoring section, cover more rock mass areas, and monitor the rock mass condition in real time during the tunneling process. At the same time, wave velocity measurement can provide more reliable data support, accurately reflect the mechanical properties, integrity and potential geological problems of the rock mass, and help to more scientifically assess the rock mass quality, improve the safety of the construction process and the accuracy of decision-making.

[0028] Optionally, in one embodiment of this application, the evaluation module includes: a second calculation unit, used to calculate the rock mass quality evaluation index value based on the rock strength and rock mass integrity information; and a determination unit, used to match the rock mass quality level with the rock mass quality evaluation index and determine the rock mass quality evaluation index.

[0029] By using the above technical means, rock mass quality evaluation index values ​​can be calculated based on rock strength and rock mass integrity information, thereby determining the rock mass quality evaluation index. This can greatly improve the standardization and accuracy of rock mass quality evaluation, and quantitatively calculate the rock mass quality evaluation index values, making the evaluation results more objective and avoiding errors caused by subjective judgment. This provides more accurate and clear rock mass quality data support for TBM tunneling construction, effectively improving the scientific nature of construction decisions and the safety and efficiency of the construction process.

[0030] A third aspect of this application provides an electronic device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor. The processor executes the program to implement the rock mass quality evaluation method based on microseismic monitoring of surrounding rock during TBM tunneling as described in the above embodiments.

[0031] A fourth aspect of this application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the rock mass quality evaluation method based on microseismic monitoring of surrounding rock during TBM tunneling as described above.

[0032] A fifth aspect of this application provides a computer program product, including a computer program that, when executed, is used to implement the rock mass quality evaluation method based on microseismic monitoring of surrounding rock during TBM tunneling as described above.

[0033] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0034] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0035] Figure 1 This is a schematic diagram of a microseismic monitoring system according to an embodiment of this application;

[0036] Figure 2 This is a schematic diagram of the layout of a TBM tunneling surrounding rock microseismic monitoring system according to an embodiment of this application;

[0037] Figure 3 This is a schematic diagram showing the arrangement of the accelerometer sensor according to one embodiment of this application;

[0038] Figure 4 This is a flowchart illustrating a rock mass quality evaluation method based on microseismic monitoring of surrounding rock during TBM tunneling, according to an embodiment of this application.

[0039] Figure 5 This is a schematic diagram of a mechanical wave signal after wavelet transform according to an embodiment of this application;

[0040] Figure 6 This is a block diagram of a rock mass quality evaluation device based on microseismic monitoring of surrounding rock during TBM tunneling, according to an embodiment of this application.

[0041] Figure 7 This is a schematic diagram of the structure of an electronic device according to an embodiment of this application.

[0042] Figure label:

[0043] 10-Rock mass quality evaluation device based on microseismic monitoring of surrounding rock during TBM tunneling; 100-Acquisition module, 200-Processing module and 300-Evaluation module; 701-Memory, 702-Processor and 703-Communication interface. Detailed Implementation

[0044] The embodiments of this application are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application.

[0045] The following describes a rock mass quality evaluation method and apparatus based on microseismic monitoring of surrounding rock during TBM tunneling, according to embodiments of this application, with reference to the accompanying drawings. Addressing the technical problems mentioned in the background art, such as long evaluation cycles, limited coverage, inability to capture subtle changes, and difficulty in reflecting real-time dynamic changes in surrounding rock, this application provides a rock mass quality evaluation method based on microseismic monitoring of surrounding rock during TBM tunneling. In this method, mechanical wave information generated by rock fracturing during TBM tunneling is acquired through microseismic monitoring technology. Combined with wavelet analysis signal processing, rock wave velocity is effectively extracted, further indirectly characterizing rock strength and rock mass integrity, ultimately generating a comprehensive evaluation index for rock mass quality. This method can capture micro-fracture signals generated within the rock mass due to stress concentration or structural disturbance in real time during TBM tunneling, exhibiting high sensitivity and spatial resolution. It avoids time delays and spatial limitations in sampling and testing, achieving refined monitoring of the micro-fracture evolution process of surrounding rock, dynamically reflecting the changing characteristics of rock mass structure. Simultaneously, it can also achieve early identification and risk warning of potentially unstable areas, significantly improving the safety of tunneling construction. This solves the problems in related technologies, such as long evaluation cycles, limited coverage, and difficulty in reflecting the dynamic changes of surrounding rock in real time.

[0046] Before explaining the rock mass quality evaluation method based on microseismic monitoring of surrounding rock during TBM tunneling provided in the embodiments of this application, the system architecture and application scenarios involved in the embodiments of this application will be described first. See Figure 1 , Figure 2 and Figure 3 .

[0047] like Figure 1As shown, the microseismic monitoring system consists of a signal amplifier 105, a signal processor 106, a control computer 108, and an accelerometer 104. When the TBM excavates the rock mass 101, micro-fracture sources 102 are generated in the rock mass within the excavation face. The resulting mechanical wave signal 103 propagates through the rock mass 101 to the accelerometer 104. The signal is then received and transmitted to the control computer 108 after passing through the integration device 107. The signal amplifier 105 amplifies the clean mechanical wave information locally, the signal processor 106 acquires P-wave arrival information from the amplified signal, the control computer 108 controls the signal acquisition throughout the process, and the accelerometer 104 is typically embedded in the rock mass 101 to receive the mechanical wave signal 103 generated by rock fracturing during TBM excavation.

[0048] Furthermore, such as Figure 2 , Figure 3 As shown, depending on the size of the tunnel excavation cross-section (generally 3-14m) and the operating environment, no fewer than four accelerometers 104 are arranged in space. Generally, the accelerometers 104 are distributed side by side on both sides of the tunnel from the arch waist to the arch top. The first row of accelerometers is 40-80m away from the tunnel face, and the adjacent rows of accelerometers are spaced 20-40m apart. The accelerometers are buried near the tunnel surface 109.

[0049] Based on the system architecture and application scenarios proposed in the above embodiments, the rock mass quality evaluation method based on microseismic monitoring of surrounding rock during TBM tunneling can be implemented according to the embodiments of this application. The method will be described in detail below in conjunction with the execution flow of the rock mass quality evaluation method based on microseismic monitoring of surrounding rock during TBM tunneling.

[0050] Specifically, Figure 4 This is a schematic flowchart of a rock mass quality evaluation method based on microseismic monitoring of surrounding rock during TBM tunneling, provided as an embodiment of this application.

[0051] like Figure 4 As shown, the rock mass quality evaluation method based on microseismic monitoring of surrounding rock during TBM tunneling includes the following steps:

[0052] In step S401, microseismic signals generated by rock fracturing during the excavation of a full-face tunnel boring machine (TBM) are collected.

[0053] In the embodiments of this application, during TBM tunneling, when the rock mass is subjected to the effects of cutterhead propulsion, ground stress disturbance, or structural shearing, minute fractures or slippages occur within it. These fracture behaviors release low-energy elastic waves, i.e., microseismic signals. By deploying a highly sensitive microseismic monitoring system around the tunnel or on the tunneling equipment, these microseismic fluctuations can be collected in real time, capturing information such as the time, location, and intensity of fracture events within the rock mass. This provides important raw data for subsequent analysis of rock mass wave velocity, strength characteristics, integrity assessment, and instability risk warning, offering advantages such as non-contact, non-destructive, continuous, and real-time operation.

[0054] In step S402, the micro-vibration signal is processed to obtain a mechanical wave signal that meets preset conditions.

[0055] It should be noted that, due to the influence of geological noise, mechanical vibration, and environmental interference during the propagation of microseismic signals, the original received signals are often mixed and noisy, and need to be processed to obtain mechanical wave signals that meet the preset conditions.

[0056] The preset conditions may include ensuring that the signal-to-noise ratio of the mechanical wave signal reaches a certain threshold and that the signal contains a complete wave group structure, including a pre-noise band, a main band, and a tail band, to ensure the accuracy of subsequent P-wave pickup and propagation time calculation. These preset conditions can be set by those skilled in the art based on actual conditions, and no specific restrictions are imposed here.

[0057] Optionally, in one embodiment of this application, the micro-vibration signal is processed to obtain a mechanical wave signal that meets preset conditions, including: performing wavelet processing and local gain amplification processing on the micro-vibration signal to obtain the processed micro-vibration signal; and extracting the arrival time information of the P-wave from the micro-vibration signal to generate a mechanical wave signal that meets preset conditions.

[0058] Among them, P-waves (Primary waves) are the fastest-propelling and first-arriving longitudinal waves in seismic waves. Accurately identifying the first arrival time of P-waves is crucial for calculating wave velocity, inverting the source location, and subsequent rock mass evaluation.

[0059] In some embodiments of this application, due to the numerous noise interference sources during the on-site TBM construction phase, the effective signals collected by the microseismic monitoring system will be subject to various noise interferences. In the process of identifying rock fracture signals, it is necessary to remove other types of signals.

[0060] Specifically, this application embodiment uses the continuous wavelet transform method to perform time-frequency analysis on the original signal, extracts the time-frequency domain features of typical signals, and effectively identifies rock fracture signals. The specific formula is as follows:

[0061]

[0062] Where W(τ,s) is the continuous wavelet transform time-scale spectrum, τ is the time window shift parameter, and s is the time window scaling parameter. Let f(t) be the wavelet basis function and f(t) be the original mechanical wave signal.

[0063] Furthermore, after filtering the microseismic signal, we can obtain the following: Figure 5 The various types of signals shown are, among which, the micro-fracture signal is the effective signal that needs to be obtained in the embodiments of this application.

[0064] It should be noted that only P-waves are selected for real-time pickup in this embodiment of the application, because S-waves are easily affected by various noise interferences and are difficult to pick up.

[0065] Furthermore, the filtered information of rock mass fracture is imported into the coordinate system, and the arrival time of P-wave is picked up based on the known coordinates of the working face and the coordinates of the accelerometer.

[0066] In the embodiments of this application, by performing wavelet processing and local gain amplification on the microseismic signal, high-quality P-wave information that can be used for calculation can be extracted from the original microseismic data, providing reliable input for rock mass wave velocity calculation, intensity inversion, structure identification, etc., and significantly improving the practicality and accuracy of microseismic monitoring.

[0067] In step S403, at least one rock mass wave velocity parameter is extracted based on the mechanical wave signal, and rock strength and rock mass integrity information are analyzed based on the at least one rock mass wave velocity parameter. Rock mass quality evaluation index is generated based on the rock strength and rock mass integrity information.

[0068] It should be noted that the rock mass wave velocity parameter mainly refers to the longitudinal wave velocity (V). p ), transverse wave velocity (V) s ) and their ratio (V) p / V s Rock mass wave velocity parameters can represent dynamic indicators of the internal structural state of a rock mass. Specifically, rock mass wave velocity parameters can assess the integrity of the rock mass; higher wave velocities generally indicate a denser rock mass, fewer fissures, and better integrity. Rock mass wave velocity parameters can also identify unfavorable geological conditions; low wave velocity areas may contain fracture zones, faults, cavities, or high water-bearing areas.

[0069] For example, the rock mass wave velocity parameter V p At speeds of 5000-6000 m / s, it might be a complete granite formation, while V... p Speeds below 3000 m / s may indicate a fractured zone or fault zone. p It may drop to 2500 m / s, V p / V s The ratio increased to over 2.0, while the V of the water-bearing fracture zone...p It may be lower, while V p / V s The ratio increased significantly.

[0070] In the embodiments of this application, the rock strength and rock mass integrity information that can be obtained by inverting microseismic wave velocity data comprehensively reflect the mechanical properties and structural state of the surrounding rock. As the basic parameters for constructing rock mass quality evaluation indicators, it has important guiding value for construction risk identification, equipment control strategy optimization and support design.

[0071] Optionally, in one embodiment of this application, extracting at least one rock mass wave velocity parameter based on the mechanical wave signal includes: analyzing the propagation time and propagation path of the microseismic signal based on the mechanical wave signal; and calculating the rock mass wave velocity of at least one rock mass wave velocity parameter based on the propagation time and propagation path.

[0072] In some embodiments, the propagation time represents the time it takes for the signal to propagate from the source to the sensor, which can be obtained by picking up the first arrival time of the P wave in the microseismic signal; the propagation path represents the propagation trajectory from the source to the sensor, which can also be determined based on the spatial geometric positional relationship between the source and the seismic detector.

[0073] Specifically, this application embodiment calculates the P-wave velocity of the rock mass by analyzing the propagation time and path of the microseismic signal, using it as an important parameter for evaluating the quality of the surrounding rock. Since the microseismic monitoring system uses a uniform wave velocity for source location, it is necessary to obtain the average P-wave velocity of the rock mass within the microseismic monitoring range. Therefore, this application embodiment can use the equivalent wave velocity principle to calculate the equivalent average P-wave velocity of the rock mass within the microseismic monitoring range.

[0074] Optionally, in one embodiment of this application, the formula for calculating rock mass wave velocity can be expressed as:

[0075]

[0076] Among them, V p L is the equivalent average P-wave velocity of the rock mass in the monitoring section; L is the length of the monitoring section; t is the time it takes for the signal to propagate in the monitoring section; i is the number of segments with different wave velocities within the monitoring section; L i V is the length of the i-th segment within the monitored segment range; ai The actual average wave velocity of the i-th segment within the monitoring range.

[0077] In one specific embodiment, during the TBM tunneling process, this application embodiment can deploy a microseismic monitoring array to collect the arrival time of P-waves after the seismic source is excited and propagates to each detector point in the rock mass. The rock mass wave velocity is calculated by combining the geometric path length. The obtained wave velocity parameters can be used to invert rock strength, determine the integrity of the surrounding rock, and further be used for rock mass quality evaluation and tunneling strategy optimization.

[0078] Optionally, in one embodiment of this application, generating a rock mass quality evaluation index based on rock strength and rock mass integrity information includes: calculating the rock mass quality evaluation index value based on rock strength and rock mass integrity information; and matching the rock mass quality level with the rock mass quality evaluation index to determine the rock mass quality evaluation index.

[0079] For example, in the embodiments of this application, the rock strength and rock mass integrity can be indirectly characterized by the P-wave velocity of the rock mass extracted by microseismic monitoring. The obtained rock strength and rock mass integrity information can be incorporated into a general rock mass quality evaluation method to calculate the rock mass quality evaluation index BQ that comprehensively considers rock strength and rock mass integrity, and to classify and evaluate the surrounding rock quality.

[0080] As one possible implementation method, the specific principle of the embodiments of this application can be as follows:

[0081] Rock mass quality is classified according to the index BQ, based on the quantitative index R of the classification factors. c and K v Calculate the BQ value:

[0082] BQ = 100 + 3R c +250K v ,

[0083] R c =0.038V p -50,

[0084]

[0085] Wherein, BQ is the rock mass quality evaluation index, and R... c K represents the saturated uniaxial compressive strength of the rock. v V is the integrity coefficient. p Equivalent average P-wave velocity of rock mass, V pl The P-wave velocity of the rock block was obtained from indoor testing.

[0086] It is important to note that when R c >90K v At +30, it should be R c =90K v +30 and K v Substitute into the formula to calculate the BQ value; when K v >0.04R c When +0.4, K should be used. v =0.04R c +0.4 and R c Substitute the values ​​into the formula to calculate the BQ value.

[0087] Furthermore, the rock mass quality can be graded and evaluated based on the calculated BQ value. Table 1 shows the rock mass quality grading table.

[0088] Table 1

[0089]

[0090] The rock mass quality evaluation method based on microseismic monitoring of surrounding rock during TBM tunneling, as proposed in this application, can acquire mechanical wave information generated by rock fracturing during TBM tunneling through microseismic monitoring technology. Combined with wavelet analysis signal processing, the rock wave velocity can be effectively extracted, further indirectly characterizing rock strength and rock mass integrity, ultimately generating a comprehensive evaluation index for rock mass quality. Therefore, it can capture micro-fracture signals generated by stress disturbance or structural changes in the rock mass in real time during TBM tunneling, achieving dynamic perception of the mechanical properties and structural stability of the surrounding rock. This provides a real-time, continuous, and accurate data foundation for rock mass quality evaluation, enabling early identification and risk warning of potentially unstable areas, and improving the safety of tunneling construction. This solves the problems of long evaluation cycles, limited coverage, and difficulty in reflecting real-time dynamic changes in surrounding rock in related technologies.

[0091] Next, referring to the accompanying drawings, a rock mass quality evaluation device based on microseismic monitoring of surrounding rock during TBM tunneling is described according to an embodiment of this application.

[0092] Figure 6 This is a block diagram of a rock mass quality evaluation device based on microseismic monitoring of surrounding rock during TBM tunneling, according to an embodiment of this application.

[0093] like Figure 6 As shown, the rock mass quality evaluation device 10 based on microseismic monitoring of surrounding rock during TBM tunneling includes: a data acquisition module 100, a processing module 200, and an evaluation module 300.

[0094] Among them, the acquisition module 100 is used to acquire microseismic signals generated by rock fracturing during the excavation of a full-face tunnel boring machine (TBM).

[0095] The processing module 200 is used to process the micro-vibration signal to obtain a mechanical wave signal that meets preset conditions.

[0096] Evaluation module 300 is used to extract at least one rock mass wave velocity parameter based on mechanical wave signal, analyze rock strength and rock mass integrity information based on at least one rock mass wave velocity parameter, and generate rock mass quality evaluation index based on rock strength and rock mass integrity information.

[0097] Optionally, in one embodiment of this application, the processing module 200 includes a processing unit and a generation unit.

[0098] The processing unit is used to perform wavelet processing and local gain amplification on the microseismic signal to obtain the processed microseismic signal.

[0099] The generation unit is used to extract the arrival time information of the P-wave from the microseismic signal to generate a mechanical wave signal under preset conditions.

[0100] Optionally, in one embodiment of this application, the evaluation module 300 includes an analysis unit and a first calculation unit.

[0101] The analysis unit is used to analyze the propagation time and path of the microseismic signal based on the mechanical wave signal.

[0102] The first calculation unit is used to calculate the rock mass wave velocity of at least one rock mass wave velocity parameter based on the propagation time and propagation path.

[0103] Optionally, in one embodiment of this application, the formula for calculating the rock mass wave velocity is:

[0104]

[0105] Among them, V p L is the equivalent average P-wave velocity of the rock mass in the monitoring section; L is the length of the monitoring section; t is the time it takes for the signal to propagate in the monitoring section; i is the number of segments with different wave velocities within the monitoring section; L i V is the length of the i-th segment within the monitored segment range; ai The actual average wave velocity of the i-th segment within the monitoring range.

[0106] Optionally, in one embodiment of this application, the evaluation module 300 includes a second calculation unit and a determination unit.

[0107] The second calculation unit is used to calculate the rock mass quality evaluation index value based on rock strength and rock mass integrity information.

[0108] The determination unit is used to match the rock mass quality level with the rock mass quality evaluation index and determine the rock mass quality evaluation index.

[0109] It should be noted that the explanation of the rock mass quality evaluation method based on microseismic monitoring of surrounding rock during TBM tunneling, as described above, also applies to the rock mass quality evaluation device based on microseismic monitoring of surrounding rock during TBM tunneling in this embodiment, and will not be repeated here.

[0110] The rock mass quality evaluation device based on micro-seismic monitoring of surrounding rock during TBM tunneling, as proposed in the embodiments of this application, can capture micro-fracture signals generated by stress disturbance or structural changes in the rock mass in real time during TBM tunneling, realize dynamic perception of the mechanical properties and structural stability of the surrounding rock, provide a real-time, continuous and accurate data foundation for rock mass quality evaluation, realize early identification and risk warning of potentially unstable areas, and improve the safety of tunneling construction.

[0111] Figure 7 A schematic diagram of the structure of an electronic device provided in an embodiment of this application. The electronic device may include:

[0112] The memory 701, the processor 702, and the computer program stored on the memory 701 and executable on the processor 702.

[0113] When the processor 702 executes the program, it implements the rock mass quality evaluation method based on microseismic monitoring of surrounding rock during TBM tunneling provided in the above embodiments.

[0114] Furthermore, electronic devices also include:

[0115] Communication interface 703 is used for communication between memory 701 and processor 702.

[0116] The memory 701 is used to store computer programs that can run on the processor 702.

[0117] The memory 701 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0118] If the memory 701, processor 702, and communication interface 703 are implemented independently, then the communication interface 703, memory 701, and processor 702 can be interconnected via a bus to complete communication between them. The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of representation, Figure 7 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0119] Optionally, in a specific implementation, if the memory 701, processor 702, and communication interface 703 are integrated on a single chip, then the memory 701, processor 702, and communication interface 703 can communicate with each other through an internal interface.

[0120] The processor 702 may be a central processing unit (CPU), an application specific integrated circuit (ASIC), or one or more integrated circuits configured to implement the embodiments of this application.

[0121] This embodiment also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the rock mass quality evaluation method based on microseismic monitoring of surrounding rock during TBM tunneling, as described above.

[0122] This application also provides a computer program product, including a computer program that can run computer instructions. When the computer instructions are executed by a processor, they implement the rock mass quality evaluation method based on microseismic monitoring of surrounding rock during TBM tunneling provided in this application.

[0123] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0124] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of that feature. In the description of this application, "N" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0125] Any process or method described in the flowchart or otherwise herein can be understood as representing a module, segment, or portion of code comprising one or N executable instructions for implementing custom logic functions or processes, and the scope of the preferred embodiments of this application includes additional implementations in which functions may be performed not in the order shown or discussed, including substantially simultaneously or in reverse order depending on the functions involved, as should be understood by those skilled in the art to which embodiments of this application pertain.

[0126] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (such as a computer-based system, a processor-included system, or other system that can fetch and execute instructions from, an instruction execution system, apparatus, or device). For the purposes of this specification, "computer-readable medium" can be any means that can contain, store, communicate, propagate, or transmit programs for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include: an electrical connection having one or more wires (electronic device), a portable computer disk drive (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and editable read-only memory (EPROM or flash memory), fiber optic devices, and portable optical disc read-only memory (CDROM). Alternatively, the computer-readable medium may be paper or other suitable media on which the program can be printed, since the program can be obtained electronically by optically scanning the paper or other medium, followed by editing, interpreting, or otherwise processing as necessary, and then stored in a computer memory.

[0127] It should be understood that the various parts of this application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, the N steps or methods can be implemented using software or firmware stored in memory and executed by a suitable instruction execution system. If implemented in hardware, as in another embodiment, it can be implemented using any one or more of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0128] Those skilled in the art will understand that all or part of the steps of the methods in the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, the program includes one or a combination of the steps of the method embodiments.

[0129] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium.

[0130] The storage medium mentioned above can be a read-only memory, a disk, or an optical disk, etc. Although embodiments of this application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting this application. Those skilled in the art can make changes, modifications, substitutions, and variations to the above embodiments within the scope of this application.

Claims

1. A rock mass quality evaluation method based on microseismic monitoring of surrounding rock during TBM tunneling, characterized in that, Includes the following steps: Collect microseismic signals generated by rock fracturing during full-face tunnel boring machine (TBM) excavation; The micro-vibration signal is processed to obtain a mechanical wave signal that meets preset conditions; At least one rock mass wave velocity parameter is extracted based on the mechanical wave signal, and rock strength and rock mass integrity information are analyzed based on the at least one rock mass wave velocity parameter. Rock mass quality evaluation index is generated based on the rock strength and rock mass integrity information, and rock mass quality is graded and evaluated. The step of extracting at least one rock mass wave velocity parameter based on the mechanical wave signal includes: The propagation time and path of the microseismic signal are analyzed based on the mechanical wave signal. The rock mass wave velocity of the at least one rock mass wave velocity parameter is calculated based on the propagation time and the propagation path; The formula for calculating the wave velocity of the rock mass is: ， ， in, The equivalent average P-wave velocity of the rock mass in the monitoring section; L The length of the monitoring segment; t This refers to the time it takes for the signal to propagate within the monitoring segment; i The number of segments with different wave velocities within the monitoring range; For the monitoring section within the first i The length of the segment; For the monitoring segment range mentioned above i The actual average wave velocity of the segment; The step of generating rock mass quality evaluation indicators based on the rock strength and rock mass integrity information, and classifying and evaluating the rock mass quality, includes: Calculate the rock mass quality evaluation index based on the rock strength and rock mass integrity information; Based on the rock mass quality evaluation indicators, the rock mass quality level is matched, and the rock mass quality is graded and evaluated. Rock mass quality is classified according to the index BQ, based on the quantitative indicators of the classification factors. and Calculate the BQ value: ， ， ， Among them, BQ is the rock mass quality evaluation index. The saturated uniaxial compressive strength of the rock. The integrity coefficient, Equivalent average P-wave velocity in rock mass The P-wave velocity of the rock block was obtained from indoor testing.

2. The method according to claim 1, characterized in that, The process of processing the micro-vibration signal to obtain a mechanical wave signal that meets preset conditions includes: The microseismic signal is subjected to wavelet processing and local gain amplification to obtain the processed microseismic signal; Based on the processed microseismic signal, the arrival time information of the P-wave is extracted to generate the mechanical wave signal under the preset conditions.

3. A rock mass quality evaluation device based on microseismic monitoring of surrounding rock during TBM tunneling, characterized in that, include: The acquisition module is used to acquire microseismic signals generated by rock fracturing during the excavation of a full-face tunnel boring machine (TBM). The processing module is used to process the micro-vibration signal to obtain a mechanical wave signal that meets preset conditions; The evaluation module is used to extract at least one rock mass wave velocity parameter based on the mechanical wave signal, analyze rock strength and rock mass integrity information based on the at least one rock mass wave velocity parameter, generate rock mass quality evaluation index based on the rock strength and rock mass integrity information, and classify and evaluate the rock mass quality. The step of extracting at least one rock mass wave velocity parameter based on the mechanical wave signal includes: The propagation time and path of the microseismic signal are analyzed based on the mechanical wave signal. The rock mass wave velocity of the at least one rock mass wave velocity parameter is calculated based on the propagation time and the propagation path; The formula for calculating the wave velocity of the rock mass is: ， ， in, The equivalent average P-wave velocity of the rock mass in the monitoring section; L The length of the monitoring segment; t This refers to the time it takes for the signal to propagate within the monitoring segment; i The number of segments with different wave velocities within the monitoring range; For the monitoring section within the first i The length of the segment; For the monitoring segment range mentioned above i The actual average wave velocity of the segment; The step of generating rock mass quality evaluation indicators based on the rock strength and rock mass integrity information, and classifying and evaluating the rock mass quality, includes: Calculate the rock mass quality evaluation index based on the rock strength and rock mass integrity information; Based on the rock mass quality evaluation indicators, the rock mass quality level is matched, and the rock mass quality is graded and evaluated. Rock mass quality is classified according to the index BQ, based on the quantitative indicators of the classification factors. and Calculate the BQ value: ， ， ， Among them, BQ is the rock mass quality evaluation index. The saturated uniaxial compressive strength of the rock. The integrity coefficient, Equivalent average P-wave velocity in rock mass The P-wave velocity of the rock block was obtained from indoor testing.

4. The apparatus according to claim 3, characterized in that, The processing module includes: The processing unit is used to perform wavelet processing and local gain amplification processing on the microseismic signal to obtain the processed microseismic signal. The generation unit is used to extract the arrival time information of the P-wave based on the processed microseismic signal in order to generate the mechanical wave signal under the preset conditions.

5. An electronic device, characterized in that, include: The system includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the rock mass quality evaluation method based on microseismic monitoring of surrounding rock during TBM tunneling as described in any one of claims 1-2.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that, The program is executed by the processor to implement the rock mass quality evaluation method based on microseismic monitoring of surrounding rock during TBM tunneling as described in any one of claims 1-2.

7. A computer program product, comprising a computer program, characterized in that, The computer program is executed to implement the rock mass quality evaluation method based on microseismic monitoring of surrounding rock during TBM tunneling, as described in any one of claims 1-2.

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