A deformation prediction system for surrounding rock structures based on multi-source information representation

Abstract

The invention discloses a surrounding rock structure deformation prediction system based on multi-source information characterization, relates to the field of geology, solves the problem of poor prediction effect of the surrounding rock structure deformation prediction system, comprises a geological data module: regional geological analysis is performed on target surrounding rock and multiple sample monitoring surrounding rock respectively to obtain surrounding rock geological data, an engineering data module: engineering quantity analysis is performed on target surrounding rock and multiple sample monitoring surrounding rock according to the surrounding rock geological data to obtain surrounding rock engineering data, a data analysis module: surrounding rock prediction analysis data is obtained by analyzing surrounding rock engineering data and surrounding rock geological data, a deformation prediction module: a surrounding rock deformation prediction model is established according to the surrounding rock prediction analysis data, and deformation prediction is performed on the target surrounding rock using the surrounding rock deformation prediction model. The invention can improve the accuracy and pertinence of the surrounding rock structure deformation prediction result.

Description

Technical Field

[0001] The invention belongs to the field of geological monitoring, relates to surrounding rock deformation prediction technology, and specifically is a surrounding rock structure deformation prediction system based on multi-source information characterization. Background Art

[0002] The existing surrounding rock structure deformation prediction methods have the following defects when predicting the structural deformation of the surrounding rock:

[0003] 1. The prediction samples selected by the existing surrounding rock structure deformation prediction methods often have large deviations from the geological data of the target prediction area, resulting in a lack of pertinence in the prediction samples, which easily leads to a large deviation between the prediction results and the actual situation;

[0004] 2. Existing methods for predicting deformation of surrounding rock structures often analyze surrounding rock deformation from the perspective of sensor data alone, lacking analysis and summary of the historical deformation laws of the target surrounding rock. While consuming a large amount of prediction resources, it is difficult to significantly improve the accuracy of the prediction results, resulting in low cost-effectiveness of the prediction method and difficulty in comprehensive promotion.

[0005] To this end, we propose a surrounding rock structure deformation prediction system based on multi-source information characterization. Summary of the invention

[0006] In view of the deficiencies in the prior art, the present invention aims to provide a surrounding rock structure deformation prediction system based on multi-source information characterization. The present invention is based on selecting target surrounding rock and multiple sample monitoring surrounding rock respectively, performing regional geological analysis on the target surrounding rock and multiple sample monitoring surrounding rock respectively, obtaining multiple geological analysis coefficients, defining the target surrounding rock, multiple sample monitoring surrounding rock and multiple geological analysis coefficients as surrounding rock geological data, performing engineering quantity analysis on the target surrounding rock and multiple sample monitoring surrounding rock according to the surrounding rock geological data, and obtaining the engineering earthwork excavation volume, engineering construction length value and profile geometric structure coefficient corresponding to each surrounding rock respectively. And analyze and obtain multiple engineering analysis coefficients to obtain surrounding rock engineering data, and obtain deformation prediction coefficients corresponding to target surrounding rock and multiple sample monitoring surrounding rocks by analyzing surrounding rock engineering data and surrounding rock geological data, and obtain sample surrounding rock deformation index values ​​corresponding to each sample monitoring surrounding rock to obtain surrounding rock prediction analysis data, and establish a surrounding rock deformation prediction model based on the surrounding rock prediction analysis data, and obtain the target surrounding rock deformation index value by inputting the target deformation coefficient into the surrounding rock deformation prediction model, and obtain the surrounding rock deformation index value threshold and the target surrounding rock deformation index value for numerical comparison, and predict the deformation of the target surrounding rock according to the numerical comparison result.

[0007] In order to achieve the above purpose, the present invention adopts the following technical solution: a surrounding rock structure deformation prediction system based on multi-source information representation, and the specific working process of each module is as follows:

[0008] Geological data module: select target surrounding rock and multiple sample monitoring surrounding rock respectively, conduct regional geological analysis on the target surrounding rock and multiple sample monitoring surrounding rock respectively, obtain multiple geological analysis coefficients, and define the target surrounding rock, multiple sample monitoring surrounding rock and multiple geological analysis coefficients as surrounding rock geological data;

[0009] Engineering data module: Perform engineering quantity analysis on target surrounding rock and multiple sample monitoring surrounding rock according to surrounding rock geological data, obtain the engineering earthwork excavation volume, engineering construction length value and profile geometric structure coefficient corresponding to each surrounding rock, and analyze and obtain multiple engineering analysis coefficients to obtain surrounding rock engineering data;

[0010] Data analysis module: by analyzing the surrounding rock engineering data and surrounding rock geological data, the deformation prediction coefficients corresponding to the target surrounding rock and multiple sample monitoring surrounding rocks are obtained, and the sample surrounding rock deformation index value corresponding to each sample monitoring surrounding rock is obtained to obtain the surrounding rock prediction analysis data;

[0011] Deformation prediction module: A surrounding rock deformation prediction model is established based on the surrounding rock prediction analysis data. The target surrounding rock deformation index value is obtained by inputting the target deformation coefficient into the surrounding rock deformation prediction model. The surrounding rock deformation index value threshold is obtained and numerically compared with the target surrounding rock deformation index value. The deformation of the target surrounding rock is predicted based on the numerical comparison results.

[0012] Furthermore, the geological data module acquires surrounding rock geological data as follows:

[0013] Mark the surrounding rock coverage area in the regional map to obtain the surrounding rock deformation prediction area, and randomly select a surrounding rock to be deformed in the surrounding rock deformation prediction area as the target surrounding rock;

[0014] Randomly select a number of surrounding rocks in the surrounding rock deformation prediction area as sample monitoring surrounding rocks, and name the obtained multiple sample monitoring surrounding rocks as the first sample monitoring surrounding rock to the pth sample monitoring surrounding rock respectively;

[0015] Conduct regional geological analysis on the target surrounding rock to obtain the regional geological analysis coefficient corresponding to the target surrounding rock;

[0016] The regional geological analysis coefficients corresponding to the first sample monitoring surrounding rock to the p-th sample monitoring surrounding rock are respectively obtained to obtain the first sample geological analysis coefficient to the p-th sample geological analysis coefficient;

[0017] The target surrounding rock, the regional geological analysis coefficient corresponding to the target surrounding rock, the first sample monitoring surrounding rock to the p-th sample monitoring surrounding rock, and the first sample geological analysis coefficient to the p-th sample geological analysis coefficient are defined as the surrounding rock geological data.

[0018] Furthermore, the geological data module obtains the regional geological analysis coefficient corresponding to the target surrounding rock, as follows:

[0019] A number of geological survey points with equal distances are randomly selected above the ground surface corresponding to the target surrounding rock, and the direction of the connecting line of the multiple geological survey points is consistent with the direction of the target surrounding rock, and the selected multiple geological survey points are named as the first geological survey point to the i-th geological survey point respectively;

[0020] Drilling rock cores of the same depth from the first geological exploration point to the i-th geological exploration point respectively to obtain the first geological exploration rock core to the i-th geological exploration rock core;

[0021] Obtaining the quantity of the selected geological survey points to obtain the quantity value of the geological survey points;

[0022] Performing structural analysis on the first geological survey core to obtain the depth value of the first rock section to the depth value of the ath rock section;

[0023] The bottom of the characteristic monitoring core is used as the first core marking point, the top of the characteristic monitoring core is used as the second core marking point, and between the first core marking point and the second core marking point, the same type of structural layer in the characteristic monitoring core is marked as a monitoring rock section, thereby obtaining multiple monitoring rock sections;

[0024] The length center point corresponding to each monitored rock section is obtained respectively to obtain multiple length center points, the distance value between each length center point and the first core length marking point is calculated, and the obtained multiple distance values ​​are marked from the first rock section depth value to the ath rock section depth value in descending order;

[0025] Repeat the process of obtaining the first rock section depth value to the a-th rock section depth value corresponding to the first geological survey core, and obtain the first rock section depth value to the a-th rock section depth value corresponding to the second geological survey core to the i-th geological survey core respectively;

[0026] Establish a rock section depth plane rectangular coordinate system by taking the first geological survey core to the i-th geological survey core as the horizontal coordinate and the first rock section depth value to the a-th rock section depth value corresponding to the first geological survey core to the i-th geological survey core as the vertical coordinate;

[0027] Connect each coordinate point corresponding to the first rock section depth value in the rock section depth distribution plane index coordinate to obtain the first rock section depth distribution broken line, connect each coordinate point corresponding to the second rock section depth value to obtain the second rock section depth distribution broken line, and so on, connect each coordinate point corresponding to the a-th rock section depth value to obtain the a-th rock section depth distribution broken line;

[0028] Analyze the depth distribution line of the first rock section to obtain the number of fractures in the first rock section;

[0029] Analyze the depth distribution line of the second rock section to the depth distribution line of the ath rock section respectively, and obtain the number of fractures in the second rock section to the number of fractures in the ath rock section;

[0030] The number of rock section fractures from the first rock section to the ath rock section is summed up to obtain the number of rock section fractures, and the ratio of the number of rock section fractures to the number of geological survey points is calculated to obtain the average number of rock section fractures at the monitoring point;

[0031] The area covered by the target surrounding rock is obtained to obtain the area value of the target surrounding rock coverage area, and the ratio of the area value of the target surrounding rock coverage area to the average number of rock segment fractures at the monitoring point is calculated to obtain the regional geological analysis coefficient corresponding to the target surrounding rock.

[0032] Furthermore, the geological data module obtains the number of fractures in the first rock section as follows:

[0033] In the first rock section depth distribution polyline, the coordinate point corresponding to the first geological survey core is marked as the first core coordinate point, the coordinate point corresponding to the second geological survey core is marked as the second core coordinate point, and so on, the coordinate point corresponding to the i-1th geological survey core is marked as the i-1th core coordinate point, and the coordinate point corresponding to the i-th geological survey core is marked as the i-th core coordinate point, and the coordinate point from the first core coordinate point to the i-th core coordinate point is obtained;

[0034] The connection line between the first core coordinate point and the second core coordinate point is marked as the first core coordinate connection line, the connection line between the second core coordinate point and the third core coordinate point is marked as the second core coordinate connection line, and so on, the connection line between the i-1th core coordinate point and the i-th core coordinate point is marked as the i-1th core coordinate connection line, and the first core coordinate connection line to the i-1th core coordinate connection line are obtained;

[0035] Obtain the slopes of the first core coordinate line to the i-1th core coordinate line to obtain the depth change rate of the first rock section to the i-1th rock section;

[0036] Obtaining a rock section depth change rate threshold, numerically comparing the first rock section depth change rate to the (i-1)th rock section depth change rate with the rock section depth change rate threshold, when the rock section depth change rate is greater than the rock section depth change rate threshold, classifying the corresponding rock section depth change rate as a first type of rock section change rate, and when the rock section depth change rate is less than the rock section depth change rate threshold, classifying the corresponding rock section depth change rate as a second type of rock section change rate;

[0037] The number of rock section depth change rates of the first type of rock section change rate from the first rock section depth change rate to the i-1th rock section depth change rate is counted to obtain the number of first rock section fractures.

[0038] Furthermore, the engineering data module acquires surrounding rock engineering data as follows:

[0039] Obtaining surrounding rock geological data, and obtaining target surrounding rock and first sample monitoring surrounding rock to pth sample monitoring surrounding rock according to the surrounding rock geological data;

[0040] Conduct engineering quantity analysis on the target surrounding rock and obtain the engineering analysis coefficient corresponding to the target surrounding rock;

[0041] The details are as follows:

[0042] Acquire the engineering project corresponding to the target surrounding rock to obtain the target engineering project;

[0043] The earthwork excavation volume corresponding to the target engineering project is obtained to obtain the engineering earthwork excavation volume;

[0044] Obtain the engineering construction length corresponding to the target engineering project to obtain the engineering construction length value;

[0045] Draw a base surface marking line on the base surface of the target project with the same horizontal direction as the project, select a number of base surface marking points on the base surface marking line, and the distance between each two consecutive base surface marking points is equal;

[0046] The distance value between each base surface marking point and the ground is obtained respectively to obtain multiple base surface marking point depth values, and the average of the obtained multiple base surface marking point depth values ​​is calculated to obtain the average depth value of the project;

[0047] Each base surface marking point is taken as a plane perpendicular to the base surface to obtain multiple marking sections, and a marking section is randomly selected from the multiple marking sections as a sample marking point section;

[0048] Performing geometric structure analysis on the sample marked section to obtain the section geometric structure coefficient corresponding to the sample marked section;

[0049] Obtaining the section geometry coefficient for each marked section of the target engineering project respectively to obtain a plurality of section geometry coefficients, and averaging the obtained plurality of section geometry coefficients to obtain an average value of the section geometry coefficients;

[0050] The engineering analysis coefficient corresponding to the target surrounding rock is obtained by calculating the engineering earthwork excavation volume, engineering construction length value and the average value of the section geometric structure coefficient;

[0051] The engineering analysis coefficient is calculated as follows:

[0052] ;

[0053] Among them, Gfx is the engineering analysis coefficient, Kwl is the engineering earth excavation volume, Sgc is the engineering construction length value, and Jgx is the average value of the section geometric structure coefficient;

[0054] Repeat the process of obtaining the engineering analysis coefficient corresponding to the target surrounding rock, respectively obtain the engineering analysis coefficients corresponding to the first sample monitoring surrounding rock to the p-th sample monitoring surrounding rock, and obtain the first engineering analysis coefficient to the p-th engineering analysis coefficient;

[0055] The engineering analysis coefficient corresponding to the target surrounding rock and the first to pth engineering analysis coefficients are defined as surrounding rock engineering data.

[0056] Furthermore, the engineering data module obtains the section geometry coefficient corresponding to the sample marked section, as follows:

[0057] Acquire the height value of the sample marked section to obtain the sample section height value, acquire the width value of the sample marked section to obtain the sample section width value, calculate the ratio of the sample section width value to the sample section height value to obtain the sample section aspect ratio, and obtain the sample section reference aspect ratio, calculate the difference between the sample section aspect ratio and the sample section reference aspect ratio, and take the absolute value of the obtained difference to obtain the section aspect ratio reference deviation;

[0058] In the sample marked section, the intersection points of the sample marked section arc and the straight lines on both sides are marked as the first characteristic marking point and the second characteristic marking point respectively, the baseline at the bottom of the section in the sample marked section is marked as the first characteristic baseline, and the midpoint of the first characteristic baseline is marked to obtain the third characteristic marking point;

[0059] The first characteristic marking point and the third characteristic marking point are connected to obtain a first characteristic marking line, the second characteristic marking point and the third characteristic marking point are connected to obtain a second characteristic marking line, the angle formed by the first characteristic marking line and the second characteristic marking line at the third characteristic marking point is obtained to obtain a first characteristic angle, and the angle value corresponding to the first characteristic angle is obtained to obtain an arc bottom angle value;

[0060] Obtain the arc bottom angle reference value, calculate the difference between the arc bottom angle value and the arc bottom angle reference value, and take the absolute value of the obtained difference to obtain the arc bottom angle reference difference;

[0061] In the sample marking section, the midpoint of the arc top curve is marked as the fourth characteristic marking point, the first characteristic marking point and the fourth characteristic marking point are connected to obtain the third characteristic marking line, the second characteristic marking point and the fourth characteristic marking point are connected to obtain the fourth characteristic marking line, the angle formed by the third characteristic marking line and the fourth characteristic marking line at the fourth characteristic marking point is obtained to obtain the second characteristic angle, and the angle value corresponding to the first characteristic angle is obtained to obtain the arc top angle value;

[0062] Obtaining the arc top angle reference value, calculating the difference between the arc top angle value and the arc top angle reference value, and taking the absolute value of the obtained difference to obtain the arc top angle reference difference;

[0063] The profile geometric structure coefficient corresponding to the sample marked profile is obtained by calculating the profile aspect ratio benchmark deviation, arc bottom angle benchmark difference and arc top angle benchmark difference;

[0064] The cross-section geometric structure coefficient is calculated, and the specific formula is as follows:

[0065] ;

[0066] Among them, Pmj is the section geometry coefficient, Kgb is the reference deviation of the section aspect ratio, Djp is the reference difference of the arc bottom angle, and Ljp is the reference difference of the arc top angle.

[0067] Furthermore, the engineering data module acquires surrounding rock prediction and analysis data, as follows:

[0068] Obtain surrounding rock geological data, and obtain the first sample monitoring surrounding rock to the p-th sample monitoring surrounding rock, the first sample geological analysis coefficient to the p-th sample geological analysis coefficient, and the regional geological analysis coefficient corresponding to the target surrounding rock according to the surrounding rock geological data;

[0069] Obtaining surrounding rock engineering data, and obtaining engineering analysis coefficients corresponding to target surrounding rock and first to pth engineering analysis coefficients according to the surrounding rock engineering data;

[0070] The structural deformation coefficient corresponding to the target surrounding rock is obtained by calculating the geological analysis coefficient and the engineering analysis coefficient corresponding to the target surrounding rock, and is named as the target deformation prediction coefficient;

[0071] The target deformation coefficient is calculated, and the specific formula is as follows:

[0072] ;

[0073] Among them, Mxx is the target deformation coefficient, Dfx is the geological analysis coefficient, and Gfx is the engineering analysis coefficient;

[0074] According to the first sample geological analysis coefficient to the p-th sample geological analysis coefficient and the first engineering analysis coefficient to the p-th engineering analysis coefficient, the structural deformation coefficients corresponding to the first sample monitoring surrounding rock to the p-th sample monitoring surrounding rock are calculated, and the first deformation prediction coefficient to the p-th deformation prediction coefficient are obtained;

[0075] Conduct historical deformation analysis on the surrounding rock monitored by the first sample to obtain the deformation index value of the surrounding rock of the first sample;

[0076] Obtain the surrounding rock deformation index values ​​corresponding to the second sample monitoring surrounding rock to the p-th sample monitoring surrounding rock respectively, and obtain the second sample surrounding rock deformation index value to the p-th sample surrounding rock deformation index value;

[0077] The first deformation prediction coefficient to the p-th deformation prediction coefficient, the first sample surrounding rock deformation index value to the p-th sample surrounding rock deformation index value, and the target deformation coefficient are defined as surrounding rock prediction analysis data.

[0078] Furthermore, the engineering data module obtains the deformation index value of the surrounding rock of the first sample, as follows:

[0079] In the historical monitoring period corresponding to the first sample monitoring surrounding rock, the first historical monitoring time point and the second historical monitoring time point are marked respectively, and the first historical monitoring time point and the second historical monitoring time point are separated by a surrounding rock prediction cycle;

[0080] Acquire the engineering project corresponding to the first sample monitoring surrounding rock to obtain the first sample engineering project;

[0081] Draw a base surface auxiliary line on the base surface of the first sample project with the same horizontal direction as the project, select a number of base surface auxiliary points on the base surface auxiliary line, and the distance between each two consecutive base surface auxiliary points is equal;

[0082] A plane perpendicular to the base surface is drawn through each auxiliary point of the base surface to obtain multiple characteristic profiles, and a characteristic profile is randomly selected from the multiple characteristic profiles as a sample characteristic profile;

[0083] Performing a structural analysis on the sample characteristic profile at the first historical monitoring time point, obtaining a profile structure coefficient corresponding to the sample characteristic profile at the first historical monitoring time point, and obtaining a first profile structure coefficient;

[0084] Obtaining a profile structure coefficient corresponding to the sample characteristic profile at the second historical monitoring time point to obtain a second profile structure coefficient;

[0085] The difference between the first section structure coefficient and the second section structure coefficient is calculated, and the absolute value of the obtained difference is taken to obtain the section deformation deviation coefficient corresponding to the sample characteristic section;

[0086] The profile deformation deviation coefficient corresponding to each characteristic profile is obtained respectively to obtain a plurality of profile deformation deviation coefficients, and the average of the obtained plurality of profile deformation deviation coefficients is calculated to obtain the first sample surrounding rock deformation index value.

[0087] Furthermore, the engineering data module obtains the first section structure coefficient as follows:

[0088] In the sample characteristic profile, the intersection points of the sample characteristic profile arc and the straight lines on both sides are marked as the first characteristic auxiliary point and the second characteristic auxiliary point respectively, the baseline at the bottom of the profile in the sample characteristic profile is marked as the first characteristic baseline, and the midpoint of the first characteristic baseline is marked to obtain the third characteristic auxiliary point;

[0089] The first feature auxiliary point and the third feature auxiliary point are connected to obtain a first feature auxiliary line, the second feature auxiliary point and the third feature auxiliary point are connected to obtain a second feature auxiliary line, the angle formed by the first feature auxiliary line and the second feature auxiliary line at the third feature auxiliary point is obtained to obtain a first feature angle, and the angle value corresponding to the first feature angle is obtained to obtain an arc bottom feature angle;

[0090] In the sample characteristic profile, the midpoint of the arc top curve is marked as the fourth characteristic auxiliary point, the first characteristic auxiliary point and the fourth characteristic auxiliary point are connected to obtain the third characteristic auxiliary line, the second characteristic auxiliary point and the fourth characteristic auxiliary point are connected to obtain the fourth characteristic auxiliary line, the angle formed by the third characteristic auxiliary line and the fourth characteristic auxiliary line at the fourth characteristic auxiliary point is obtained to obtain the second characteristic angle, and the angle value corresponding to the first characteristic angle is obtained to obtain the arc top characteristic angle;

[0091] The height value of the characteristic profile of the sample is obtained to obtain the profile height value, and the width value of the characteristic profile of the sample is obtained to obtain the profile width value;

[0092] The arc bottom characteristic angle, arc top characteristic angle, profile height value and profile width value are calculated to obtain the profile structure coefficient corresponding to the first historical monitoring time point, and the profile structure coefficient is named as the first profile structure coefficient;

[0093] The first profile structure coefficient corresponding to the sample characteristic profile is calculated. The specific formula is as follows:

[0094] ;

[0095] Among them, Pjx1 is the first section structure coefficient, Hdz is the arc bottom characteristic angle, Hlz is the arc top characteristic angle, Pgz is the section height value, and Pkz is the section width value.

[0096] Furthermore, the deformation prediction module performs deformation prediction on the target surrounding rock, as follows:

[0097] Obtain surrounding rock prediction and analysis data, and obtain first to p-th deformation prediction coefficients, first to p-th sample surrounding rock deformation index values, and a target deformation coefficient according to the surrounding rock prediction and analysis data;

[0098] Establishing a surrounding rock deformation prediction model according to the first deformation prediction coefficient to the p-th deformation prediction coefficient and the first sample surrounding rock deformation index value to the p-th sample surrounding rock deformation index value;

[0099] The details are as follows:

[0100] Establish a polynomial fitting function by using the first deformation prediction coefficient to the p-th deformation prediction coefficient and the first sample surrounding rock deformation index value to the p-th sample surrounding rock deformation index value;

[0101] The polynomial fitting function is as follows:

[0102] ;

[0103] Among them, y is the surrounding rock deformation index value, x is the deformation prediction coefficient, a0 to a n The coefficients of the polynomial fitting function, n is the order of the polynomial fitting function;

[0104] Substitute the first deformation prediction coefficient to the p-th deformation prediction coefficient and the first sample surrounding rock deformation index value to the p-th sample surrounding rock deformation index value into the polynomial fitting function respectively, and calculate the residual sum of squares function RSS of the surrounding rock deformation index value;

[0105] The coefficients a0 to a of the polynomial fitting function in the residual sum of squares function RSS are respectively n Calculate partial derivatives and get n unknown numbers a0 to a n Function expression, and convert n unknown numbers a0 to a n The function expressions of are combined to obtain n groups containing a0 to a n The system of equations, and solve the system of equations to obtain a0 to a n Specific value of

[0106] Change a0 to a n The specific value of is substituted back into the polynomial fitting function to obtain the surrounding rock deformation prediction model;

[0107] Substituting the target deformation coefficient into the surrounding rock deformation prediction model, and obtaining the result value output by the surrounding rock deformation prediction model, to obtain the target surrounding rock deformation index value;

[0108] Obtaining a surrounding rock deformation index threshold, numerically comparing the target surrounding rock deformation index value with the surrounding rock deformation index threshold, and predicting the deformation of the target surrounding rock according to the numerical comparison result;

[0109] The details are as follows:

[0110] When the target surrounding rock deformation index value is greater than or equal to the surrounding rock deformation index threshold, it is predicted that the target surrounding rock will have structural deformation;

[0111] When the target surrounding rock deformation index value is less than the surrounding rock deformation index threshold, it is predicted that the target surrounding rock will not experience structural deformation.

[0112] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0113] 1. The present invention selects surrounding rocks in the same area as the target surrounding rocks as prediction samples, and performs deformation prediction analysis on the prediction samples from geological and engineering perspectives, which can effectively improve the accuracy of deformation prediction results;

[0114] 2. The present invention establishes a surrounding rock deformation prediction model based on the surrounding rock prediction analysis data, obtains the target surrounding rock deformation index value by inputting the target deformation coefficient into the surrounding rock deformation prediction model, obtains the surrounding rock deformation index value threshold and compares it numerically with the target surrounding rock deformation index value, and predicts the deformation of the target surrounding rock based on the numerical comparison result, which can effectively ensure the scientific nature of the deformation prediction process and the accuracy of the results. BRIEF DESCRIPTION OF THE DRAWINGS

[0115] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0116] Figure 1 is the overall system block diagram of the present invention;

[0117] Figure 2 The rectangular coordinate system of the rock section depth plane of the present invention;

[0118] Figure 3 It is a schematic cross-sectional diagram of a sample marker of the present invention. DETAILED DESCRIPTION

[0119] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0120] For example 1 of this application, please refer to Figure 1The present invention provides a technical solution: a surrounding rock structure deformation prediction system based on multi-source information representation, including a geological data module, an engineering data module, a data analysis module, a deformation prediction module and a server, wherein the geological data module, the engineering data module, the data analysis module and the deformation prediction module are respectively connected to the server, and the server controls the geological data module, the engineering data module, the data analysis module and the deformation prediction module respectively.

[0121] The geological data module selects target surrounding rocks and multiple sample monitoring surrounding rocks respectively, performs regional geological analysis on the target surrounding rocks and multiple sample monitoring surrounding rocks respectively, obtains multiple geological analysis coefficients, and defines the target surrounding rocks, multiple sample monitoring surrounding rocks and the corresponding multiple geological analysis coefficients as surrounding rock geological data;

[0122] Mark the surrounding rock coverage area in the regional map to obtain the surrounding rock deformation prediction area, and randomly select a surrounding rock to be deformed in the surrounding rock deformation prediction area as the target surrounding rock;

[0123] In the surrounding rock deformation prediction area, several surrounding rocks are randomly selected as sample monitoring surrounding rocks, and the obtained multiple sample monitoring surrounding rocks are named as the first sample monitoring surrounding rock to the pth sample monitoring surrounding rock.

[0124] It should be noted here that:

[0125] The p involved here is the quantity value corresponding to the sample monitoring surrounding rock, and p is an integer greater than 0;

[0126] Conduct regional geological analysis on the target surrounding rock to obtain the regional geological analysis coefficient corresponding to the target surrounding rock;

[0127] The details are as follows:

[0128] Above the ground surface corresponding to the target surrounding rock, several geological survey points with equal distances are randomly selected, and the direction of the connecting line of the multiple geological survey points is consistent with the direction of the target surrounding rock. The selected multiple geological survey points are named as the first geological survey point to the i-th geological survey point.

[0129] It should be noted here that:

[0130] Here, i is designed to be the quantity value corresponding to the geological survey point, and i is the quantity value corresponding to the geological survey point;

[0131] Cores of the same depth are drilled downward from the first geological exploration point to the i-th geological exploration point respectively to obtain the first geological survey core to the i-th geological survey core.

[0132] Obtaining the quantity of the selected geological survey points to obtain the quantity value of the geological survey points;

[0133] Performing structural analysis on the first geological survey core to obtain the depth value of the first rock section to the depth value of the ath rock section;

[0134] The bottom of the characteristic monitoring core is taken as the first core marking point, and the top of the characteristic monitoring core is taken as the second core marking point. Between the first core marking point and the second core marking point, the same type of structural layer in the characteristic monitoring core is marked as a monitoring rock section, and multiple monitoring rock sections are obtained.

[0135] It should be noted here that:

[0136] In the present application, the same type of structural layer specifically refers to a core section formed by the accumulation of the same type of geological components in the core. The monitored rock sections involved here include but are not limited to soil, sand and gravel, and sedimentary rock.

[0137] The length center point corresponding to each monitored rock section is obtained respectively to obtain multiple length center points, and the distance value between each length center point and the first core length marking point is calculated, and the obtained multiple distance values ​​are marked from the first rock section depth value to the ath rock section depth value in descending order.

[0138] It should be noted here that:

[0139] In the present application, a is a quantitative value corresponding to the monitored rock section, and a is an integer greater than 0.

[0140] Repeat the process of obtaining the first rock section depth value to the ath rock section depth value corresponding to the first geological survey core, and obtain the first rock section depth value to the ath rock section depth value corresponding to the second geological survey core to the i-th geological survey core respectively.

[0141] See also Figure 2 , taking the first geological survey core to the ith geological survey core as the horizontal coordinate, and the first rock section depth value to the ath rock section depth value corresponding to the first geological survey core to the ith geological survey core as the vertical coordinate to establish a rock section depth plane rectangular coordinate system;

[0142] In the rock section depth distribution plane indicator coordinates, each coordinate point corresponding to the first rock section depth value is connected to obtain the first rock section depth distribution broken line, and each coordinate point corresponding to the second rock section depth value is connected to obtain the second rock section depth distribution broken line. And so on, each coordinate point corresponding to the a-th rock section depth value is connected to obtain the a-th rock section depth distribution broken line.

[0143] Analyze the depth distribution line of the first rock section to obtain the number of fractures in the first rock section;

[0144] The details are as follows:

[0145] In the first rock section depth distribution polyline, the coordinate point corresponding to the first geological survey core is marked as the first core coordinate point, the coordinate point corresponding to the second geological survey core is marked as the second core coordinate point, and so on, the coordinate point corresponding to the i-1th geological survey core is marked as the i-1th core coordinate point, and the coordinate point corresponding to the i-th geological survey core is marked as the i-th core coordinate point, and the coordinate point from the first core coordinate point to the i-th core coordinate point is obtained;

[0146] The line between the first core coordinate point and the second core coordinate point is marked as the first core coordinate line, the line between the second core coordinate point and the third core coordinate point is marked as the second core coordinate line, and so on, the line between the i-1th core coordinate point and the i-th core coordinate point is marked as the i-1th core coordinate line, and the first core coordinate line to the i-1th core coordinate line are obtained.

[0147] Obtain the slopes of the first core coordinate line to the i-1th core coordinate line to obtain the depth change rate of the first rock section to the i-1th rock section;

[0148] The rock section depth change rate threshold is obtained, and the rock section depth change rate to the i-1th rock section depth change rate are numerically compared with the rock section depth change rate threshold; when the rock section depth change rate is greater than the rock section depth change rate threshold, the corresponding rock section depth change rate is classified as the first type of rock section change rate; when the rock section depth change rate is less than the rock section depth change rate threshold, the corresponding rock section depth change rate is classified as the second type of rock section change rate.

[0149] Count the depth change rate of the first rock section to the depth change rate of the i-1th rock section, which is the first type of rock section change rate, to obtain the number of fractures in the first rock section;

[0150] Repeat the process of obtaining the number of fractures in the first rock section, analyze the depth distribution line of the second rock section to the depth distribution line of the a-th rock section, and obtain the number of fractures in the second rock section to the a-th rock section;

[0151] The number of rock section fractures is summed up to the number of rock section fractures from the first rock section to the ath rock section to obtain the number of rock section fractures. The ratio of the number of rock section fractures to the number of geological survey points is calculated to obtain the average number of rock section fractures at the monitoring point.

[0152] The area covered by the target surrounding rock is obtained to obtain the area value of the target surrounding rock covered area, and the ratio of the area value of the target surrounding rock covered area to the average number of rock segment fractures at the monitoring point is calculated to obtain the regional geological analysis coefficient corresponding to the target surrounding rock;

[0153] Repeat the process of obtaining the regional geological analysis coefficient corresponding to the target surrounding rock, respectively obtain the regional geological analysis coefficients corresponding to the first sample monitoring surrounding rock to the p-th sample monitoring surrounding rock, and obtain the first sample geological analysis coefficient to the p-th sample geological analysis coefficient.

[0154] The target surrounding rock, the regional geological analysis coefficient corresponding to the target surrounding rock, the first sample monitoring surrounding rock to the pth sample monitoring surrounding rock, and the first sample geological analysis coefficient to the pth sample geological analysis coefficient are defined as surrounding rock geological data;

[0155] The geological data module acquires the surrounding rock geological data and transmits it to the engineering data module, deformation prediction module and data analysis module;

[0156] The engineering data module performs engineering quantity analysis on the target surrounding rock and multiple sample monitoring surrounding rocks according to the surrounding rock geological data, obtains the engineering analysis coefficient corresponding to the target surrounding rock and the first engineering analysis coefficient to the pth engineering analysis coefficient, and obtains the surrounding rock engineering data;

[0157] Obtain surrounding rock geological data, and obtain target surrounding rock and first sample monitoring surrounding rock to pth sample monitoring surrounding rock according to the surrounding rock geological data.

[0158] Conduct engineering quantity analysis on the target surrounding rock and obtain the engineering analysis coefficient corresponding to the target surrounding rock;

[0159] The details are as follows:

[0160] Acquire the engineering project corresponding to the target surrounding rock to obtain the target engineering project;

[0161] It should be noted here that:

[0162] In the present application, the engineering project corresponding to the target surrounding rock is specifically the engineering project within the target surrounding rock coverage area, the target surrounding rock is the rock environment surrounding the target engineering project, and the target engineering project involved here is specifically the tunnel engineering project.

[0163] The earthwork excavation volume corresponding to the target engineering project is obtained to obtain the engineering earthwork excavation volume;

[0164] Obtain the engineering construction length corresponding to the target engineering project to obtain the engineering construction length value;

[0165] Draw a base surface marking line on the base surface of the target project with the same horizontal direction as the project, select several base surface marking points on the base surface marking line, and the distance between every two consecutive base surface marking points is equal.

[0166] It should be noted here that:

[0167] The target project base surface referred to here is the ground where the target project is located.

[0168] The distance value between each base surface marking point and the ground is obtained respectively to obtain multiple base surface marking point depth values, and the average of the obtained multiple base surface marking point depth values ​​is calculated to obtain the average depth value of the project;

[0169] Each base surface marking point is taken as a plane perpendicular to the base surface to obtain multiple marking sections, and a marking section is randomly selected from the multiple marking sections as a sample marking point section.

[0170] Performing geometric structure analysis on the sample marked section to obtain the section geometric structure coefficient corresponding to the sample marked section;

[0171] The details are as follows:

[0172] The height value of the sample marked section is obtained to obtain the sample section height value, the width value of the sample marked section is obtained to obtain the sample section width value, the ratio of the sample section width value to the sample section height value is calculated to obtain the sample section aspect ratio, and the sample section reference aspect ratio is obtained, the difference between the sample section aspect ratio and the sample section reference aspect ratio is calculated, and the absolute value of the obtained difference is taken to obtain the section aspect ratio reference deviation.

[0173] It should be noted here that:

[0174] In the present application, the sample profile reference aspect ratio refers to the proportional relationship between the width and height of the tunnel section, usually expressed as the ratio of width to height. The sample profile reference aspect ratio here needs to be specifically set according to the actual construction conditions of the tunnel.

[0175] See also Figure 3 , in the sample marked section, mark the intersection points of the sample marked section arc and the straight lines on both sides as the first characteristic marking point and the second characteristic marking point respectively, mark the baseline at the bottom of the section in the sample marked section as the first characteristic baseline, and mark the midpoint of the first characteristic baseline to obtain the third characteristic marking point;

[0176] The first characteristic marking point and the third characteristic marking point are connected to obtain the first characteristic marking line, the second characteristic marking point and the third characteristic marking point are connected to obtain the second characteristic marking line, the angle formed by the first characteristic marking line and the second characteristic marking line at the third characteristic marking point is obtained to obtain the first characteristic angle, and the angle value corresponding to the first characteristic angle is obtained to obtain the arc bottom angle value.

[0177] Obtain the arc bottom angle reference value, calculate the difference between the arc bottom angle value and the arc bottom angle reference value, and take the absolute value of the obtained difference to obtain the arc bottom angle reference difference;

[0178] In the sample marking section, the midpoint of the arc top curve is marked as the fourth characteristic marking point, the first characteristic marking point and the fourth characteristic marking point are connected to obtain the third characteristic marking line, the second characteristic marking point and the fourth characteristic marking point are connected to obtain the fourth characteristic marking line, the angle formed by the third characteristic marking line and the fourth characteristic marking line at the fourth characteristic marking point is obtained to obtain the second characteristic angle, and the angle value corresponding to the first characteristic angle is obtained to obtain the arc top angle value;

[0179] Obtain the arc top angle reference value, calculate the difference between the arc top angle value and the arc top angle reference value, and take the absolute value of the obtained difference to obtain the arc top angle reference difference.

[0180] It should be noted here that:

[0181] The arc bottom angle reference value and arc top angle reference value involved here are the optimal arc bottom angle value and optimal arc top angle value studied by engineering designers based on regional geological conditions.

[0182] The profile geometric structure coefficient corresponding to the sample marked profile is obtained by calculating the profile aspect ratio benchmark deviation, arc bottom angle benchmark difference and arc top angle benchmark difference;

[0183] The cross-section geometric structure coefficient is calculated, and the specific formula is as follows:

[0184] ;

[0185] Among them, Pmj is the section geometry coefficient, Kgb is the reference deviation of the section aspect ratio, Djp is the reference difference of the arc bottom angle, and Ljp is the reference difference of the arc top angle.

[0186] The section geometry coefficients are obtained for each marked section of the target engineering project respectively to obtain a plurality of section geometry coefficients, and the average of the obtained plurality of section geometry coefficients is calculated to obtain an average value of the section geometry coefficients.

[0187] The engineering analysis coefficient corresponding to the target surrounding rock is obtained by calculating the engineering earthwork excavation volume, engineering construction length value and the average value of the section geometric structure coefficient;

[0188] The engineering analysis coefficient is calculated as follows:

[0189] ;

[0190] Among them, Gfx is the engineering analysis coefficient, Kwl is the engineering earth excavation volume, Sgc is the engineering construction length value, and Jgx is the average value of the section geometric structure coefficient.

[0191] The process of obtaining the engineering analysis coefficient corresponding to the target surrounding rock is repeated, and the engineering analysis coefficients corresponding to the first sample monitoring surrounding rock to the p-th sample monitoring surrounding rock are obtained respectively, so as to obtain the first engineering analysis coefficient to the p-th engineering analysis coefficient.

[0192] The engineering analysis coefficient corresponding to the target surrounding rock and the first engineering analysis coefficient to the pth engineering analysis coefficient are defined as surrounding rock engineering data;

[0193] The engineering data module acquires the surrounding rock engineering data and transmits it to the deformation prediction module and the data analysis module;

[0194] The data analysis module obtains surrounding rock prediction analysis data by analyzing surrounding rock engineering data and surrounding rock geological data;

[0195] Obtain surrounding rock geological data, and obtain the first sample monitoring surrounding rock to the p-th sample monitoring surrounding rock, the first sample geological analysis coefficient to the p-th sample geological analysis coefficient, and the regional geological analysis coefficient corresponding to the target surrounding rock according to the surrounding rock geological data.

[0196] Obtaining surrounding rock engineering data, and obtaining engineering analysis coefficients corresponding to target surrounding rock and first to pth engineering analysis coefficients according to the surrounding rock engineering data;

[0197] The structural deformation coefficient corresponding to the target surrounding rock is obtained by calculating the geological analysis coefficient and engineering analysis coefficient corresponding to the target surrounding rock, and is named as the target deformation prediction coefficient.

[0198] The target deformation coefficient is calculated, and the specific formula is as follows:

[0199] ;

[0200] Among them, Mxx is the target deformation coefficient, Dfx is the geological analysis coefficient, and Gfx is the engineering analysis coefficient;

[0201] Repeat the process of obtaining the structural deformation coefficient corresponding to the target surrounding rock, and calculate the structural deformation coefficients corresponding to the first sample monitoring surrounding rock to the p-th sample monitoring surrounding rock according to the first sample geological analysis coefficient to the p-th sample geological analysis coefficient and the first engineering analysis coefficient to the p-th engineering analysis coefficient, and obtain the first deformation prediction coefficient to the p-th deformation prediction coefficient.

[0202] Conduct historical deformation analysis on the surrounding rock monitored by the first sample to obtain the deformation index value of the surrounding rock of the first sample;

[0203] The details are as follows:

[0204] In the historical monitoring period corresponding to the first sample monitoring surrounding rock, the first historical monitoring time point and the second historical monitoring time point are marked respectively, and the first historical monitoring time point and the second historical monitoring time point are separated by a surrounding rock prediction cycle;

[0205] Acquire the engineering project corresponding to the first sample monitoring surrounding rock to obtain the first sample engineering project;

[0206] Draw a base surface auxiliary line on the base surface of the first sample project with the same horizontal direction as the project, select a number of base surface auxiliary points on the base surface auxiliary line, and the distance between each two consecutive base surface auxiliary points is equal;

[0207] A plane perpendicular to the base surface is drawn through each auxiliary point of the base surface to obtain multiple characteristic profiles, and a characteristic profile is randomly selected from the multiple characteristic profiles as a sample characteristic profile.

[0208] Performing a structural analysis on the sample characteristic profile at the first historical monitoring time point, obtaining a profile structure coefficient corresponding to the sample characteristic profile at the first historical monitoring time point, and obtaining a first profile structure coefficient;

[0209] The details are as follows:

[0210] In the sample characteristic profile, the intersection points of the sample characteristic profile arc and the straight lines on both sides are marked as the first characteristic auxiliary point and the second characteristic auxiliary point respectively, the baseline at the bottom of the profile in the sample characteristic profile is marked as the first characteristic baseline, and the midpoint of the first characteristic baseline is marked to obtain the third characteristic auxiliary point;

[0211] The first feature auxiliary point and the third feature auxiliary point are connected to obtain a first feature auxiliary line, the second feature auxiliary point and the third feature auxiliary point are connected to obtain a second feature auxiliary line, the angle formed by the first feature auxiliary line and the second feature auxiliary line at the third feature auxiliary point is obtained to obtain a first feature angle, and the angle value corresponding to the first feature angle is obtained to obtain an arc bottom feature angle;

[0212] In the sample feature profile, the midpoint of the arc top curve is marked as the fourth feature auxiliary point, the first feature auxiliary point and the fourth feature auxiliary point are connected to obtain the third feature auxiliary line, the second feature auxiliary point and the fourth feature auxiliary point are connected to obtain the fourth feature auxiliary line, the angle formed by the third feature auxiliary line and the fourth feature auxiliary line at the fourth feature auxiliary point is obtained to obtain the second feature angle, the angle value corresponding to the first feature angle is obtained to obtain the arc top feature angle.

[0213] The height value of the characteristic profile of the sample is obtained to obtain the profile height value, and the width value of the characteristic profile of the sample is obtained to obtain the profile width value;

[0214] The arc bottom characteristic angle, arc top characteristic angle, profile height value and profile width value are calculated to obtain the profile structure coefficient corresponding to the first historical monitoring time point, and it is named the first profile structure coefficient.

[0215] The first profile structure coefficient corresponding to the sample characteristic profile is calculated. The specific formula is as follows:

[0216] ;

[0217] Among them, Pjx1 is the first section structure coefficient, Hdz is the arc bottom characteristic angle, Hlz is the arc top characteristic angle, Pgz is the section height value, and Pkz is the section width value.

[0218] Obtaining a profile structure coefficient corresponding to the sample characteristic profile at the second historical monitoring time point to obtain a second profile structure coefficient;

[0219] The difference between the first section structure coefficient and the second section structure coefficient is calculated, and the absolute value of the obtained difference is taken to obtain the section deformation deviation coefficient corresponding to the sample characteristic section.

[0220] The profile deformation deviation coefficient corresponding to each characteristic profile is obtained respectively to obtain a plurality of profile deformation deviation coefficients, and the average of the obtained plurality of profile deformation deviation coefficients is calculated to obtain a first sample surrounding rock deformation index value;

[0221] Repeat the process of obtaining the deformation index value of the first sample surrounding rock, respectively obtain the surrounding rock deformation index values ​​corresponding to the second sample monitoring surrounding rock to the p-th sample monitoring surrounding rock, and obtain the second sample surrounding rock deformation index value to the p-th sample surrounding rock deformation index value;

[0222] The first deformation prediction coefficient to the p-th deformation prediction coefficient, the first sample surrounding rock deformation index value to the p-th sample surrounding rock deformation index value, and the target deformation coefficient are defined as surrounding rock prediction analysis data.

[0223] The data analysis module acquires the surrounding rock prediction analysis data and transmits it to the deformation prediction module;

[0224] The deformation prediction module establishes a surrounding rock deformation prediction model based on the surrounding rock prediction analysis data, obtains the target surrounding rock deformation index value by inputting the target deformation coefficient into the surrounding rock deformation prediction model, obtains the surrounding rock deformation index value threshold and compares it with the target surrounding rock deformation index value, and predicts the deformation of the target surrounding rock based on the numerical comparison results.

[0225] Obtain surrounding rock prediction and analysis data, and obtain the first deformation prediction coefficient to the p-th deformation prediction coefficient, the first sample surrounding rock deformation index value to the p-th sample surrounding rock deformation index value and the target deformation coefficient according to the surrounding rock prediction and analysis data.

[0226] Establishing a surrounding rock deformation prediction model according to the first deformation prediction coefficient to the p-th deformation prediction coefficient and the first sample surrounding rock deformation index value to the p-th sample surrounding rock deformation index value;

[0227] The details are as follows:

[0228] Establish a polynomial fitting function by using the first deformation prediction coefficient to the p-th deformation prediction coefficient and the first sample surrounding rock deformation index value to the p-th sample surrounding rock deformation index value;

[0229] The polynomial fitting function is as follows:

[0230] ;

[0231] Among them, y is the surrounding rock deformation index value, x is the deformation prediction coefficient, a0 to a n The coefficients of the polynomial fitting function, n is the order of the polynomial fitting function.

[0232] It should be noted here that:

[0233] In this application, the surrounding rock deformation index value is the dependent variable, and the deformation prediction coefficient is the independent variable.

[0234] Substitute the first deformation prediction coefficient to the p-th deformation prediction coefficient and the first sample surrounding rock deformation index value to the p-th sample surrounding rock deformation index value into the polynomial fitting function respectively, and calculate the residual sum of squares function RSS of the surrounding rock deformation index value;

[0235] The coefficients a0 to a of the polynomial fitting function in the residual sum of squares function RSS are respectively n Calculate partial derivatives and get n unknown numbers a0 to a n Function expression, and convert n unknown numbers a0 to a n The function expressions of are combined to obtain n groups containing a0 to a n The system of equations, and solve the system of equations to obtain a0 to a n Specific value of

[0236] Change a0 to a n The specific value of is substituted back into the polynomial fitting function to obtain the surrounding rock deformation prediction model.

[0237] Assumptions: The first deformation prediction coefficient to the third deformation prediction coefficient are 1, 2, and 3 respectively; the first surrounding rock deformation index value to the third surrounding rock deformation index value are 2, 4, and 6 respectively;

[0238] There are three sets of data points: when x=1, y=2, when x=2, y=3, when x=3, y=6;

[0239] The residual sum of squares (RSS) function is: ;

[0240] in, The model's predicted value at xi, and ;

[0241] Substituting the three sets of data points, we get:

[0242] ;

[0243] Take the partial derivatives of RSS with respect to a0 and a1 respectively, and set them to 0, and we get a0=0, a1=2.

[0244] Substituting the target deformation coefficient into the surrounding rock deformation prediction model, and obtaining the result value output by the surrounding rock deformation prediction model, to obtain the target surrounding rock deformation index value;

[0245] The surrounding rock deformation index threshold is obtained, the target surrounding rock deformation index value is numerically compared with the surrounding rock deformation index threshold, and the deformation of the target surrounding rock is predicted according to the numerical comparison result.

[0246] It should be noted here that:

[0247] The surrounding rock deformation index threshold involved here is a quantitative indicator of structural deformation of the surrounding rock, and the surrounding rock deformation index threshold needs to be specifically set according to actual conditions.

[0248] The details are as follows:

[0249] When the target surrounding rock deformation index value is greater than or equal to the surrounding rock deformation index threshold, it is predicted that the target surrounding rock will have structural deformation;

[0250] When the target surrounding rock deformation index value is less than the surrounding rock deformation index threshold, it is predicted that the target surrounding rock will not experience structural deformation.

[0251] In this application, if corresponding calculation formulas appear, the above calculation formulas are all dimensionless and take their numerical calculations. The weight coefficients, proportional coefficients and other coefficients in the formulas are set to a result value obtained by quantifying each parameter. The size of the weight coefficient and the proportional coefficient can be determined as long as it does not affect the proportional relationship between the parameter and the result value.

[0252] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A surrounding rock structure deformation prediction system based on multi-source information representation, characterized in that: include: Geological data module: select target surrounding rock and multiple sample monitoring surrounding rock respectively, conduct regional geological analysis on the target surrounding rock and multiple sample monitoring surrounding rock respectively, obtain multiple geological analysis coefficients, and define the target surrounding rock, multiple sample monitoring surrounding rock and multiple geological analysis coefficients as surrounding rock geological data; Engineering data module: Perform engineering quantity analysis on target surrounding rock and multiple sample monitoring surrounding rock according to surrounding rock geological data, obtain the engineering earthwork excavation volume, engineering construction length value and profile geometric structure coefficient corresponding to each surrounding rock, and analyze and obtain multiple engineering analysis coefficients to obtain surrounding rock engineering data; Data analysis module: by analyzing the surrounding rock engineering data and surrounding rock geological data, the deformation prediction coefficients corresponding to the target surrounding rock and multiple sample monitoring surrounding rocks are obtained, and the sample surrounding rock deformation index value corresponding to each sample monitoring surrounding rock is obtained to obtain the surrounding rock prediction analysis data; Deformation prediction module: establish a surrounding rock deformation prediction model based on surrounding rock prediction analysis data, obtain the target surrounding rock deformation index value by inputting the target deformation prediction coefficient into the surrounding rock deformation prediction model, obtain the surrounding rock deformation index value threshold and compare it with the target surrounding rock deformation index value, and predict the deformation of the target surrounding rock according to the numerical comparison result; The geological data module acquires surrounding rock geological data, as follows: Mark the surrounding rock coverage area in the regional map to obtain the surrounding rock deformation prediction area, and randomly select a surrounding rock in the surrounding rock deformation prediction area as the target surrounding rock; Randomly select a number of surrounding rocks in the surrounding rock deformation prediction area as sample monitoring surrounding rocks, and name the obtained multiple sample monitoring surrounding rocks as the first sample monitoring surrounding rock to the pth sample monitoring surrounding rock respectively; Conduct regional geological analysis on the target surrounding rock to obtain the regional geological analysis coefficient corresponding to the target surrounding rock; The regional geological analysis coefficients corresponding to the first sample monitoring surrounding rock to the p-th sample monitoring surrounding rock are respectively obtained to obtain the first sample geological analysis coefficient to the p-th sample geological analysis coefficient; The target surrounding rock, the regional geological analysis coefficient corresponding to the target surrounding rock, the first sample monitoring surrounding rock to the p-th sample monitoring surrounding rock, and the first sample geological analysis coefficient to the p-th sample geological analysis coefficient are defined as the surrounding rock geological data.

2. The surrounding rock structure deformation prediction system based on multi-source information characterization according to claim 1 is characterized in that: The geological data module obtains the regional geological analysis coefficients corresponding to the target surrounding rock, as follows: A number of geological survey points with equal distances are randomly selected above the ground surface corresponding to the target surrounding rock, and the direction of the connecting line of the multiple geological survey points is consistent with the direction of the target surrounding rock, and the selected multiple geological survey points are named as the first geological survey point to the i-th geological survey point respectively; Drilling rock cores of the same depth from the first geological exploration point to the i-th geological exploration point respectively to obtain the first geological exploration rock core to the i-th geological exploration rock core; Obtaining the quantity of the selected geological survey points to obtain the quantity value of the geological survey points; Performing structural analysis on the first geological survey core to obtain the depth value of the first rock section to the depth value of the ath rock section; The bottom of the characteristic monitoring core is used as the first core marking point, the top of the characteristic monitoring core is used as the second core marking point, and between the first core marking point and the second core marking point, the same type of structural layer in the characteristic monitoring core is marked as a monitoring rock section, thereby obtaining multiple monitoring rock sections; The length center point corresponding to each monitored rock section is obtained respectively to obtain multiple length center points, the distance value between each length center point and the first core length marking point is calculated, and the obtained multiple distance values ​​are marked from the first rock section depth value to the ath rock section depth value in descending order; Respectively obtaining the first rock section depth value to the ath rock section depth value corresponding to the second geological survey core to the i-th geological survey core; Establish a rock section depth plane rectangular coordinate system by taking the first geological survey core to the i-th geological survey core as the horizontal coordinate and the first rock section depth value to the a-th rock section depth value as the vertical coordinate; Connect each coordinate point corresponding to the first rock section depth value in the rock section depth distribution plane index coordinate to obtain the first rock section depth distribution broken line, connect each coordinate point corresponding to the second rock section depth value to obtain the second rock section depth distribution broken line, and so on, connect each coordinate point corresponding to the a-th rock section depth value to obtain the a-th rock section depth distribution broken line; Analyze the depth distribution line of the first rock section to obtain the number of fractures in the first rock section; Analyze the depth distribution line of the second rock section to the depth distribution line of the ath rock section respectively, and obtain the number of fractures in the second rock section to the number of fractures in the ath rock section; The number of rock section fractures from the first rock section to the ath rock section is summed up to obtain the number of rock section fractures, and the ratio of the number of rock section fractures to the number of geological survey points is calculated to obtain the average number of rock section fractures at the monitoring point; The area covered by the target surrounding rock is obtained to obtain the area value of the target surrounding rock coverage area, and the ratio of the area value of the target surrounding rock coverage area to the average number of rock segment fractures at the monitoring point is calculated to obtain the regional geological analysis coefficient corresponding to the target surrounding rock.

3. The surrounding rock structure deformation prediction system based on multi-source information characterization according to claim 2 is characterized in that: The geological data module obtains the number of fractures in the first rock section as follows: In the first rock section depth distribution polyline, the coordinate point corresponding to the first geological survey core is marked as the first core coordinate point, the coordinate point corresponding to the second geological survey core is marked as the second core coordinate point, and so on, the coordinate point corresponding to the i-1th geological survey core is marked as the i-1th core coordinate point, and the coordinate point corresponding to the i-th geological survey core is marked as the i-th core coordinate point, and the coordinate point from the first core coordinate point to the i-th core coordinate point is obtained; The connection line between the first core coordinate point and the second core coordinate point is marked as the first core coordinate connection line, the connection line between the second core coordinate point and the third core coordinate point is marked as the second core coordinate connection line, and so on, the connection line between the i-1th core coordinate point and the i-th core coordinate point is marked as the i-1th core coordinate connection line, and the first core coordinate connection line to the i-1th core coordinate connection line are obtained; Obtain the slopes of the first core coordinate line to the i-1th core coordinate line to obtain the depth change rate of the first rock section to the i-1th rock section; Obtaining a rock section depth change rate threshold, numerically comparing the first rock section depth change rate to the (i-1)th rock section depth change rate with the rock section depth change rate threshold, if the rock section depth change rate is greater than or equal to the rock section depth change rate threshold, classifying the corresponding rock section depth change rate as a first type of rock section change rate, if the rock section depth change rate is less than the rock section depth change rate threshold, classifying the corresponding rock section depth change rate as a second type of rock section change rate; The number of rock section depth change rates of the first type of rock section change rate from the first rock section depth change rate to the i-1th rock section depth change rate is counted to obtain the number of first rock section fractures.

4. The surrounding rock structure deformation prediction system based on multi-source information characterization according to claim 1 is characterized in that: The engineering data module acquires surrounding rock engineering data, as follows: Obtaining surrounding rock geological data, and obtaining target surrounding rock and first sample monitoring surrounding rock to pth sample monitoring surrounding rock according to the surrounding rock geological data; Conduct engineering quantity analysis on the target surrounding rock and obtain the engineering analysis coefficient corresponding to the target surrounding rock; The details are as follows: Acquire the engineering project corresponding to the target surrounding rock to obtain the target engineering project; The earthwork excavation volume corresponding to the target engineering project is obtained to obtain the engineering earthwork excavation volume; Obtain the engineering construction length corresponding to the target engineering project to obtain the engineering construction length value; Draw a base surface marking line on the base surface of the target project with the same horizontal direction as the project, select a number of base surface marking points on the base surface marking line, and the distance between each two consecutive base surface marking points is equal; The distance value between each base surface marking point and the ground is obtained respectively to obtain multiple base surface marking point depth values, and the average of the obtained multiple base surface marking point depth values ​​is calculated to obtain the average depth value of the project; Each base surface marking point is taken as a plane perpendicular to the base surface to obtain multiple marking sections, and a marking section is randomly selected from the multiple marking sections as a sample marking point section; Performing geometric structure analysis on the sample marked section to obtain the section geometric structure coefficient corresponding to the sample marked section; Obtaining the section geometry coefficient for each marked section of the target engineering project respectively to obtain a plurality of section geometry coefficients, and averaging the obtained plurality of section geometry coefficients to obtain an average value of the section geometry coefficients; The engineering analysis coefficient corresponding to the target surrounding rock is obtained by calculating the engineering earthwork excavation volume, engineering construction length value and the average value of the section geometric structure coefficient; The engineering analysis coefficient is calculated as follows: ； Among them, Gfx is the engineering analysis coefficient, Kwl is the engineering earth excavation volume, Sgc is the engineering construction length value, and Jgx is the average value of the section geometric structure coefficient; The engineering analysis coefficients corresponding to the first sample monitoring surrounding rock to the p-th sample monitoring surrounding rock are respectively obtained to obtain the first engineering analysis coefficient to the p-th engineering analysis coefficient; The engineering analysis coefficient corresponding to the target surrounding rock and the first to pth engineering analysis coefficients are defined as surrounding rock engineering data.

5. The surrounding rock structure deformation prediction system based on multi-source information representation according to claim 4 is characterized in that: The engineering data module obtains the profile geometric structure coefficient corresponding to the sample marked profile, as follows: Acquire the height value of the sample marked section to obtain the sample section height value, acquire the width value of the sample marked section to obtain the sample section width value, calculate the ratio of the sample section width value to the sample section height value to obtain the sample section aspect ratio, and obtain the sample section reference aspect ratio, calculate the difference between the sample section aspect ratio and the sample section reference aspect ratio, and take the absolute value of the obtained difference to obtain the section aspect ratio reference deviation; In the sample marked section, the intersection points of the sample marked section arc and the straight lines on both sides are marked as the first characteristic marking point and the second characteristic marking point respectively, the baseline at the bottom of the section in the sample marked section is marked as the first characteristic baseline, and the midpoint of the first characteristic baseline is marked to obtain the third characteristic marking point; The first characteristic marking point and the third characteristic marking point are connected to obtain a first characteristic marking line, the second characteristic marking point and the third characteristic marking point are connected to obtain a second characteristic marking line, the angle formed by the first characteristic marking line and the second characteristic marking line at the third characteristic marking point is obtained to obtain a first characteristic angle, and the angle value corresponding to the first characteristic angle is obtained to obtain an arc bottom angle value; Obtain the arc bottom angle reference value, calculate the difference between the arc bottom angle value and the arc bottom angle reference value, and take the absolute value of the obtained difference to obtain the arc bottom angle reference difference; In the sample marking section, the midpoint of the arc top curve is marked as the fourth characteristic marking point, the first characteristic marking point and the fourth characteristic marking point are connected to obtain the third characteristic marking line, the second characteristic marking point and the fourth characteristic marking point are connected to obtain the fourth characteristic marking line, the angle formed by the third characteristic marking line and the fourth characteristic marking line at the fourth characteristic marking point is obtained to obtain the second characteristic angle, and the angle value corresponding to the second characteristic angle is obtained to obtain the arc top angle value; Obtaining the arc top angle reference value, calculating the difference between the arc top angle value and the arc top angle reference value, and taking the absolute value of the obtained difference to obtain the arc top angle reference difference; The profile geometric structure coefficient corresponding to the sample marked profile is obtained by calculating the profile aspect ratio benchmark deviation, arc bottom angle benchmark difference and arc top angle benchmark difference; The cross-section geometric structure coefficient is calculated, and the specific formula is as follows: ； Among them, Pmj is the section geometry coefficient, Kgb is the reference deviation of the section aspect ratio, Djp is the reference difference of the arc bottom angle, and Ljp is the reference difference of the arc top angle.

6. The surrounding rock structure deformation prediction system based on multi-source information representation according to claim 1 is characterized in that: The engineering data module acquires surrounding rock prediction and analysis data, as follows: Obtain surrounding rock geological data, and obtain the first sample monitoring surrounding rock to the p-th sample monitoring surrounding rock, the first sample geological analysis coefficient to the p-th sample geological analysis coefficient, and the regional geological analysis coefficient corresponding to the target surrounding rock according to the surrounding rock geological data; Obtaining surrounding rock engineering data, and obtaining engineering analysis coefficients corresponding to target surrounding rock and first to pth engineering analysis coefficients according to the surrounding rock engineering data; The structural deformation coefficient corresponding to the target surrounding rock is obtained by calculating the geological analysis coefficient and the engineering analysis coefficient corresponding to the target surrounding rock, and is named as the target deformation prediction coefficient; The target deformation prediction coefficient is calculated, and the specific formula is as follows: ； Among them, Mxx is the target deformation prediction coefficient, Dfx is the geological analysis coefficient, and Gfx is the engineering analysis coefficient; According to the first sample geological analysis coefficient to the p-th sample geological analysis coefficient and the first engineering analysis coefficient to the p-th engineering analysis coefficient, the structural deformation coefficients corresponding to the first sample monitoring surrounding rock to the p-th sample monitoring surrounding rock are calculated, and the first deformation prediction coefficient to the p-th deformation prediction coefficient are obtained; Conduct historical deformation analysis on the surrounding rock monitored by the first sample to obtain the deformation index value of the surrounding rock of the first sample; Obtain the surrounding rock deformation index values ​​corresponding to the second sample monitoring surrounding rock to the p-th sample monitoring surrounding rock respectively, and obtain the second sample surrounding rock deformation index value to the p-th sample surrounding rock deformation index value; The first deformation prediction coefficient to the p-th deformation prediction coefficient, the first sample surrounding rock deformation index value to the p-th sample surrounding rock deformation index value, and the target deformation prediction coefficient are defined as surrounding rock prediction analysis data.

7. The surrounding rock structure deformation prediction system based on multi-source information representation according to claim 6 is characterized in that: The engineering data module obtains the deformation index value of the surrounding rock of the first sample, as follows: In the historical monitoring period corresponding to the first sample monitoring surrounding rock, the first historical monitoring time point and the second historical monitoring time point are marked respectively, and the first historical monitoring time point and the second historical monitoring time point are separated by a surrounding rock prediction cycle; Acquire the engineering project corresponding to the first sample monitoring surrounding rock to obtain the first sample engineering project; Draw a base surface auxiliary line on the base surface of the first sample project with the same horizontal direction as the project, select a number of base surface auxiliary points on the base surface auxiliary line, and the distance between each two consecutive base surface auxiliary points is equal; A plane perpendicular to the base surface is drawn through each auxiliary point of the base surface to obtain multiple characteristic profiles, and a characteristic profile is randomly selected from the multiple characteristic profiles as a sample characteristic profile; Performing a structural analysis on the sample characteristic profile at the first historical monitoring time point, obtaining a profile structure coefficient corresponding to the sample characteristic profile at the first historical monitoring time point, and obtaining a first profile structure coefficient; Obtaining a profile structure coefficient corresponding to the sample characteristic profile at the second historical monitoring time point to obtain a second profile structure coefficient; The difference between the first section structure coefficient and the second section structure coefficient is calculated, and the absolute value of the obtained difference is taken to obtain the section deformation deviation coefficient corresponding to the sample characteristic section; The profile deformation deviation coefficient corresponding to each characteristic profile is obtained respectively to obtain a plurality of profile deformation deviation coefficients, and the average of the obtained plurality of profile deformation deviation coefficients is calculated to obtain the first sample surrounding rock deformation index value.

8. The surrounding rock structure deformation prediction system based on multi-source information representation according to claim 7 is characterized in that: The engineering data module obtains the first section structure coefficient, as follows: In the sample characteristic profile, the intersection points of the sample characteristic profile arc and the straight lines on both sides are marked as the first characteristic auxiliary point and the second characteristic auxiliary point respectively, the baseline at the bottom of the profile in the sample characteristic profile is marked as the first characteristic baseline, and the midpoint of the first characteristic baseline is marked to obtain the third characteristic auxiliary point; The first feature auxiliary point and the third feature auxiliary point are connected to obtain a first feature auxiliary line, the second feature auxiliary point and the third feature auxiliary point are connected to obtain a second feature auxiliary line, the angle formed by the first feature auxiliary line and the second feature auxiliary line at the third feature auxiliary point is obtained to obtain a first feature angle, and the angle value corresponding to the first feature angle is obtained to obtain an arc bottom feature angle; In the sample characteristic profile, the midpoint of the arc top curve is marked as the fourth characteristic auxiliary point, the first characteristic auxiliary point and the fourth characteristic auxiliary point are connected to obtain the third characteristic auxiliary line, the second characteristic auxiliary point and the fourth characteristic auxiliary point are connected to obtain the fourth characteristic auxiliary line, the angle formed by the third characteristic auxiliary line and the fourth characteristic auxiliary line at the fourth characteristic auxiliary point is obtained to obtain the second characteristic angle, and the angle value corresponding to the second characteristic angle is obtained to obtain the arc top characteristic angle; The height value of the characteristic profile of the sample is obtained to obtain the profile height value, and the width value of the characteristic profile of the sample is obtained to obtain the profile width value; The arc bottom characteristic angle, arc top characteristic angle, profile height value and profile width value are calculated to obtain the profile structure coefficient corresponding to the first historical monitoring time point, and the profile structure coefficient is named as the first profile structure coefficient; The first profile structure coefficient corresponding to the sample characteristic profile is calculated. The specific formula is as follows: ； Among them, Pjx1 is the first section structure coefficient, Hdz is the arc bottom characteristic angle, Hlz is the arc top characteristic angle, Pgz is the section height value, and Pkz is the section width value.

9. The surrounding rock structure deformation prediction system based on multi-source information representation according to claim 1 is characterized in that: The deformation prediction module predicts the deformation of the target surrounding rock, as follows: Obtain surrounding rock prediction and analysis data, and obtain first to p-th deformation prediction coefficients, first to p-th sample surrounding rock deformation index values, and a target deformation prediction coefficient according to the surrounding rock prediction and analysis data; Establishing a surrounding rock deformation prediction model according to the first deformation prediction coefficient to the p-th deformation prediction coefficient and the first sample surrounding rock deformation index value to the p-th sample surrounding rock deformation index value; The details are as follows: Establish a polynomial fitting function by using the first deformation prediction coefficient to the p-th deformation prediction coefficient and the first sample surrounding rock deformation index value to the p-th sample surrounding rock deformation index value; The polynomial fitting function is as follows: ； Among them, y is the surrounding rock deformation index value, x is the deformation prediction coefficient, a0 to a n The coefficients of the polynomial fitting function, n is the order of the polynomial fitting function; Substitute the first deformation prediction coefficient to the p-th deformation prediction coefficient and the first sample surrounding rock deformation index value to the p-th sample surrounding rock deformation index value into the polynomial fitting function respectively, and calculate the residual sum of squares function RSS of the surrounding rock deformation index value; The coefficients a0 to a of the polynomial fitting function in the residual sum of squares function RSS are respectively n Calculate partial derivatives and obtain n unknown numbers a0 to a n Function expression, and convert n unknown numbers a0 to a n The function expressions of are combined to obtain n groups containing a0 to a n The system of equations, and solve the system of equations to obtain a0 to a n Specific value of Change a0 to a n The specific value of is substituted back into the polynomial fitting function to obtain the surrounding rock deformation prediction model; Substituting the target deformation prediction coefficient into the surrounding rock deformation prediction model, and obtaining the result value output by the surrounding rock deformation prediction model to obtain the target surrounding rock deformation index value; Obtaining a surrounding rock deformation index threshold, numerically comparing the target surrounding rock deformation index value with the surrounding rock deformation index threshold, and predicting the deformation of the target surrounding rock according to the numerical comparison result; The details are as follows: When the target surrounding rock deformation index value is greater than or equal to the surrounding rock deformation index threshold, it is predicted that the target surrounding rock will have structural deformation; When the target surrounding rock deformation index value is less than the surrounding rock deformation index threshold, it is predicted that the target surrounding rock will not experience structural deformation.

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