Tunnel surrounding rock stability discrimination method and system based on multi-source information

Abstract

The present application mainly relates to the technical field of tunnel engineering, in order to improve the accuracy and real-time of surrounding rock stability discrimination, the present application provides a kind of tunnel surrounding rock stability discrimination method and system based on multi-source information, its core is: with surrounding rock mass strength and stability index as basic stability discrimination factor, while considering groundwater influence correction coefficient, structure surface occurrence influence correction coefficient, initial stress state influence correction coefficient as the influence of disturbance factor on basic stability, establish surrounding rock stability index calculation model, based on body strength compression index real-time adjustment high rock mass strength on the nonlinear leading degree of basic stability calculation result, correct basic stability, based on correction coefficient coupling coefficient consider the mutual influence between three correction coefficients, correct disturbance factor, so that surrounding rock stability index calculation model can better adapt to the geological environment under complex changes.

Description

TECHNICAL FIELD

[0001] The present application mainly relates to the technical field of tunnel engineering, in particular to a tunnel surrounding rock stability discrimination method and system based on multi-source information. BACKGROUND

[0002] Traditional tunnel surrounding rock stability discrimination is mainly based on one or two indexes obtained during tunneling by a tunneling machine, such as rock mass strength, rock mass integrity, one or two of the tunneling parameters, but the stability of surrounding rock is a problem affected by the coupling of multiple factors, and it is difficult to accurately discriminate the stability of the surrounding rock in front during tunneling and give early warning by relying on real-time collection of one or two indexes and judging the stability of surrounding rock according to various indexes alone, ignoring the interaction between various index factors. Therefore, production accidents often occur due to inaccurate prediction of the stability of surrounding rock during tunneling, affecting the efficiency and safety of tunneling machine construction, delaying the construction period, and causing serious economic losses.

[0003] At the same time, there are also methods for evaluating the stability of surrounding rock using multiple indexes, mainly the BQ method (engineering rock mass classification standard method). Although the BQ method has the advantages of rigorous system, strong operability, and good correlation with the RMR method, it also has the following main defects in actual application:

[0004] (1) The traditional BQ method and RMR method are static evaluations before construction, which rely on construction experience and cannot respond to geological mutations during tunneling;

[0005] (2) The traditional BQ method and RMR method often treat each correction coefficient as an independent multiplier, ignoring the mutual influence between correction coefficients;

[0006] (3) It cannot evaluate the deviation of rock mass damage evolution theory and correct the nonlinear effects of water-stress coupling, and is not suitable for complex geological environments. SUMMARY

[0007] The technical problem to be solved by the present application is to provide a tunnel surrounding rock stability discrimination method and system based on multi-source information, aiming to improve the accuracy and real-time performance of surrounding rock stability discrimination.

[0008] The technical solution adopted by the present application to solve the above technical problem is:

[0009] On the one hand, the present application provides a tunnel surrounding rock stability discrimination method based on multi-source information, which comprises:

[0010] determining the basic stability of surrounding rock based on rock mass strength , integrity coefficient and rock mass strength compression index determining the basic stability of surrounding rock based on rock mass strength Method for adjusting rock mass strength Dominance degree of the calculation result of the foundation stability;

[0011] Correction coefficient based on groundwater influence , correction coefficient based on structure surface occurrence , correction coefficient based on initial stress state , and coupling amplification coefficient of correction coefficients Calculate disturbance factor, the coupling amplification coefficient of correction coefficients for controlling the correction coefficient based on groundwater influence , the correction coefficient based on structure surface occurrence , the correction coefficient based on initial stress state Amplification degree of the calculation result of the disturbance factor by the superposition effect of the correction coefficients;

[0012] Establish the surrounding rock stability index calculation model based on the foundation stability and the disturbance factor;

[0013] Real-time calculation of the target surrounding rock stability index based on the surrounding rock stability index calculation model, and determination of the stability degree of the surrounding rock according to the stability index.

[0014] Further, the foundation stability is:

[0015] , ;

[0016] ;

[0017] Wherein is the first residual, representing the difference between the true strength compression index and the rock mass strength compression index foundation value , is the change amount of the rock mass strength in a set time.

[0018] Further, the disturbance factor is:

[0019] ;

[0020] ;

[0021] ;

[0022] Wherein is the second residual, representing the difference between the true value of the coupling amplification coefficient of correction coefficients and the foundation value of the coupling amplification coefficient of correction coefficients .

[0023] Furthermore, the calculation model for the surrounding rock stability evaluation index is as follows:

[0024] ;

[0025] This represents the stability index of the surrounding rock.

[0026] Furthermore, the first residual The method for obtaining the data is as follows: A first residual prediction model is established based on random forest or LightGBM, using rock mass strength as the basis. Integrity coefficient rock mass strength variation and brittleness index ( ) is the input feature, and the first residual is... The true values ​​are used as the true labels to train the first residual prediction model. The output of the first residual prediction result is compared with the true labels, the corresponding loss function is calculated, the first residual prediction model is optimized, and the optimized model is used as the trained residual parameter prediction model.

[0027] Furthermore, the second residual The method for obtaining the data is as follows: a second residual prediction model is established based on random forest or LightGBM, using the groundwater influence correction coefficient of the surrounding rock. Correction coefficient for the influence of structural surface attitude Correction factor for the influence of initial stress state , , , perturbation entropy , , , min of the mean ( Rock mass integrity coefficient Change over a set time period For input features, the second residual The true values ​​are used as the true labels to train the second residual prediction model. The second residual prediction results are compared with the true labels, the corresponding loss function is calculated, the second residual prediction model is optimized, and the optimized model is used as the trained second residual parameter prediction model.

[0028] Furthermore, groundwater correction factor The acquisition method is as follows: acquire surrounding rock images, preprocess the surrounding rock images, identify the seepage area on the surface of the surrounding rock based on the preprocessed images, and divide the range of wet or point-like water outflow, rain-like or line-like water outflow, and gushing water outflow.

[0029] ;

[0030] in For the first The area of ​​the water outlet within each unit measurement area. The number of samples measured on the surface of the surrounding rock. This represents the lower limit of the range of BQ values ​​corresponding to different seepage types.

[0031] Furthermore, the rock mass strength The calculations include: or ,in For the total thrust of the TBM, This refers to the cutter head torque.

[0032] On the other hand, the present invention also provides a tunnel surrounding rock stability discrimination system based on multi-source information. The system includes a data acquisition module, a basic stability calculation module, a disturbance factor calculation module, and a surrounding rock stability discrimination module.

[0033] The data acquisition module is used to acquire the strength of the surrounding rock mass. Integrity coefficient Rock mass strength compression index Groundwater impact correction factor Correction coefficient for the influence of structural surface attitude Correction factor for the influence of initial stress state Coupling amplification factor and correction factor ;

[0034] The basic stability calculation module is used to calculate the stability based on the strength of the surrounding rock mass. Integrity coefficient and rock mass strength compressibility index Determine the foundation stability of the surrounding rock;

[0035] The disturbance factor calculation module is used to calculate the groundwater influence correction coefficient. Correction coefficient for the influence of structural surface attitude Correction factor for the influence of initial stress state Coupling amplification factor and correction factor The disturbance factor that affects the basic stability;

[0036] The surrounding rock stability discrimination module is used to calculate the surrounding rock stability index based on the basic stability and disturbance factor of the surrounding rock, and to judge the stability of the surrounding rock based on the surrounding rock stability index.

[0037] The beneficial effects of this invention are:

[0038] (1) Based on multiple geological influence parameters, the surrounding rock stability index calculation model is established to cooperatively and dynamically determine the surrounding rock stability, comprehensively considers the influence of the interaction between multiple geological influence parameters on the surrounding rock stability, and compresses the rock mass strength based on the rock mass strength compression index in real time adjustment of rock mass strength The nonlinear dominant degree of the foundation stability calculation result is corrected, and the disturbance factor is corrected according to the correction coefficient coupling coefficient The mutual influence between the three correction coefficients is considered, the disturbance factor is corrected, the influence degree of the three disturbance coefficients in the surrounding rock stability index calculation is balanced, and the surrounding rock stability index calculation model can better adapt to the geological environment under complex changes.

[0039] (2) In the process of obtaining the rock mass strength compression index and the correction coefficient coupling coefficient , not only the influence of each geological parameter itself is considered, but also the machine learning model training is cooperatively performed by adding multiple derivative parameters of each geological parameter, a first residual prediction model and a second residual prediction model are established, and the values of the rock mass strength compression index and the correction coefficient coupling coefficient are more accurately obtained based on the first residual prediction model and the second residual prediction model, so that the interaction degree between various geological influence parameters is more accurately reflected, and more accurate surrounding rock stability determination results are obtained. BRIEF DESCRIPTION OF DRAWINGS

[0040] Figure 1 The tunnel surrounding rock stability determination method based on multiple source information described in the present application is a flow chart. DETAILED DESCRIPTION

[0041] The core of the tunnel surrounding rock stability determination method based on multiple source information described in the present application to solve the above technical problems is that the rock mass strength and the stability index are used as the basic stability determination factors, the influences of the three disturbance factors, i.e., the groundwater influence correction coefficient , the structure surface occurrence influence correction coefficient , and the initial stress state influence correction coefficient on the basic stability are considered, the surrounding rock stability index calculation model is established, the surrounding rock stability is cooperatively and dynamically determined based on multiple geological influence parameters, the influences of the interaction between multiple geological influence parameters on the surrounding rock stability are comprehensively considered, and the rock mass strength is compressed based on the rock mass strength compression index in real time adjustment of rock mass strength The nonlinear dominant degree of the calculation result of the foundation stability is corrected, and the coupling coefficient is coupled according to the correction coefficient in the calculation of the disturbance factor The mutual influence among the three correction coefficients is considered, the disturbance factor is corrected, the influence of the mutual action among various geological influence parameters on the stability degree of the surrounding rock is considered, and the surrounding rock stability index calculation model can better adapt to the geological environment under complex changes.

[0042] As shown in Figure 1 The tunnel surrounding rock stability discrimination method based on multi-source information comprises the following processes.

[0043] S1: determining the groundwater influence correction coefficient .

[0044] A plurality of fixed cameras are arranged on both sides of the TBM main beam, and TBM tunnel surrounding rock surface images are automatically and real-timely collected for a long time. Generally, in the TBM construction process, the surrounding rock condition of the upper half of the tunnel has the greatest influence on the stability of the whole tunnel, so the image pictures of the upper half of the tunnel can be collected. After the pictures are collected, the pictures of different fields of view are integrated by using the picture three-dimensional reconstruction unfolding method to eliminate the distortion error caused by the tunnel arc shape. Based on the images after distortion processing, the surrounding rock surface seepage water area range is identified, the three states (wet or point water outflow, rain or linear water outflow, gushing water outflow) of the groundwater outflow are distinguished, and the specific value of is calculated. , wherein is the water outflow area in the first unit measurement area, is the sample number of the surrounding rock surface measurement, and the lower limit of the value interval of the BQ value corresponding to different water seepage types is confirmed through the identified groundwater outflow state. The specific calculation process of the groundwater influence correction coefficient can be obtained according to the content disclosed in the TBM tunnel construction stage surrounding rock stability intelligent discrimination method research.

[0045] In this embodiment, the surrounding rock surface seepage water area range is identified based on an algorithm model with picture segmentation function such as FCN, U-Net or Mask R-CNN.

[0046] S2: obtaining the structure surface occurrence influence correction coefficient .

[0047] By the difference between the structural plane and the conventional surrounding rock pixels in the surrounding rock image, the structural plane is identified and the surrounding rock structural plane boundary contour is described, the structural plane condition most affecting the surrounding rock stability is determined by combining the site construction conditions, the influence is considered by one or more indexes of structural plane length, width and area, the structural plane most affecting the surrounding rock stability is determined, and the position and trend of the structural plane are recorded, the inclination of the structural plane and the angle between the structural plane trend line and the tunnel axis are calculated in real time based on the recorded structural plane position and trend and the construction record tunnel axis, and finally the inclination and the angle are combined with the BQ method standard to obtain the structural plane occurrence influence correction coefficient .

[0048] S3: Obtain the initial stress state correction coefficient of surrounding rock .

[0049] The intelligent anchor rod integrated sensor is arranged on the TBM tunneling machine, the sensor is embedded in the supporting anchor rod, the rock mass stress is synchronously perceived, and the stress value is collected in real time. The arrangement interval of the intelligent anchor rod integrated sensor can be determined according to the complexity of the geological conditions and the stability of the surrounding rock, and the arrangement interval can be selected as 1 m in the complex and changeable geological conditions, that is, the intelligent anchor rod integrated sensor is re-arranged every 1 m to perform real-time monitoring of the rock mass stress, the arrangement interval is determined by the site personnel, and finally the monitored ground stress is combined with the BQ method standard to obtain the initial stress state correction coefficient .

[0050] S4: Obtain the rock mass strength of surrounding rock .

[0051] The running parameters generated during TBM excavation are collected in real time by the sensor, the running parameters at least include at least one of total thrust, cutter head torque, advancing speed, penetration and cutter head speed, and the rock mass strength is obtained based on the total thrust, cutter head torque, advancing speed, penetration or cutter head speed. The rock mass strength calculation method based on the cutter head torque is , is the cutter head torque; the rock mass strength calculation method based on the total thrust is , is the total thrust.

[0052] S5: Obtain the integrity coefficient of surrounding rock .

[0053] The image of the slag is collected, a camera is arranged above the belt slag conveyor according to the slag discharge mode of the on-site belt, and a light supplement device is matched to collect a high-definition slag image, the camera collection frequency can be adjusted in real time according to the running speed of the conveyor, the two-dimensional image of the slag is converted into a three-dimensional shape through a slag shape equivalent method, the slag grading information (one of the four characteristic parameters of the curvature coefficient, the uneven coefficient, the maximum particle size and the roughness index) is obtained according to the converted shape, and the slag grading information is input into the subsequent rock mass integrity identification model. The model can be based on but not limited to the following types: linear, logarithmic, inverse, quadratic, power, composite, S-curve and growth, and the relationship between rock mass integrity and slag grading parameters is fitted, so that the rock mass integrity index can be output in real time after the slag grading information is input , and the value is transmitted in real time to the surrounding rock stability real-time judgment and early warning system.

[0054] S6: Determine the basic stability of the surrounding rock based on the rock mass strength , the integrity coefficient and the rock mass strength compression index .

[0055] In this embodiment, the basic stability of the surrounding rock is defined as: , the rock mass strength compression index is used to adjust the dominant degree of high rock mass strength on the calculation result of the basic stability.

[0056] The rock mass strength compression index is: ; ; wherein the first residual error is the difference between the true strength compression index and the rock mass strength compression index basic value , is the rock mass strength variation.

[0057] The first residual error mainly reflects the deficiency of the rock mass strength characteristic description of the surrounding rock stability index calculation model. Since high rock mass strength usually means that the rock mass hardness is high, but if the actual rock mass contains hidden cracks, the surrounding rock stability index calculation model may overestimate its strength contribution, resulting in the first residual error less than 0, the integrity coefficient low indicates the degree of rock mass fragmentation, and the surrounding rock stability index calculation model has been considered by the term in the rock mass strength compression index basic value , but if the actual fragmentation degree exceeds the expectation (such as the hidden cleavage of the excavation stratum), the strength compression index needs to be further reduced. ( (less than 0), rock mass A sharp drop may indicate a fault or alteration zone. The surrounding rock stability index calculation model does not respond adequately to this, and it is necessary to further reduce the rock mass strength compressibility index. ( Less than 0), to quickly reflect the loss of rock mass strength, brittleness index ( A high value indicates that the rock mass is prone to brittle failure. The surrounding rock stability index calculation model does not directly consider brittleness; therefore, it is necessary to reduce the surrounding rock strength compressibility index. To enhance sensitivity to brittle fracture. (less than 0), therefore in the first residual The rock mass strength needs to be considered during the acquisition process. Integrity coefficient rock mass strength variation and brittleness ( The impact of ).

[0058] First residual The acquisition method is as follows: A first residual prediction model is established based on random forest or LightGBM, using rock mass strength as the basis. Integrity coefficient rock mass strength variation and brittleness index ( ) is the input feature, and the first residual is... Using the true label as the real label, the first residual prediction model is trained. The output of the first residual prediction result is compared with the real label, the corresponding loss function is calculated, the first prediction model is effectively optimized, and the optimized model is used as the trained residual parameter prediction model.

[0059] The first residual, used as the true label in the training of the first residual prediction model. The true value is obtained by inverting the true strength compression index from the actual monitored surrounding rock deformation values. Basic value of rock mass strength compressibility index The difference between them, or directly based on experience, can be used to assign values.

[0060] S7: Determine the groundwater impact correction factor Correction coefficient for the influence of structural surface attitude Correction factor for the influence of initial stress state Correction coefficient and coupling amplification coefficient The disturbance factor that affects the basic stability.

[0061] The disturbance factor mentioned in this embodiment is: Correction factor, coupling amplification factor For controlling the amplification degree of the superposition effect of multiple correction coefficients on the calculation result of disturbance factors.

[0062] The correction coefficient coupling amplification coefficient , , wherein is a second residual error, representing the difference between the true value of the correction coefficient coupling amplification coefficient and the base value .

[0063] The second residual error mainly reflects the modeling deficiency of the correction coefficient coupling effect, when the groundwater influence correction coefficient , the structural plane occurrence influence correction coefficient , and the initial stress state influence correction coefficient are all low and balanced (such as high disturbance entropy ), the synergistic effect of the surrounding rock stability index calculation model may be underestimated, and the correction coefficient coupling amplification coefficient ( greater than 0) needs to be increased; in a high ground stress environment, the initial stress state influence correction coefficient is low, and the influences of the groundwater influence correction coefficient and the structural plane occurrence influence correction coefficient are nonlinearly amplified, and the nonlinearities of the three correction coefficients may be underestimated when the surrounding rock stability index calculation model predicts the stability index, and the correction coefficient coupling amplification coefficient ( greater than 0) needs to be increased. When the three correction coefficients are close and all low, the synergistic effect of the disturbance factors is strong, and the simple coupling term of the surrounding rock stability index calculation model may not be enough to describe this synergy, and the correction coefficient coupling amplification coefficient ( greater than 0) needs to be increased significantly. If the historical correction coefficient value is continuously low, indicating that it has been in a high-risk state for a long time, the surrounding rock stability index calculation model may underestimate the cumulative effect of the disturbance, and the correction coefficient coupling amplification coefficient ( greater than 0) needs to be increased. The decrease of the complete coefficient amplifies the disturbance effect (for example, the structural plane is more sensitive to groundwater), and although the surrounding rock stability index calculation model considers the term in , if the rapidly decreases, the actual amplification may exceed the expectation, and the needs to be adjusted ( greater than 0). Therefore, the prediction of the second residual error needs to consider the groundwater influence correction coefficient , the structural plane occurrence influence correction coefficient , and the initial stress state influence correction coefficient , disturbance entropy , , , , the mean min( ), rock mass integrity coefficient the change amount within the set time influence.

[0064] second residual error The acquisition method is: based on random forest or LightGBM to establish a second residual error prediction model, the groundwater influence correction coefficient , the structure surface occurrence influence correction coefficient , the initial stress state influence correction coefficient , disturbance entropy , , , , the mean min( ), rock mass integrity coefficient is input feature, the true value of the second residual error as the real label, train the second residual error prediction model, compare the second residual error prediction result with the real label, calculate the corresponding loss function, effectively optimize the second residual error prediction model, and the optimized model is used as the trained second residual error parameter prediction model.

[0065] The true value of the second residual error as the real label in the training of the second residual error prediction model is obtained by subtracting the dynamic adjustment parameter base value from the optimal correction coefficient coupling amplification coefficient inverted from the actual monitoring of the surrounding rock deformation value, or is valued based on experience.

[0066] S8: Establish a surrounding rock stability index calculation model based on the basic stability and the disturbance factor.

[0067] In this embodiment, the surrounding rock stability evaluation index calculation model is:

[0068] ;

[0069] represents the surrounding rock stability index.

[0070] S9: Real-time calculate the target surrounding rock stability index based on the surrounding rock stability index calculation model, and determine the stability degree of the surrounding rock according to the stability index.

[0071] The tunnel surrounding rock stability discrimination system based on multi-source information comprises a data acquisition module, a basic stability calculation module, a disturbance factor calculation module and a surrounding rock stability discrimination module.

[0072] The data acquisition module is used for acquiring surrounding rock mass strength , integrity coefficient , rock mass strength compression index , groundwater influence correction coefficient , structure surface occurrence influence correction coefficient , initial stress state influence correction coefficient and correction coefficient coupling amplification coefficient .

[0073] The basic stability calculation module is used for determining the basic stability of surrounding rock based on surrounding rock mass strength , integrity coefficient and rock mass strength compression index .

[0074] The disturbance factor calculation module is used for calculating the disturbance factor of the basic stability based on groundwater influence correction coefficient , structure surface occurrence influence correction coefficient , initial stress state influence correction coefficient and correction coefficient coupling amplification coefficient .

[0075] The surrounding rock stability discrimination module is used for calculating the surrounding rock stability index according to the basic stability of surrounding rock and the disturbance factor, and judging the stability degree of surrounding rock according to the surrounding rock stability index.

[0076] Finally, the application further provides a tunneling machine for dynamic discrimination of surrounding rock stability based on multi-source information, which comprises the above-mentioned dynamic discrimination system of surrounding rock stability based on multi-source information.

Claims

1. A method for determining the stability of surrounding rock in tunnels based on multi-source information, characterized in that, The method includes Based on the strength of the surrounding rock mass Integrity coefficient and rock mass strength compressibility index Determine the basic stability of the surrounding rock and the rock mass strength compressibility index. Used to adjust rock mass strength The degree to which the results of the basic stability calculation are dominated; The basic stability is: ; ; ;in The first residual represents the true strength compression index. Basic value of rock mass strength compressibility index The difference between them rock mass strength The amount of change within a set time period; Based on groundwater influence correction factor Correction coefficient for the influence of structural surface attitude Correction factor for the influence of initial stress state Coupling amplification factor and correction factor Calculate the disturbance factor, the correction coefficient, and the coupling amplification coefficient. Correction factor for controlling groundwater influence Correction coefficient for the influence of structural surface attitude Correction factor for the influence of initial stress state The degree to which the superposition effect amplifies the calculation result of the perturbation factor; the perturbation factor is: ; ; ;in The second residual represents the true value of the correction factor and the coupling amplification factor. The base value of the coupling amplification factor with the correction factor The difference between them; A calculation model for the surrounding rock stability index is established based on the fundamental stability and disturbance factor; the calculation model for the surrounding rock stability index is as follows: , Indicates the stability index of the surrounding rock; The stability index of the target surrounding rock is calculated in real time based on the surrounding rock stability index calculation model, and the stability degree of the surrounding rock is determined according to the stability index.

2. The tunnel surrounding rock stability discrimination method based on multi-source information according to claim 1, characterized in that, First residual The method for obtaining the data is as follows: A first residual prediction model is established based on random forest or LightGBM, using rock mass strength as the basis. Integrity coefficient rock mass strength variation and brittleness index ( ) is the input feature, and the first residual is... The true values ​​are used as the true labels to train the first residual prediction model. The output of the first residual prediction result is compared with the true labels, the corresponding loss function is calculated, the first residual prediction model is optimized, and the optimized model is used as the trained residual parameter prediction model.

3. The method for determining the stability of tunnel surrounding rock based on multi-source information according to claim 1, characterized in that, Second residual The method for obtaining the data is as follows: a second residual prediction model is established based on random forest or LightGBM, using the groundwater influence correction coefficient of the surrounding rock. Correction coefficient for the influence of structural surface attitude Correction factor for the influence of initial stress state , , , perturbation entropy , , , min of the mean ( Rock mass integrity coefficient Change over a set time period For input features, the second residual The true values ​​are used as the true labels to train the second residual prediction model. The second residual prediction results are compared with the true labels, the corresponding loss function is calculated, the second residual prediction model is optimized, and the optimized model is used as the trained second residual parameter prediction model.

4. The method for determining the stability of tunnel surrounding rock based on multi-source information according to claim 1, characterized in that, Groundwater correction factor The acquisition includes: acquiring surrounding rock images, preprocessing the surrounding rock images, identifying the range of seepage areas on the surface of the surrounding rock based on the preprocessed images, and dividing the range of water seepage such as dampness or point-like water, rain-like or linear water, and gushing water. ； in For the first The area of ​​the water outlet within each unit measurement area The number of samples measured on the surface of the surrounding rock. This represents the lower limit of the range of BQ values ​​corresponding to different seepage types.

5. The method for determining the stability of tunnel surrounding rock based on multi-source information according to claim 1, characterized in that, The rock mass strength The calculation method is as follows: or Where F is the total thrust of the TBM and T is the cutterhead torque.

6. A tunnel surrounding rock stability discrimination system based on multi-source information, used to implement the tunnel surrounding rock stability discrimination method based on multi-source information as described in any one of claims 1-5, characterized in that, The system includes a data acquisition module, a basic stability calculation module, a disturbance factor calculation module, and a surrounding rock stability discrimination module. The data acquisition module is used to acquire the strength of the surrounding rock mass. Integrity coefficient Rock mass strength compression index Groundwater impact correction factor Correction coefficient for the influence of structural surface attitude Correction factor for the influence of initial stress state Coupling amplification factor and correction factor ; The basic stability calculation module is used to calculate the stability based on the strength of the surrounding rock mass. Integrity coefficient and rock mass strength compressibility index Determine the foundation stability of the surrounding rock; The disturbance factor calculation module is used to calculate the groundwater influence correction coefficient. Correction coefficient for the influence of structural surface attitude Correction factor for the influence of initial stress state Coupling amplification factor and correction factor The disturbance factor that affects the basic stability; The surrounding rock stability discrimination module is used to calculate the surrounding rock stability index based on the basic stability and disturbance factor of the surrounding rock, and to judge the stability of the surrounding rock based on the surrounding rock stability index.

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