Tunnel rock mass damage prediction method and system based on microseismic data

Abstract

The application provides a tunnel rock mass damage prediction method and system based on microseismic data, and relates to the technical field of tunnel engineering safety monitoring. The method comprises the following steps: collecting microseismic monitoring data in the tunnel construction process; performing data preprocessing on the microseismic monitoring data to obtain normalized microseismic data sequences; extracting microseismic characteristic parameters related to rock mass damage based on the normalized microseismic data sequences; performing multi-parameter fusion analysis on the microseismic characteristic parameters, forming a comprehensive damage index based on a preset analysis rule set; determining three core monitoring positions in the monitoring area based on the spatial distribution characteristics of the comprehensive damage index, wherein the three core monitoring positions are respectively a current construction working face central area, a vault stress concentration area and a side wall stability key area; and constructing a spatial analysis unit for representing the rock mass damage evolution trend based on the three core monitoring positions. The application can improve the damage evaluation accuracy and the construction guidance practicability.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of tunnel engineering safety monitoring, in particular to a tunnel rock mass damage prediction method and system based on microseismic data. BACKGROUND

[0002] With the advancement of various scale development projects in the country, especially the continuous expansion of the scale of deep-buried high-stress tunnel construction, rock burst, collapse and other disasters induced by rock mass damage have become a core threat to construction safety.

[0003] However, in the face of various construction safety threats, the existing technology generally has many shortcomings: first, the data processing accuracy is insufficient, the mechanical noise and microseismic signals are intertwined in the TBM construction scene, the effective signal ratio is often less than 1 / 3, and the signal distortion caused by the difference in propagation path has not been effectively corrected; second, the feature analysis dimension is single, for example, it depends on the event frequency, energy and other isolated parameters, and does not form a comprehensive evaluation index that integrates time-frequency domain features, making it difficult to reflect the damage nature characteristics; in addition, the spatial analysis lacks systematization, for example, the traditional method does not establish a special monitoring unit for key areas such as the tunnel face and the arch top, and ignores the influence of spatial variation on damage assessment, resulting in low early warning accuracy; moreover, the decision-making is not coherent, the monitoring results are mostly qualitative descriptions, and cannot be directly converted into quantitative suggestions for support parameter adjustment and blasting scheme optimization.

[0004] These defects are particularly prominent under high-stress and complex geological conditions, and although some improvements have been made in existing technology, some practical technical defects such as damage correction mechanism blank, decision-making conversion fault and feature fusion analysis deficiency still exist. SUMMARY

[0005] The technical problem to be solved by the present application is to provide a tunnel rock mass damage prediction method and system based on microseismic data, which can realize real-time monitoring, grade determination, spatial visualization and construction decision guidance of rock mass damage during construction, and improve the damage assessment accuracy and construction guidance practicability.

[0006] To solve the above technical problems, the technical scheme of the present application is as follows:

[0007] In a first aspect, a tunnel rock mass damage prediction method based on microseismic data, the method comprising:

[0008] Collecting microseismic monitoring data during tunnel construction; pre-processing the microseismic monitoring data to obtain normalized microseismic data sequences;

[0009] Based on the normalized microseismic data sequence, microseismic characteristic parameters related to rock mass damage are extracted; multi-parameter fusion analysis is performed on the microseismic characteristic parameters, and based on a preset analysis rule set, a comprehensive damage index is formed;

[0010] Based on the spatial distribution characteristics of the comprehensive damage index, three core monitoring positions are determined in the monitoring area, and the three core monitoring positions are respectively the center area of the current construction face, the stress concentration area of the vault, and the key area of the side wall stability; based on the three core monitoring positions, a spatial analysis unit for representing the evolution trend of rock mass damage is constructed;

[0011] Based on the spatial analysis unit, a minimum circumscribed triangle is constructed to establish a quantitative description of the stability of the rock mass structure, that is, the structural morphology parameters of the minimum circumscribed triangle are calculated to obtain the side length ratio and the internal angle distribution characteristics; based on the structural morphology parameters, a spatial variation correction coefficient is formed, and the comprehensive damage index is corrected according to the spatial variation correction coefficient to obtain an optimized comprehensive damage index;

[0012] The optimized comprehensive damage index is compared with a preset damage threshold interval; and the damage degree grade of the tunnel rock mass is determined according to the comparison result;

[0013] Based on the determined damage degree grade, a tunnel rock mass damage spatial distribution map is formed;

[0014] According to the damage degree grade and the tunnel rock mass damage spatial distribution map, a decision suggestion for guiding the adjustment of the tunnel support parameters and the optimization of the blasting scheme is obtained.

[0015] Further, microseismic monitoring data in the tunnel construction process is collected; data preprocessing is performed on the microseismic monitoring data to obtain a normalized microseismic data sequence, including:

[0016] Through the microseismic sensor array arranged in the tunnel surrounding rock, the microseismic event waveform signals induced by construction disturbance are continuously collected;

[0017] The collected microseismic event waveform signals are subjected to noise reduction processing to filter out environmental noise interference generated by construction machinery vibration to obtain noise-reduced waveform signals;

[0018] Based on a preset amplitude threshold, effective microseismic signal segments are identified and extracted from the noise-reduced waveform signals;

[0019] The extracted microseismic signal segments are subjected to time domain normalization processing to eliminate signal intensity deviation caused by differences in propagation paths to obtain normalized microseismic signal segments;

[0020] The normalized microseismic signal segments are reorganized and arranged in time sequence to form a normalized microseismic data sequence.

[0021] Further, based on the normalized microseismic data sequence, microseismic characteristic parameters related to rock mass damage are extracted; multi-parameter fusion analysis is performed on the microseismic characteristic parameters, and based on a preset analysis rule set, a comprehensive damage index is formed, including:

[0022] Based on the normalized microseismic data sequence, the time-frequency domain characteristic parameters of each microseismic event are calculated;

[0023] Key characteristic parameters related to rock mass damage are extracted from the time-frequency domain characteristic parameters, including event energy, main frequency characteristics and duration;

[0024] Multi-parameter weighted fusion processing is performed on the key characteristic parameters to obtain a preliminary damage evaluation value;

[0025] Spatial clustering analysis is performed on the preliminary damage evaluation value, and based on a preset analysis rule set, a damage concentrated area is identified;

[0026] According to the distribution characteristics of the identified damage concentrated area, a comprehensive damage index is calculated.

[0027] Further, based on the spatial distribution characteristics of the comprehensive damage index, three core monitoring positions are determined in the monitoring area, and the three core monitoring positions are respectively the current construction center area, the arch stress concentration area and the key area of the side wall stability; based on the three core monitoring positions, a spatial analysis unit for representing the evolution trend of rock mass damage is constructed, including:

[0028] Based on the spatial distribution characteristics of the comprehensive damage index, a key area of damage concentration distribution is identified;

[0029] According to the distribution characteristics of the key area of damage concentration distribution, three core monitoring positions are determined, and the three core monitoring positions respectively correspond to the current construction center area, the arch stress concentration area and the key area of the side wall stability;

[0030] Taking the three core monitoring positions as reference points, the perpendicular bisectors between adjacent reference points are calculated, and the monitoring area is divided into three non-overlapping spatial partitions;

[0031] Based on the three non-overlapping spatial partitions, the spatial influence range corresponding to the core monitoring positions is determined;

[0032] According to the geometric characteristics of the spatial influence range, a spatial analysis unit representing the evolution trend of rock mass damage is constructed.

[0033] Further, based on the spatial analysis unit, a minimum circumscribed triangle is constructed to establish a quantitative description of the stability of the rock mass structure, that is, the structural morphology parameters of the minimum circumscribed triangle are calculated to obtain the edge length ratio and the internal angle distribution characteristics; based on the structural morphology parameters, a spatial variation correction coefficient is formed, and the spatial feature correction is performed on the comprehensive damage index according to the spatial variation correction coefficient to obtain an optimized comprehensive damage index, including:

[0034] Based on the spatial influence range of the spatial analysis unit, the peripheral boundary points of the spatial distribution of rock mass damage are determined;

[0035] By connecting the outermost boundary points, a minimum enclosing region is constructed to form a minimum circumscribed triangle of the spatial distribution of rock mass damage;

[0036] The structural morphology parameters of the minimum circumscribed triangle are calculated, including the length ratio of each edge, the internal angle distribution, and the area-perimeter ratio;

[0037] Based on the structural morphology parameters, a spatial variation correction coefficient is obtained by multi-parameter fusion calculation;

[0038] Based on the spatial variation correction coefficient, the spatial distribution characteristics of the comprehensive damage index are calibrated to obtain an optimized comprehensive damage index.

[0039] Further, the optimized comprehensive damage index is compared with the preset damage threshold interval; according to the comparison result, the damage degree grade of the tunnel rock mass is determined, including:

[0040] The optimized comprehensive damage index is compared and analyzed with the preset multi-level damage threshold interval to obtain a comparison and analysis value;

[0041] Based on the comparison and analysis value, a preliminary grade determination of rock mass damage is determined;

[0042] The preliminary grade determination is verified for spatial consistency, and the spatial consistency verification result data is obtained in combination with the geometric feature parameters of the spatial analysis unit;

[0043] According to the spatial consistency verification result data, a final tunnel rock mass damage degree grade and its confidence evaluation are formed.

[0044] Further, based on the determined damage degree grade, a tunnel rock mass damage spatial distribution map is formed, including:

[0045] Based on the damage degree grade and its confidence evaluation, a mapping relationship between the damage grade and the spatial coordinates is established;

[0046] According to the geometric feature parameters of the spatial analysis unit, spatial interpolation calculation is performed on the mapping relationship to obtain a continuous rock mass damage spatial distribution surface;

[0047] Based on the rock mass damage spatial distribution surface, a tunnel rock mass damage spatial distribution map containing multi-level damage marks is constructed.

[0048] The damage level and confidence information of the key monitoring position in the tunnel rock mass damage spatial distribution map are marked.

[0049] Further, according to the damage degree level and the tunnel rock mass damage spatial distribution map, a decision suggestion for guiding the adjustment of tunnel support parameters and the optimization of blasting scheme is obtained, including:

[0050] Based on the damage degree level and the spatial distribution characteristics, the rock mass damage area that needs to be treated is identified;

[0051] According to the distribution range and damage degree of the identified rock mass damage area, a corresponding support parameter adjustment scheme is formed;

[0052] Based on the distribution characteristics of the rock mass damage area, the key control area of the blasting scheme optimization is determined by combining the tunnel rock mass damage spatial distribution map;

[0053] The support parameter adjustment scheme and the key control area of the blasting scheme optimization are integrated, and the decision suggestion containing the support priority and the blasting control points is obtained by combining the confidence evaluation of the damage degree level.

[0054] In the second aspect, the tunnel rock mass damage prediction system based on microseismic data includes:

[0055] The acquisition module is used to collect microseismic monitoring data in the tunnel construction process; the microseismic monitoring data is preprocessed to obtain normalized microseismic data sequence;

[0056] The analysis module is used to extract microseismic characteristic parameters related to rock mass damage based on the normalized microseismic data sequence; the microseismic characteristic parameters are analyzed by multi-parameter fusion, and the comprehensive damage index is formed based on the preset analysis rule set;

[0057] The setting module is used to determine three core monitoring positions in the monitoring area based on the spatial distribution characteristics of the comprehensive damage index, and the three core monitoring positions are the current construction center area, the vault stress concentration area and the side wall stability key area respectively; the spatial analysis unit for representing the rock mass damage evolution trend is constructed based on the three core monitoring positions;

[0058] The construction module is used to construct the minimum circumscribed triangle based on the spatial analysis unit to establish the quantitative description of the rock mass structure stability, that is, to calculate the structure shape parameters of the minimum circumscribed triangle to obtain the side length ratio and the internal angle distribution characteristics; the spatial variation correction coefficient is formed based on the structure shape parameters, and the spatial characteristic correction of the comprehensive damage index is performed according to the spatial variation correction coefficient to obtain the optimized comprehensive damage index;

[0059] a comparison module configured to compare the optimized comprehensive damage index with a preset damage threshold interval, and determine a damage degree level of the tunnel rock mass according to a comparison result;

[0060] a summary module configured to form a tunnel rock mass damage spatial distribution map based on the determined damage degree level, and obtain a decision suggestion for guiding adjustment of a tunnel support parameter and optimization of a blasting scheme according to the damage degree level and the tunnel rock mass damage spatial distribution map.

[0061] In a third aspect, a computing device includes:

[0062] one or more processors;

[0063] a storage device configured to store one or more programs, when the one or more programs are executed by the one or more processors, the one or more processors are caused to implement the method.

[0064] In a fourth aspect, a computer readable storage medium has stored therein a program, which, when executed by a processor, implements the method.

[0065] The above scheme of the present application at least has the following beneficial effects:

[0066] Because the microseismic data preprocessing means of noise reduction processing plus time domain normalization is adopted, the problems of large mechanical noise interference, low effective signal ratio and signal distortion caused by transmission path difference in the construction scene of the prior art are overcome, and the effectiveness and standardization of the microseismic data are improved; Because the means of time-frequency domain key feature parameters such as event energy, main frequency feature, duration, weighted fusion and spatial clustering analysis are adopted to construct a comprehensive damage index, the problems of single feature analysis dimension, dependence on isolated parameters and inability to reflect the essence of damage in the traditional technology are overcome, and the core evaluation basis that can accurately represent the overall damage state of the rock mass is obtained; Because the spatial analysis unit is constructed based on the three core monitoring positions of the center of the working face, the stress concentration area of the arch top and the key area of the side wall stability, and the spatial variation correction coefficient is formed by combining the minimum circumscribed triangle structure shape parameters, the problems of lack of systematicness in spatial analysis, key area monitoring blind area and damage correction mechanism blank in the prior art are overcome, and the spatial accurate positioning and evaluation optimization of rock mass damage are realized; Because the damage grade is determined by adopting multi-level damage threshold comparison plus spatial consistency verification, the damage spatial distribution map containing confidence annotation is constructed, and the means of outputting quantitative support parameters and blasting scheme suggestions combined with damage characteristics are adopted, the problems of qualitative description of traditional monitoring results, poor decision coherence and decision conversion fault are overcome, and the visual presentation of rock mass damage and the direct guidance of construction decision are realized, the accuracy of tunnel rock mass damage prediction and the practicality of construction guidance are improved as a whole, and the occurrence risk of construction disasters such as rock burst and collapse is effectively reduced. BRIEF DESCRIPTION OF DRAWINGS

[0067] Figure 1 is a flowchart of the tunnel rock mass damage prediction method based on microseismic data provided by the embodiments of the present application.

[0068] Figure 2 is a schematic diagram of the tunnel rock mass damage prediction system based on microseismic data provided by the embodiments of the present application. DETAILED DESCRIPTION

[0069] Exemplary embodiments of the present disclosure will be described in greater detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided so that the present disclosure can be more thoroughly understood and the scope of the present disclosure can be accurately conveyed to those skilled in the art.

[0070] As Figure 1 shown, the embodiments of the present application propose a tunnel rock mass damage prediction method based on microseismic data, which comprises the following steps:

[0071] Step 1, collecting microseismic monitoring data in the tunnel construction process; performing data preprocessing on the microseismic monitoring data to obtain normalized microseismic data sequences;

[0072] Step 2, based on the normalized microseismic data sequences, extracting microseismic characteristic parameters related to rock mass damage; performing multi-parameter fusion analysis on the microseismic characteristic parameters, and forming a comprehensive damage index based on a pre-set analysis rule set;

[0073] Step 3, based on the spatial distribution characteristics of the comprehensive damage index, determining three core monitoring positions in the monitoring area, the three core monitoring positions being the current construction center area, the arch stress concentration area and the key area of the side wall stability respectively; based on the three core monitoring positions, constructing a spatial analysis unit for representing the rock mass damage evolution trend;

[0074] Step 4, based on the spatial analysis unit, constructing a minimum circumscribed triangle to establish a quantitative description of the rock mass structure stability, i.e. calculating the structure shape parameters of the minimum circumscribed triangle to obtain the side length ratio and the internal angle distribution characteristics; based on the structure shape parameters, forming a spatial variation correction coefficient, and correcting the comprehensive damage index according to the spatial variation correction coefficient to obtain an optimized comprehensive damage index;

[0075] Step 5, comparing the optimized comprehensive damage index with a pre-set damage threshold interval; determining the damage degree grade of the tunnel rock mass according to the comparison result;

[0076] Step 6, based on the determined damage degree grade, forming a tunnel rock mass damage spatial distribution map;

[0077] Step 7, according to the damage degree grade and the tunnel rock mass damage spatial distribution map, obtaining a decision suggestion for guiding the adjustment of the tunnel support parameters and the optimization of the blasting scheme.

[0078] In the embodiment of the present application, by collecting and preprocessing the tunnel construction microseismic monitoring data, mechanical noise can be filtered out, signal propagation bias can be eliminated, and standardized microseismic data sequence can be obtained; based on the sequence, rock mass damage related microseismic characteristic parameters are extracted and multi-parameter fusion analysis is carried out, which can avoid the limitations of single parameter evaluation, form a comprehensive damage index that accurately reflects the rock mass damage state according to the preset rules; combined with the spatial distribution of the comprehensive damage index, three core monitoring positions are determined, and a spatial analysis unit is constructed, which can cover the key areas prone to problems in the tunnel and effectively represent the rock mass damage evolution trend; based on the spatial analysis unit, a minimum circumscribed triangle is constructed, and a structure form parameter is calculated to form a spatial variation correction coefficient, which can correct the influence of spatial differences on damage evaluation, and obtain an optimized comprehensive damage index; comparing the optimized index with the preset damage threshold can determine the damage grade, which can clearly determine the rock mass damage degree; based on the damage grade, a damage spatial distribution map can be formed, which can intuitively present the spatial distribution of damage; combined with the damage grade and the distribution map, decision suggestions for support parameter adjustment and blasting scheme optimization can be given, which can directly guide the on-site construction and help to ensure the safety of tunnel construction.

[0079] In a preferred embodiment of the present application, step 1 can include:

[0080] Step 1.1, continuously collecting the microseismic event waveform signals induced by construction disturbance through the microseismic sensor array arranged in the tunnel surrounding rock, specifically including: first, according to the cross-sectional size of the tunnel and the influence range of construction disturbance, arranging the microseismic sensor array in the tunnel surrounding rock at an interval of 3-5 meters in the ring direction and a depth of 2-4 meters in the radial direction, to ensure that the sensor can cover the current construction face and the surrounding rock area within a certain distance behind the face, then starting the sensor array to continuously collect the microseismic event waveform signals generated by the rock mass due to microfracture during construction at a frequency of not less than 1000 sampling points per second. These continuously collected original waveform signals record the rock mass activity information induced by construction disturbance.

[0081] Step 1.2, noise reduction processing of the collected microseismic event waveform signals to filter out the environmental noise interference caused by construction machinery vibration and obtain the noise-reduced waveform signals, specifically including: for the microseismic event waveform signals collected containing TBM tunneling, blasting vibration and other construction machinery noise, processing by using the adaptive wavelet threshold noise reduction method, i.e. first decomposing the original waveform signal into a preset number of wavelet coefficients, such as 8 layers of wavelet coefficients, then dynamically adjusting the threshold value according to the noise energy distribution of each layer of wavelet coefficients, zero processing the wavelet coefficients smaller than the threshold value, and retaining the wavelet coefficients that can reflect the characteristics of the microseismic signal, then through inverse wavelet transform, the processed wavelet coefficients are reconstructed into complete waveform to obtain the noise-reduced waveform signals. This step effectively filters out the interference of environmental noise on the microseismic signal, making the characteristics of the microseismic signal clearer.

[0082] Step 1.3, based on the preset amplitude threshold, identify and extract the effective microseismic signal segment from the denoised waveform signal, specifically including: based on the denoised waveform signal, first collect the effective microseismic signal data under the same geological conditions of the tunnel in the past half year, analyze the maximum and minimum amplitude of these effective signals, determine the lower limit of the amplitude threshold as 80% of the minimum amplitude of the effective signal, and the upper limit is not limited, then use a sliding time window to scan the denoised waveform signal segment by segment, the window length is set to 1.5 times the typical duration of the microseismic event, when the amplitude of the signal in the window exceeds the set amplitude threshold, the signal segment corresponding to the window is marked as a candidate effective segment, then by comparing the similarity of the signal waveform of the candidate segment with the historical effective microseismic signal waveform, the interference segment with inconsistent waveform characteristics is removed, and finally the effective microseismic signal segment is extracted.

[0083] Step 1.4, time domain normalization processing is performed on the extracted microseismic signal segment to eliminate signal intensity deviation caused by different propagation paths, and normalized microseismic signal segment is obtained, specifically including: considering that the extracted effective microseismic signal segment may have intensity deviation due to different propagation paths, first prepare a standard microseismic source with known energy, fix it in the surrounding rock drill hole at a set distance behind the tunnel face, the drill hole depth is consistent with the sensor deployment depth, and at the same time, all sensors simultaneously collect signals; after removing abnormal sampling points, calculate the average signal intensity of each collection as the standard signal intensity of the corresponding sensor; then determine the attenuation coefficient, select the sensor closest to the standard source as the reference, record its distance and standard intensity; record the distances and standard intensities of other sensors, for each non-reference sensor, divide the reference intensity by the sensor intensity, and then divide by the ratio of the reference distance to the sensor distance, to obtain the respective attenuation coefficient, and take the average as the unified attenuation coefficient of the tunnel surrounding rock; for each effective microseismic signal segment, calculate the straight-line distance from the event occurrence position to each receiving sensor by combining the time difference of the received signal; according to the reference distance, reference intensity and attenuation coefficient, calculate the theoretical signal intensity at this distance, which is the theoretical correction value; finally, calculate the ratio of the theoretical correction value to the actual intensity to obtain the intensity correction coefficient, multiply the intensity of each sampling point of the signal by this coefficient, so that the signal intensities of different propagation paths are consistent, and the normalized microseismic signal segment is obtained.

[0084] Step 1.5, recombine the normalized microseismic signal segments according to the time sequence to form a normalized microseismic data sequence, specifically including: collecting all the normalized microseismic signal segments, first extracting the corresponding time stamp from the acquisition record of each segment, sorting all the segments in the order of time stamp from early to late, then connecting the sorted segments in turn to form a continuous signal sequence, while labeling the corresponding sensor number and spatial coordinates of the microseismic event every interval of a segment in the sequence, finally checking the integrity of the entire sequence, supplementing the time markers of the missing segments caused by temporary interruption, forming a normalized microseismic data sequence, which completely retains the time sequence and spatial information of the microseismic event, and the data format is unified.

[0085] In the embodiment of the present application, the microseismic event waveform signals induced by construction disturbance are continuously collected by the microseismic sensor array arranged in the tunnel surrounding rock, which can ensure that complete and continuous original microseismic data is obtained, providing a basis for data processing; the noise reduction processing of the collected waveform signals can effectively filter out the environmental noise interference caused by construction machinery vibration and reduce the interference of noise on microseismic signal analysis; the effective microseismic signal segments are extracted from the noise-reduced signals based on the preset amplitude threshold, which can accurately screen out useful signals related to rock mass damage and eliminate invalid signal components; the time domain normalization processing of the extracted effective signal segments can eliminate the signal intensity deviation caused by the difference in propagation path and ensure the comparability of microseismic signal intensity at different positions; finally, the normalized signal segments are recombined according to the time sequence to form a normalized microseismic data sequence, which makes the data structure unified and the logic clear, providing a data basis for extracting microseismic characteristic parameters and constructing comprehensive damage indicators.

[0086] In a preferred embodiment of the present application, the above step 2 can include:

[0087] Step 2.1, based on the normalized microseismic data sequence, calculate the time-frequency domain characteristic parameters of each microseismic event, specifically including: split each independent microseismic event signal from the normalized microseismic data sequence, for each microseismic event signal, calculate its peak amplitude, signal rise time and signal fall time in the time domain, wherein the signal rise time is the time length required for the signal to rise from 10% to 90% of the peak amplitude, and the signal fall time is the time length required for the signal to fall from 90% to 10% of the peak amplitude; in the frequency domain, convert the time domain signal to the frequency domain signal, calculate the power spectral density of the signal, and then obtain the main frequency range, frequency bandwidth and power value corresponding to the peak frequency of the signal, integrate these time domain calculation results and frequency domain calculation results to form the complete time-frequency domain characteristic parameters of each microseismic event.

[0088] Step 2.2, extracting key feature parameters related to rock mass damage from time-frequency domain feature parameters, including event energy, main frequency feature and duration, specifically including: collecting damage research data of similar rock mass in the area where the tunnel is located, combining the correlation records of rock mass damage degree and microseismic parameters in past projects, determining the parameter types closely related to rock mass damage, finding that event energy, main frequency feature and duration have the most obvious influence on damage assessment; among them, event energy is calculated by time integration of the amplitude of microseismic event signal, and the integration interval is the complete time period from the beginning to the end of the signal; the main frequency feature selects the frequency value corresponding to the maximum power spectral density in the frequency domain analysis as the main frequency, and records the proportion of the power corresponding to the main frequency to the total power; the duration is calculated by the time period when the signal amplitude exceeds the preset minimum effective amplitude threshold, starting from the first time the signal reaches the threshold to the last time the signal falls below the threshold, and the key feature parameters are extracted from the time-frequency domain feature parameters in this way.

[0089] Step 2.3, multi-parameter weighted fusion processing of key feature parameters to obtain preliminary damage assessment value, specifically including: scoring according to the influence degree of each key feature parameter on rock mass damage assessment, among them, event energy has the most direct reflection on damage scale, and has the highest weight score, main frequency feature is second, and duration has relatively low weight score, after averaging the expert scoring results, the weight coefficient of event energy is 0.5, the weight coefficient of main frequency feature is 0.3, and the weight coefficient of duration is 0.2; then standardize the key feature parameters of each microseismic event, convert each parameter value to the interval of 0 to 1; then multiply each standardized key feature parameter by the corresponding weight coefficient, and add the three product results to obtain the preliminary damage assessment value corresponding to each microseismic event.

[0090] Step 2.4, spatial clustering analysis of preliminary damage assessment value, identifying damage concentrated areas based on a preset analysis rule set, specifically including: obtaining the spatial coordinate information of each microseismic event in the tunnel, associating these spatial coordinates with the corresponding preliminary damage assessment values to form a data set containing location and assessment value; spatial clustering analysis of the data set, i.e. according to the actual range of the tunnel construction area and the past damage distribution law, setting the number of clusters to 5 to 8 to ensure that the possible damage area can be covered; during the clustering process, the spatial distance and the similarity of the preliminary damage assessment value are used as the clustering basis, and the microseismic events with similar spatial positions and small differences in assessment values are classified into the same class; then according to the preset analysis rule set, each cluster category is judged, if the average preliminary damage assessment value of a category exceeds the set damage warning threshold, and the number of microseismic events in the category exceeds 15% of the total number of events, the spatial area corresponding to the category is determined as a damage concentrated area, and in this way the key area of rock mass damage is effectively located.

[0091] Step 2.5, according to the distribution characteristics of the identified damage concentrated area, the comprehensive damage index is calculated, specifically including: statistics of the basic distribution characteristics of each damage concentrated area, including the spatial range area of the region, the number density of microseismic events in the region, that is, the number of microseismic events in the unit area, and the average value of the preliminary damage evaluation value of all microseismic events in the region; then according to these distribution characteristics, the comprehensive damage index is calculated, and when calculating, the area of the region, the number density and the average preliminary evaluation value are quantitatively converted according to the preset standard, so that the three are in the same numerical magnitude, then the converted area of the region is multiplied by 0.3, the number density is multiplied by 0.4, and the average preliminary evaluation value is multiplied by 0.3, finally the three product results are added to obtain the local damage contribution value corresponding to the damage concentrated area, the local damage contribution value of all damage concentrated areas is added to the basic damage value of the whole tunnel which does not form a damage concentrated area, and finally the comprehensive damage index reflecting the overall damage state of the tunnel rock mass is obtained.

[0092] In the embodiment of the application, the time-frequency domain characteristic parameters of each microseismic event are calculated based on the normalized microseismic data sequence, which can comprehensively capture the basic information related to rock mass damage in the microseismic signal; the key characteristic parameters such as event energy, main frequency feature and duration are extracted from the time-frequency domain characteristic parameters, which can focus on the core influencing factors of rock mass damage, eliminate the interference of irrelevant parameters, and make the characteristic analysis more suitable for damage assessment requirements; the preliminary damage evaluation value is obtained by performing multi-parameter weighted fusion processing on the key characteristic parameters, which can comprehensively consider the different influence degrees of various parameters on damage, avoid the one-sidedness of single parameter evaluation, and improve the rationality of the preliminary evaluation result; the spatial clustering analysis is performed on the preliminary damage evaluation value, and the damage concentrated area is identified based on the preset rule, which can accurately locate the key area of rock mass damage and solve the problem that the traditional global analysis cannot find local damage aggregation; finally, the comprehensive damage index is calculated according to the distribution characteristics of the damage concentrated area, which can integrate local damage information and overall distribution law, so that the index can comprehensively reflect the overall damage state of the tunnel rock mass, and provide reliable core basis for spatial analysis unit construction and damage grade judgment.

[0093] In a preferred embodiment of the application, the above-mentioned step 3 can include:

[0094] Step 3.1, based on the spatial distribution characteristics of the comprehensive damage index, identify the key areas where damage is concentrated, specifically including: first, associate the comprehensive damage index with the three-dimensional spatial coordinates of the tunnel to form a spatial distribution heat map of the comprehensive damage index. In the heat map, different colors are used to mark the high and low values of the index. Red areas represent areas with higher comprehensive damage index, and blue areas represent areas with lower index. Then set a threshold value for the comprehensive damage index, which is determined by reference to the index value when the rock mass experiences slight damage under the geological conditions of the tunnel. Mark the areas in the heat map where the index value exceeds this threshold as candidate areas. Then check the continuity of the candidate areas. If the area of a candidate area exceeds 5 square meters and there is no obvious fracture interval inside, then the area is determined as a key area where damage is concentrated.

[0095] Step 3.2, according to the distribution characteristics of the key areas where damage is concentrated, determine three core monitoring positions, which correspond to the current construction of the center area of the tunnel face, the stress concentration area of the vault, and the key area of the side wall stability, respectively. Specifically including: based on the identified key areas where damage is concentrated, first analyze the correspondence between each key area and the key parts of the tunnel construction. For key areas distributed near the current construction of the tunnel face, take the geometric center of the area as the core monitoring position of the center area of the current construction of the tunnel face. This position can directly reflect the real-time damage state of the rock mass of the tunnel face. For key areas distributed on the top of the tunnel, combined with the design axis of the tunnel vault, select the point in the area closest to the design axis of the vault and with the highest comprehensive damage index as the core monitoring position of the stress concentration area of the vault. This position can accurately capture the damage changes caused by the stress of the vault. For key areas distributed on the two side walls of the tunnel, according to the stability requirements of the side wall, select the point in the area along the height direction midpoint of the side wall and with a higher comprehensive damage index as the core monitoring position of the key area of the side wall stability. In this way, the three core monitoring positions are determined, covering the key parts of the tunnel where damage is prone to occur.

[0096] Step 3.3, based on three core monitoring positions, calculate the perpendicular bisector between adjacent reference points, and divide the monitoring area into three non-overlapping spatial partitions, specifically including: first mark three core monitoring positions in the three-dimensional coordinate of the tunnel, respectively marked as point A, namely the center area of the tunnel face, point B, namely the stress concentration area of the vault, and point C, namely the key area of the sidewall stability; first connect point A and point B, measure the length of AB line segment and find the midpoint, then draw a straight line through the midpoint which is perpendicular to AB line segment, this straight line is the perpendicular bisector of AB line segment; similarly, draw the perpendicular bisectors of BC line segment and AC line segment; the three perpendicular bisectors intersect in the monitoring area, dividing the entire monitoring area into three non-overlapping spatial partitions, respectively the partition with A as the core, the partition with B as the core and the partition with C as the core, this division method ensures that each partition corresponds to a core monitoring position, avoiding analysis interference caused by overlapping of monitoring areas.

[0097] Step 3.4, based on the three non-overlapping spatial partitions, determine the spatial influence range corresponding to the core monitoring position, specifically including: for the three non-overlapping spatial partitions divided, first select multiple sampling points in each partition, the sampling points are uniformly distributed in the corners of the partition, and the number of sampling points in each partition is not less than 20; measure the distance from each sampling point to the corresponding core monitoring position and record the comprehensive damage index value of the sampling point; by analyzing the change rule of the comprehensive damage index of the sampling points, when the comprehensive damage index value of a sampling point drops to 50% of the index value of the core monitoring position, the position of the sampling point is determined as the boundary point of the spatial influence range of the core monitoring position; connect all the boundary points in the same partition to form a closed area, which is the spatial influence range corresponding to the core monitoring position.

[0098] Step 3.5, according to the geometric characteristics of the spatial influence range, construct a spatial analysis unit representing the damage evolution trend of the rock mass, specifically including: extracting the geometric characteristics of the spatial influence range of the three core monitoring positions, including the shape of each influence range, such as circular, elliptical or irregular polygon, area size and boundary contour data; then combine the time variation data of the comprehensive damage index in each influence range, such as the maximum value, minimum value and change rate of the index in the past 24 hours, integrate these geometric characteristics and time variation data; establish an independent monitoring data record table for each spatial influence range, record the damage index data, geometric boundary change and index change trend in the influence range, and determine the independent monitoring unit containing geometric characteristics, real-time data and change trend as the spatial analysis unit representing the damage evolution trend of the rock mass.

[0099] In the embodiment of the present application, the key area of damage concentration is identified based on the spatial distribution characteristics of the comprehensive damage index, which can accurately lock the key range of rock mass damage; three core monitoring positions corresponding to the current construction center area of the working face, the stress concentration area of the vault and the key area of the side wall stability are determined according to the distribution characteristics of the key area, which can cover the key parts prone to damage in tunnel construction and make up for the defects of traditional methods that do not establish special monitoring units for key areas; taking the three core monitoring positions as reference points, the perpendicular bisector between adjacent reference points is calculated to divide three non-overlapping spatial partitions, which can avoid analysis confusion caused by overlapping monitoring areas and make the area division clearer and more orderly; the spatial influence range corresponding to each core monitoring position is determined based on the non-overlapping spatial partitions, which can clearly define the effective coverage area of each core position and provide boundary basis for accurate analysis of the damage state of different areas; the spatial analysis unit representing the evolution trend of rock mass damage is constructed according to the geometric characteristics of the spatial influence range, which can systematically integrate the damage information of the key area, form a structured analysis framework and solve the problem of lack of systematicness in traditional spatial analysis.

[0100] In a preferred embodiment of the present application, step 4 can include:

[0101] Step 4.1, based on the spatial influence range of the spatial analysis unit, determining the peripheral boundary points of the spatial distribution of rock mass damage, specifically including: retrieving the spatial influence range data of each spatial analysis unit, including the three-dimensional coordinate profile of the range and the distribution coordinates of all microseismic events inside; within the spatial influence range, uniformly arranging sampling points at a density of 1 sampling point per square meter, ensuring that the sampling points cover the entire profile and internal area of the influence range; calculating the straight-line distance from each sampling point to the geometric center of the spatial analysis unit, and determining whether the sampling point is on the edge of the influence range, i.e. there are no other sampling points within 0.5 meters around the sampling point; marking the sampling point farthest from the center and on the edge of the profile as a candidate boundary point, and then screening the candidate boundary points to remove redundant points with a mutual distance of less than 1 meter, finally determining 10-15 rock mass damage spatial distribution peripheral boundary points that can completely outline the peripheral profile of the damage area.

[0102] Step 4.2, the minimum circumscribed triangle of the rock mass damage spatial distribution is formed by connecting the outermost boundary points to construct the minimum enclosing region, specifically including: sorting the outer boundary points in the form of X, Y, Z three-dimensional coordinates, respectively extracting the boundary points with the maximum and minimum coordinate values along the tunnel axis direction, the horizontal direction perpendicular to the axis and the vertical direction, and preliminarily screening out 8-10 key boundary points most likely to constitute the outer contour; the minimum enclosing region is constructed by using point-by-point trial, three key boundary points are first randomly selected to form an initial triangle, the area of the triangle is calculated; then the other key boundary points are replaced with the vertices of the initial triangle, and the area of the new triangle is recalculated, and the triangle with the smallest area that can completely enclose all the outer boundary points is retained; repeat the replacement process until no smaller enclosing triangle can be found, and finally form the minimum circumscribed triangle of the rock mass damage spatial distribution, which can reflect the spatial range of the damage area in the most compact geometric form.

[0103] Step 4.3, calculate the structural morphology parameters of the minimum circumscribed triangle, including the length ratio of each side, the distribution of internal angle, and the area to perimeter ratio, specifically including: obtaining the coordinates of the three vertices of the minimum circumscribed triangle, calculating the actual lengths of the three sides of the triangle, sorting the three sides by length from large to small, calculating the ratio of the longest side to the shortest side and the ratio of the longest side to the medium length side to obtain the length ratio of each side; then according to the cosine law, the length of the three sides is used to calculate the degree of the three internal angles of the triangle, and the specific value of each internal angle and whether it is in the reasonable interval of 60° to 120° are recorded to form the internal angle number distribution data; finally, the area of the triangle is calculated, the perimeter is obtained by adding the lengths of the three sides, and the area to perimeter ratio is obtained by dividing the area by the perimeter. In this way, the structural morphology parameters of the minimum circumscribed triangle are completely calculated.

[0104] Step 4.4, based on the structural morphology parameters, the spatial variation correction coefficient is obtained by performing multi-parameter fusion calculation, specifically including: combining the geological conditions of tunnel engineering and the past damage assessment experience, the influence weight of each structural morphology parameter on spatial variation is determined: the side length ratio reflects the uniformity of damage distribution, the weight is set to 0.3; the internal angle number distribution reflects the regularity of damage region morphology, the weight is set to 0.4; the area perimeter ratio reflects the compactness of the damage region, the weight is set to 0.3; then each structural morphology parameter is standardized, the parameter value is converted to the interval of 0 to 1, for example, the closer the side length ratio is to 1, the more uniform the distribution is, and the closer the standardized value is to 1; the closer the internal angle number is to 90°, the more regular the morphology is, and the closer the standardized value is to 1; the larger the area perimeter ratio is, the more compact the region is, and the closer the standardized value is to 1; the standardized parameters are multiplied by the corresponding weights, and the three product results are added to obtain the spatial variation correction coefficient corresponding to each spatial analysis unit, which can quantitatively reflect the influence degree of spatial variation on damage assessment.

[0105] Step 4.5, based on the spatial variation correction coefficient, the spatial distribution characteristics of the comprehensive damage index are calibrated to obtain the optimized comprehensive damage index, specifically including: obtaining the original comprehensive damage index value of each spatial analysis unit and the spatial variation correction coefficient corresponding to the unit; judging the size relationship between the correction coefficient and 1: if the correction coefficient is greater than 1, it means that the original comprehensive damage index may underestimate the actual damage degree due to the irregularity of damage region morphology, uneven distribution and other spatial variation factors; if the correction coefficient is less than 1, it means that the original index may overestimate the actual damage degree; the original comprehensive damage index value is multiplied by the corresponding spatial variation correction coefficient to obtain the calibrated damage index value; the calibrated value is checked for reasonableness, if the value exceeds the reasonable range of rock mass damage under the geological conditions, the reasonable range is set according to the past engineering data, then the value of the correction coefficient is adjusted appropriately until the calibrated value is in the reasonable interval, and finally the optimized comprehensive damage index of each spatial analysis unit is obtained, which eliminates the evaluation deviation caused by spatial variation and is more consistent with the actual damage state of rock mass.

[0106] In the embodiment of the present application, the peripheral boundary points of the rock mass damage spatial distribution are determined based on the spatial influence range of the spatial analysis unit, which can accurately lock the peripheral contour of the damage area, avoid deviation in analysis caused by ambiguous boundaries, and provide clear and accurate basic points for constructing the minimum enclosing region; by connecting the outermost boundary points to form the minimum circumscribed triangle of the rock mass damage spatial distribution, the dispersed damage area can be converted into a regular geometric shape, making the originally difficult-to-quantify damage spatial distribution easy to analyze and providing an intuitive geometric carrier for evaluating the stability of the rock mass structure; calculating the length proportion relationship of each side of the minimum circumscribed triangle, the internal angle distribution, and the area-perimeter ratio and other structural morphology parameters can extract the spatial characteristic information of the damage area from the geometric dimension, accurately capture the spatial variation differences of different areas, and provide specific data support for quantifying the influence of spatial variation on damage evaluation; based on these structural morphology parameters, the spatial variation correction coefficient is calculated through multi-parameter fusion, which fills the gap in the damage correction mechanism in the traditional technology, can quantitatively evaluate the evaluation error caused by spatial variation, and solves the problem of ignoring the influence of spatial variation in the traditional method; finally, the spatial distribution characteristic of the comprehensive damage index is calibrated by the spatial variation correction coefficient, which can effectively eliminate the index deviation caused by spatial variation and obtain the optimized comprehensive damage index that is more in line with the actual rock mass damage state.

[0107] In a preferred embodiment of the present application, step 5 can include:

[0108] Step 5.1, compare and analyze the optimized comprehensive damage index with the preset multi-level damage threshold interval to obtain a comparison and analysis value, specifically including: combining the rock mass mechanical parameters of the area where the tunnel is located, the damage case data of similar tunnel projects, and the results of indoor rock mass damage simulation experiments, presetting three-level damage threshold intervals: the mild damage interval is 0.2 to 0.4, the moderate damage interval is 0.4 to 0.6, and the severe damage interval is 0.6 to 0.8; for the optimized comprehensive damage index of each spatial analysis unit, compare its value with the three threshold intervals one by one to determine which interval the index value falls into, and calculate the distance between the index value and the upper and lower boundaries of the interval, for example, if the index value is 0.5, it falls in the moderate damage interval, the distance to the lower boundary 0.4 is 0.1, and the distance to the upper boundary 0.6 is 0.1, and the combination of the interval and the distance to the boundary is taken as the comparison and analysis value of the spatial analysis unit.

[0109] Step 5.2, based on the comparison analysis value, determine the preliminary grade determination of rock mass damage, specifically including: based on the comparison analysis value, establish the corresponding rules of comparison analysis value and damage grade: if the comparison analysis value shows that the index falls in the mild damage interval, it is preliminarily determined that the rock mass damage grade of the spatial analysis unit is mild damage; if it falls in the moderate damage interval, it is preliminarily determined as moderate damage; if it falls in the severe damage interval, it is preliminarily determined as severe damage; at the same time, the cases where the index value is close to the interval boundary are marked, for example, the index value is 0.39, then 0.39 is close to the upper boundary 0.4 of the mild interval; or 0.61, then 0.61 is close to the lower boundary 0.6 of the severe interval, when the preliminary grade determination result is marked close to the adjacent grade, to ensure that the preliminary determination result is clear and can reflect the critical state of the value.

[0110] Step 5.3, verify the spatial consistency of the preliminary grade determination, combine the geometric characteristic parameters of the spatial analysis unit to obtain the spatial consistency verification result data, specifically including: calling the geometric characteristic parameters of each spatial analysis unit, including the spatial coordinate range of the unit, the boundary coincidence length with the adjacent unit and the unit area; for the preliminary grade determination result, check whether the preliminary grade of the adjacent spatial analysis unit is consistent or presents reasonable transition, for example, the adjacent unit of the mild damage unit should be mild or moderate damage, if the mild damage unit is adjacent to the severe damage unit, it is marked as grade abnormal; at the same time, the total area of the spatial analysis unit corresponding to each damage grade is calculated, the proportion of the total area of the monitoring area, if the area of a certain grade unit accounts for more than 60%, but there are individual adjacent units with large grade difference, it is also marked as spatial distribution abnormal; integrate the number of grade abnormal units, the boundary length of abnormal adjacent units and the area proportion data of each grade to form the spatial consistency verification result data.

[0111] Step 5.4, according to the spatial consistency verification result data, the final tunnel rock mass damage degree grade and its confidence evaluation are formed, specifically including: analyzing the spatial consistency verification result data, if the proportion of the number of abnormal units to the total number of units is less than 10%, it is considered that the spatial consistency of the preliminary grade determination is good, and the preliminary determination grade is directly used; if the proportion of abnormal units exceeds 10%, the optimized comprehensive damage index of the abnormal units is rechecked, combined with its geometric characteristic parameters, such as whether it is in the stress concentrated dome area, the grade is adjusted, for example, the abnormal units in the dome area, if the preliminary determination is slight damage but most of the adjacent units are moderate damage, it can be adjusted to moderate damage combined with the stress characteristics of the dome; then, the confidence of the final grade determination result is calculated, the confidence is calculated based on the proportion of the number of units passing the spatial consistency verification to the total number of units, for example, the proportion of the units passing the verification is 92%, the confidence is preliminarily set to 92%, and then the confidence is fine-tuned according to the number of adjusted units, the adjustment range is not more than 5%, and finally the tunnel rock mass damage degree grade of each spatial analysis unit and its corresponding confidence evaluation are formed, so that the damage grade result is more reliable.

[0112] In the embodiment of the application, the optimized comprehensive damage index is compared and analyzed with the preset multi-level damage threshold interval to obtain a comparison analysis value, which can avoid the ambiguity of qualitative description of traditional monitoring results through quantitative comparison, and provide clear numerical basis for damage grade determination; based on the comparison analysis value, the preliminary grade determination of rock mass damage is determined, which can quickly lock the approximate degree of rock mass damage; the spatial consistency verification is carried out on the preliminary grade determination combined with the geometric characteristic parameters of the spatial analysis unit, which can check the grade misjudgment caused by local spatial variation, solve the problem of low warning accuracy caused by ignoring spatial correlation in traditional method, and obtain more spatially reasonable verification result data; according to the spatial consistency verification result data, the final tunnel rock mass damage degree grade and its confidence evaluation are formed, which not only fills the blank of lack of result reliability quantization in traditional technology, but also makes the damage grade result more persuasive.

[0113] In a preferred embodiment of the application, step 6 can include:

[0114] Step 6.1, based on the damage degree level and its confidence evaluation, a mapping relationship between the damage level and the spatial coordinates is established, which specifically includes: calling the damage degree level of each spatial analysis unit, such as mild, moderate, severe, and its corresponding confidence evaluation value, and obtaining the geometric center coordinates of each spatial analysis unit, which is obtained by calculating the average value of all vertex coordinates of the unit boundary contour, including the X coordinate along the tunnel axis, the Y coordinate in the horizontal direction perpendicular to the axis, and the Z coordinate in the vertical direction; the geometric center coordinates of each spatial analysis unit are associated with the corresponding damage degree level and confidence value, for example, the coordinates (X1, Y1, Z1) correspond to mild damage with a confidence of 90%; the coordinates (X2, Y2, Z2) correspond to moderate damage with a confidence of 85%, forming an association table with spatial coordinates as index and damage information as content, and the mapping relationship between the damage level and the spatial coordinates is established in this way.

[0115] Step 6.2, according to the geometric characteristic parameters of the spatial analysis unit, the mapping relationship is calculated by spatial interpolation to obtain a continuous rock mass damage spatial distribution surface, which specifically includes: based on the mapping relationship between the damage level and the spatial coordinates, the range of spatial interpolation is first determined, which covers the entire tunnel monitoring area and extends 10 meters outside the monitoring area boundary to avoid interpolation distortion in the edge area; then the geometric characteristic parameters of each spatial analysis unit are called, including the area size and boundary coordinates of the unit, to determine the spatial distance and distribution density between different units, for areas with dense unit distribution, such as near the tunnel face, a smaller interpolation grid spacing is set, and for areas with sparse distribution, a larger grid spacing is set; the discrete data in the mapping relationship is calculated, with the damage level corresponding to the quantitative value of the adjacent spatial analysis unit, such as mild damage assigned a value of 1, moderate damage assigned a value of 2, and severe damage assigned a value of 3, and the confidence as the weight, by fitting the spatial variation trend of adjacent data points, the damage level quantitative value corresponding to each interpolation grid node is calculated, and all grid node quantitative values are connected to form a continuous rock mass damage spatial distribution surface, which fills the damage data gap between discrete analysis units and makes the damage distribution present a more complete spatial rule.

[0116] Step 6.3, based on the rock mass damage spatial distribution surface, a tunnel rock mass damage spatial distribution map containing multi-level damage marks is constructed, specifically including: based on the rock mass damage spatial distribution surface, a three-dimensional simplified template of the tunnel is established, the template contains the outlines of key structures such as the vault, sidewall and working face of the tunnel, and the coordinate system of the template is consistent with the coordinate system of the spatial analysis unit; according to the damage level, multi-level damage marks are set: the light damage area is filled with light green, the moderate damage area is filled with orange yellow, and the severe damage area is filled with dark red, and a legend is set in the graph to mark the damage level and the corresponding quantitative value range of each color; the continuous damage spatial distribution surface is superimposed on the template, so that the color filling of the surface is accurately matched with the template structure, and then coordinate scales and units are added to the graph to mark the starting mileage and key section position of the tunnel axis, and in this way, a tunnel rock mass damage spatial distribution map containing multi-level damage marks is constructed.

[0117] Step 6.4, mark the damage level and confidence information of the key monitoring positions in the tunnel rock mass damage spatial distribution map, specifically including: from the three core monitoring positions, the precise spatial coordinates of each position are extracted, and the corresponding positions of these coordinates are found in the tunnel rock mass damage spatial distribution map; for each core monitoring position, different special symbols are used for marking: the center area of the working face is marked with a black triangle, the stress concentration area of the vault is marked with a blue circle, and the key area of the sidewall stability is marked with a red square, the symbol size is set to 1.5 times the size of the legend, to ensure that it is eye-catching and easy to find in the graph; mark the damage level and confidence information corresponding to each special symbol, for example, mark the center of the working face with a black triangle, light damage, confidence 92%, mark the stress concentration area of the vault with a blue circle, moderate damage, confidence 88%, in this way, the construction personnel can quickly focus on the damage state and reliability of the key area.

[0118] In the embodiment of the present application, based on the damage degree level and its confidence evaluation, a mapping relationship between the damage level and the spatial coordinates is established, which can accurately associate the abstract damage level with the specific spatial position of the tunnel, and solve the problem that the traditional monitoring results lack clear spatial correspondence and are difficult to locate the damage position; according to the geometric characteristic parameters of the spatial analysis unit, the mapping relationship is calculated by spatial interpolation, which can fill in the damage data blank between different analysis units, convert the discrete damage information into a continuous rock mass damage spatial distribution surface, avoid the fragmentation of the damage distribution, and facilitate intuitive understanding of the overall damage trend of the tunnel; based on the surface, a tunnel rock mass damage spatial distribution map containing multiple damage levels is constructed, which can clearly distinguish the light, moderate and severe damage areas through different labels, and solve the defect that the traditional qualitative description cannot intuitively present the damage difference; in the distribution map, the damage level and confidence information of the key monitoring position are marked, which can quickly focus on the damage state and reliability of the key areas such as the center of the tunnel face and the stress concentration area of the vault, provide intuitive and accurate spatial reference for construction decision-making, and overall improve the visualization degree and practical value of the damage information.

[0119] In a preferred embodiment of the present application, step 7 can include:

[0120] Step 7.1, based on the damage degree level and its spatial distribution characteristics, identifying the rock mass damage area that needs to be treated as a key, specifically including: based on the tunnel rock mass damage spatial distribution map, combining the damage degree level of each area, setting the judgment standard of the key treatment area; for the severe damage area, no matter its position, it is included in the key treatment range; for the moderate damage area, if it is distributed in the stress concentration area of the vault, the key area of the side wall stability, and other weak parts of the tunnel structure, or the area exceeds 10 square meters, it is also included in the key treatment range; for the light damage area, only when it is adjacent to the severe damage area and the confidence evaluation exceeds 90%, it is included in the key treatment range; by circling the area meeting the above standard on the damage spatial distribution map, the boundary coordinates and area size of each key area are determined, and a list of rock mass damage areas that need to be treated as a key is formed.

[0121] Step 7.2, according to the distribution range and damage degree of the identified rock mass damage area, a corresponding support parameter adjustment scheme is formed, specifically including: based on the key treatment area, first, the damage degree grade and distribution range parameters of each area are counted, including the maximum radial depth of the area, the extension length along the tunnel axis, and the involved tunnel structure parts, such as the vault, the side wall or the working face; for the severely damaged area, if it is located at the vault, the length of the anchor rod in the original support scheme is increased by 0.5 meters, the anchor cable spacing is reduced to 1.5 meters, and the sprayed concrete thickness is increased by 5 centimeters; if it is located at the side wall, the anchor rod arrangement is densified, 2 anchor rods per square meter are added, and a grid arch is added; for the moderately damaged area, the parameters are adjusted according to the area size, when the area size exceeds 15 square meters, the length of the anchor rod is increased by 0.3 meters, and the sprayed concrete thickness is increased by 3 centimeters; the area with smaller size only appropriately reduces the anchor rod spacing; the parameter adjustment contents are associated with the position information of the corresponding area to form a regional support parameter adjustment scheme.

[0122] Step 7.3, based on the distribution characteristics of the rock mass damage area, by combining the tunnel rock mass damage spatial distribution map, the key control area of the blasting scheme optimization is determined, specifically including: superimposing the tunnel rock mass damage spatial distribution map and the tunnel blasting operation design range to determine the spatial position relationship between the blasting operation area and the rock mass damage area; for the blasting subarea with a distance less than 5 meters from the edge of the severely damaged area, it is marked as a first-level control area, which needs to strictly limit the blasting vibration velocity; for the blasting subarea with a distance of 3 to 5 meters from the edge of the moderately damaged area, it is marked as a second-level control area, which needs to appropriately reduce the blasting intensity; combined with the distribution characteristics of the damage area, if the damage area is continuously distributed along the tunnel axis, the blasting cycle footage of the corresponding section is shortened by 20%; if the damage area is concentrated on the left or right side of the working face, the charge structure of the holes on that side is adjusted to reduce the single-hole charge amount; in this way, the key control area of the blasting scheme optimization and its corresponding control requirements are clearly defined.

[0123] Step 7.4, the support parameter adjustment scheme and the key control area of the blasting scheme optimization are integrated, the confidence evaluation of the damage degree level is combined, the decision suggestion containing the support priority and the blasting control points is obtained, and the decision suggestion specifically includes: the support parameter adjustment scheme and the blasting key control area are spatially matched, if a certain area needs both support parameter adjustment and blasting control area, the support operation is arranged first and then the blasting optimization is performed; the confidence evaluation of the damage degree level is referred to, for the severe damage area with a confidence exceeding 90%, the support priority is set to the highest, and the support adjustment is required to be completed within 24 hours; for the moderate damage area with a confidence of 80% to 90%, the support priority is set to moderate, and the adjustment is completed within 48 hours; in terms of the blasting control points, the presplitting blasting technology is required to be used in the first-class control area, the single-response explosive quantity is not more than 50 kg, and the vibration speed is controlled to be less than 1.5 cm / s; the smooth blasting is used in the second-class control area, and the single-response explosive quantity is not more than 80 kg; the support priority, the specific parameter adjustment value, the blasting control index and the like are integrated to form the decision suggestion with clear arrangement, which directly guides the field construction personnel to adjust the support parameter and optimize the blasting scheme.

[0124] In the embodiment of the present application, based on the damage degree level and the spatial distribution characteristics thereof, the rock mass damage area needing to be treated as a key point is identified, the high-risk area needing to be paid attention to in construction can be accurately locked, and blind investment of resources is avoided; according to the distribution range and the damage degree of the key damage area, the corresponding support parameter adjustment scheme is formed, the traditional one-size-fits-all limitation of the support parameter is broken, the parameters such as the anchor rod length and the anchor cable spacing can be matched with the actual damage demand of different areas, and the quantitative adaptation of the support parameter is realized; based on the distribution characteristics of the rock mass damage area and combined with the tunnel rock mass damage spatial distribution map, the key control area of the blasting scheme optimization is determined, the area needing to reduce the blasting strength or adjust the charging structure can be accurately positioned, and the secondary disturbance of the blasting to the damaged rock mass is reduced; the support parameter adjustment scheme and the blasting key control area are integrated, and the confidence evaluation of the damage degree level is combined, the support priority and the blasting control points are clearly defined, the problems of poor decision-making connection and fuzzy implementation of the traditional monitoring results can be solved, and the decision-making suggestion is more systematic and operable.

[0125] As shown in Figure 2 The embodiment of the present application also provides a tunnel rock mass damage prediction system based on microseismic data, which comprises:

[0126] An acquisition module is configured to collect microseismic monitoring data in the tunnel construction process; and perform data preprocessing on the microseismic monitoring data to obtain a normalized microseismic data sequence.

[0127] The analysis module is configured to extract microseismic characteristic parameters related to rock mass damage based on the normalized microseismic data sequence, perform multi-parameter fusion analysis on the microseismic characteristic parameters, and form a comprehensive damage index based on a preset analysis rule set;

[0128] The setting module is configured to determine three core monitoring positions in the monitoring area based on the spatial distribution characteristics of the comprehensive damage index, with the three core monitoring positions being a current construction face center area, a vault stress concentration area, and a key area of side wall stability, respectively, and to construct a spatial analysis unit for representing the rock mass damage evolution trend based on the three core monitoring positions.

[0129] The construction module is configured to construct a minimum circumscribed triangle based on the spatial analysis unit to establish a quantitative description of the rock mass structure stability, i.e., to calculate structure form parameters of the minimum circumscribed triangle to obtain side length ratios and internal angle distribution characteristics, to form a spatial variation correction coefficient based on the structure form parameters, to correct the comprehensive damage index based on the spatial variation correction coefficient to obtain an optimized comprehensive damage index, and to form a tunnel rock mass damage spatial distribution map based on the determined damage degree level.

[0130] The comparison module is configured to compare the optimized comprehensive damage index with a preset damage threshold interval, and to determine a damage degree level of the tunnel rock mass according to a comparison result.

[0131] The summary module is configured to form a tunnel rock mass damage spatial distribution map based on the determined damage degree level, and to obtain a decision suggestion for guiding adjustment of a tunnel support parameter and optimization of a blasting scheme based on the damage degree level and the tunnel rock mass damage spatial distribution map.

[0132] The above describes preferred embodiments of the present application. It should be noted that, for those skilled in the art, without departing from the principles of the present application, a number of improvements and refinements can be made, and these improvements and refinements should also be considered within the scope of protection of the present application.

Claims

1. A method for predicting damage of a tunnel rock mass based on microseismic data, characterized in that, The method comprises: Step 1, collecting microseismic monitoring data in the tunnel construction process; data preprocessing is performed on the microseismic monitoring data to obtain normalized microseismic data sequence; Step 2, based on the normalized microseismic data sequence, extracting microseismic characteristic parameters related to rock mass damage; performing multi-parameter fusion analysis on the microseismic characteristic parameters, and forming a comprehensive damage index based on a preset analysis rule set; Step 3, based on the spatial distribution characteristics of the comprehensive damage index, determining three core monitoring positions in the monitoring area, the three core monitoring positions being the current construction working face center area, the arch top stress concentration area and the key area of the side wall stability respectively; based on the three core monitoring positions, a spatial analysis unit for representing the rock mass damage evolution trend is constructed; Step 4, based on the spatial analysis unit, constructing a minimum circumscribed triangle to establish a quantitative description of the rock mass structure stability, that is, calculating the structure form parameters of the minimum circumscribed triangle to obtain the side length ratio and the internal angle distribution characteristics; based on the structure form parameters, a spatial variation correction coefficient is formed, the spatial characteristics of the comprehensive damage index are corrected according to the spatial variation correction coefficient, and an optimized comprehensive damage index is obtained; Step 5, comparing the optimized comprehensive damage index with a preset damage threshold interval; determining the damage degree grade of the tunnel rock mass according to the comparison result; Step 6, based on the determined damage degree grade, forming a tunnel rock mass damage spatial distribution map; Step 7, according to the damage degree grade and the tunnel rock mass damage spatial distribution map, obtaining a decision suggestion for guiding the adjustment of the tunnel support parameters and the optimization of the blasting scheme. 2.The microseismic data based tunnel rock mass damage prediction method according to claim 1, characterized in that, Collecting microseismic monitoring data in the tunnel construction process; Data preprocessing is performed on the microseismic monitoring data to obtain normalized microseismic data sequence, including: Through the microseismic sensor array arranged in the tunnel surrounding rock, continuously collecting the microseismic event waveform signals induced by construction disturbance; Performing noise reduction processing on the collected microseismic event waveform signals to filter out the environmental noise interference generated by the construction machinery vibration to obtain the denoised waveform signals; Based on a preset amplitude threshold, identifying and extracting effective microseismic signal segments from the denoised waveform signals; Performing time domain normalization processing on the extracted microseismic signal segments to eliminate the signal intensity deviation caused by the difference in propagation path to obtain normalized microseismic signal segments; Recombining and arranging the normalized microseismic signal segments in time sequence to form a normalized microseismic data sequence. 3.The microseismic data based tunnel rock mass damage prediction method according to claim 2, characterized in that, Based on the normalized microseismic data sequence, extracting microseismic characteristic parameters related to rock mass damage; Performing multi-parameter fusion analysis on the microseismic characteristic parameters, and forming a comprehensive damage index based on a preset analysis rule set, including: Based on the normalized microseismic data sequence, calculating the time-frequency domain characteristic parameters of each microseismic event; From the time-frequency domain characteristic parameters, extracting key characteristic parameters related to rock mass damage, including event energy, main frequency feature and duration; Performing multi-parameter weighted fusion processing on the key characteristic parameters to obtain a preliminary damage evaluation value; Performing spatial clustering analysis on the preliminary damage evaluation value, identifying damage concentration areas based on a preset analysis rule set; According to the distribution characteristics of the identified damage concentration areas, the comprehensive damage index is calculated. 4.The microseismic data based tunnel rock mass damage prediction method according to claim 3, characterized in that, Based on the spatial distribution characteristics of the comprehensive damage index, three core monitoring positions are determined in the monitoring area, and the three core monitoring positions are respectively the center area of the current construction face, the stress concentration area of the arch top and the key area of the side wall stability; Based on the three core monitoring positions, a spatial analysis unit for representing the damage evolution trend of the rock mass is constructed, including: Based on the spatial distribution characteristics of the comprehensive damage index, the key area with concentrated damage is identified; According to the distribution characteristics of the key area with concentrated damage, three core monitoring positions are determined, and the three core monitoring positions correspond to the center area of the current construction face, the stress concentration area of the arch top and the key area of the side wall stability respectively; Taking the three core monitoring positions as reference points, the perpendicular bisector between adjacent reference points is calculated, and the monitoring area is divided into three non-overlapping spatial partitions; Based on the three non-overlapping spatial partitions, the spatial influence range corresponding to the core monitoring position is determined; According to the geometric characteristics of the spatial influence range, a spatial analysis unit representing the damage evolution trend of the rock mass is constructed. 5.The microseismic data based tunnel rock mass damage prediction method according to claim 4, characterized in that, Based on the spatial analysis unit, a minimum circumscribed triangle is constructed to establish a quantitative description of the stability of the rock mass structure, that is, the structural morphology parameters of the minimum circumscribed triangle are calculated to obtain the length ratio and the internal angle distribution characteristics; Based on the structural morphology parameters, a spatial variation correction coefficient is formed, and the comprehensive damage index is corrected based on the spatial variation correction coefficient to obtain an optimized comprehensive damage index, including: Based on the spatial influence range of the spatial analysis unit, the peripheral boundary points of the spatial distribution of rock mass damage are determined; By connecting the outermost boundary points, a minimum enclosing region is constructed to form a minimum circumscribed triangle of the spatial distribution of rock mass damage; The structural morphology parameters of the minimum circumscribed triangle are calculated, including the length ratio relationship, the internal angle distribution and the area-perimeter ratio; Based on the structural morphology parameters, a spatial variation correction coefficient is obtained by multi-parameter fusion calculation; Based on the spatial variation correction coefficient, the spatial distribution characteristics of the comprehensive damage index are calibrated to obtain an optimized comprehensive damage index. 6.The microseismic data based tunnel rock mass damage prediction method according to claim 5, characterized in that, The optimized comprehensive damage index is compared with the preset damage threshold interval; according to the comparison result, the damage degree grade of the tunnel rock mass is determined, including: The optimized comprehensive damage index is compared and analyzed with the preset multi-level damage threshold interval to obtain the comparison and analysis value; Based on the comparison and analysis value, the preliminary grade determination of rock mass damage is determined; The spatial consistency verification of the preliminary grade determination is carried out, and the spatial consistency verification result data is obtained combined with the geometric characteristic parameters of the spatial analysis unit; According to the spatial consistency verification result data, the final damage degree grade of the tunnel rock mass and its confidence evaluation are formed. 7.The microseismic data based tunnel rock mass damage prediction method according to claim 6, characterized in that, Based on the determined damage degree grade, a tunnel rock mass damage spatial distribution map is formed, including: Based on the damage degree grade and its confidence evaluation, a mapping relationship between the damage grade and the spatial coordinates is established; According to the geometric characteristic parameters of the spatial analysis unit, the mapping relationship is calculated by spatial interpolation to obtain a continuous rock mass damage spatial distribution surface; Based on the rock mass damage spatial distribution surface, a tunnel rock mass damage spatial distribution map containing multi-level damage marks is constructed; In the tunnel rock mass damage spatial distribution map, the damage level and confidence information of the key monitoring position are marked. 8.The microseismic data based tunnel rock mass damage prediction method according to claim 7, characterized in that, According to the damage degree level and the tunnel rock mass damage spatial distribution map, the decision suggestions for guiding the adjustment of tunnel support parameters and the optimization of blasting scheme are obtained, including: Based on the damage degree level and its spatial distribution characteristics, the rock mass damage area that needs to be treated is identified; According to the distribution range and damage degree of the identified rock mass damage area, the corresponding support parameter adjustment scheme is formed; Based on the distribution characteristics of the rock mass damage area, the key control area of blasting scheme optimization is determined by combining the tunnel rock mass damage spatial distribution map; The key control area of blasting scheme optimization is integrated with the support parameter adjustment scheme, and the decision suggestions containing support priority and blasting control points are obtained by combining the confidence evaluation of damage degree level.

9. A system for predicting rock mass damage in a tunnel based on microseismic data, the system implementing the method of any one of claims 1 to 8, characterized in that, Including: The acquisition module is used to collect microseismic monitoring data in the tunnel construction process; The microseismic monitoring data is preprocessed to obtain normalized microseismic data sequence; The analysis module is used to extract microseismic characteristic parameters related to rock mass damage based on the normalized microseismic data sequence; Multi-parameter fusion analysis is performed on the microseismic characteristic parameters, and a comprehensive damage index is formed based on the preset analysis rule set; The setting module is used to determine three core monitoring positions in the monitoring area based on the spatial distribution characteristics of the comprehensive damage index, and the three core monitoring positions are the current construction center area, the vault stress concentration area and the side wall stability key area respectively; Based on the three core monitoring positions, a spatial analysis unit is constructed to represent the rock mass damage evolution trend; The construction module is used to construct the minimum circumscribed triangle based on the spatial analysis unit to establish the quantitative description of rock mass structure stability, i.e. to calculate the structure shape parameters of the minimum circumscribed triangle to obtain the side length ratio and internal angle distribution characteristics; Based on the structure shape parameters, a spatial variation correction coefficient is formed, and the spatial characteristics of the comprehensive damage index are corrected according to the spatial variation correction coefficient to obtain the optimized comprehensive damage index; The comparison module is used to compare the optimized comprehensive damage index with the preset damage threshold interval; and the damage degree level of the tunnel rock mass is determined according to the comparison result; The summary module is used to form a tunnel rock mass damage spatial distribution map based on the determined damage degree level. According to the damage degree level and the tunnel rock mass damage spatial distribution map, the decision suggestions for guiding the adjustment of tunnel support parameters and the optimization of blasting scheme are obtained.

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