Anchoring engineering rock mass risk index system construction method, system, equipment and medium

Abstract

The invention relates to an anchoring engineering rock mass risk index system construction method and system, equipment and a medium. The method comprises the following steps: acquiring a final allowable corrosion rate; calculating the annual corrosion rate based on the annual average dry-wet cycle index, the stress environment label and the corrosion environment label, and calculating the theoretical life of anchoring engineering; dividing the actual service time of the anchoring engineering by the theoretical service life of the anchoring engineering to obtain the relative service life of the anchoring engineering, and calculating the failure risk possibility grade of the anchoring engineering based on the relative service life of the anchoring engineering; obtaining anchoring engineering rock mass risk indexes, and inputting the anchoring engineering rock mass risk indexes into the anchoring engineering failure loss severity fuzzy mapping model to obtain anchoring engineering failure severity grades; and obtaining an anchoring engineering rock mass risk grade based on the anchoring engineering failure risk possibility grade and the anchoring engineering failure severity grade. By adopting the method, systematic assessment of anchoring engineering rock mass risk can be realized through multi-dimensional index system construction.

Description

Technical Field

[0001] This application belongs to the field of risk assessment for anchoring engineering, and in particular relates to a method, system, equipment and medium for constructing a rock mass risk index system for anchoring engineering. Background Technology

[0002] With the continuous development of support engineering such as geotechnical engineering, mining, and slope protection, anchoring technology has gradually matured and been widely used as a core support method. Anchoring technology can strengthen and stabilize rock mass structures and adapt well to complex geological environments, making it a key support for ensuring engineering safety.

[0003] In traditional technologies, the design of anchoring projects often refers to engineering parameters in a single dimension. During construction, the focus is on compliance checks of material specifications and installation procedures. In risk control, the main means is to set a fixed safety factor and achieve passive protection by limiting the strength of anchor cable materials and anchoring depth. There is a lack of dynamic attention to the changes in risks during the service life of the project, and the assessment process also relies heavily on engineers' on-site observation and subjective judgment.

[0004] In existing technologies, due to the concealed nature of anchoring projects, construction quality defects are easily covered by rock masses and difficult to detect. During the service life of anchoring projects, the performance of core components such as anchor cables is continuously degraded due to the coupled effects of multiple factors such as wet-dry cycles, stress, and corrosive media. Traditional methods are insufficient to measure the dynamically changing corrosion process. Furthermore, existing risk assessment technologies mostly remain at the qualitative level, lacking a systematic integration of multi-dimensional factors, making it difficult to achieve early prediction and effective control of risks. There is an urgent need to construct a systematic risk assessment method for anchoring projects that integrates multi-dimensional indicators, dynamic environmental response, and quantitative loss assessment. Summary of the Invention

[0005] Therefore, it is necessary to provide a method, system, equipment, and medium for constructing a multi-dimensional indicator system to achieve a systematic assessment of rock mass risk in anchoring projects, addressing the aforementioned technical issues.

[0006] Firstly, this application provides a method for constructing a rock mass risk index system for anchoring engineering, including:

[0007] Obtain the allowable corrosion rate of steel strand breaking force, allowable corrosion rate of anchoring force, and allowable corrosion rate of steel strength, and set the final allowable corrosion rate as the minimum value among the allowable corrosion rate of steel strand breaking force, allowable corrosion rate of anchoring force, and allowable corrosion rate of steel strength;

[0008] The annual average number of wet and dry cycles, stress environment label and corrosion environment label during the service life of the anchor cable are obtained. The annual corrosion rate is calculated based on the annual average number of wet and dry cycles, stress environment label and corrosion environment label during the service life of the anchor cable. The theoretical life of the anchoring project is calculated by dividing the final allowable corrosion rate by the annual corrosion rate.

[0009] The actual service time of the anchoring project is obtained. The relative service life of the anchoring project is calculated by dividing the actual service time of the anchoring project by the theoretical service life of the anchoring project. The relative service life of the anchoring project is input into the failure risk probability assessment model of the anchoring project to calculate the failure risk probability of the anchoring project. Based on the failure risk probability of the anchoring project, the failure risk probability level of the anchoring project is divided.

[0010] The rock mass risk indicators of the anchoring project are obtained and input into the fuzzy mapping model of the severity of failure loss of the anchoring project to obtain the severity level of failure of the anchoring project. Among them, the rock mass risk indicators of the anchoring project include environmental indicators, soil and rock property indicators, material design indicators and anchoring construction indicators.

[0011] The comprehensive risk assessment value of the rock mass of the anchoring project is calculated based on the probability level and severity level of the anchoring project failure, and the rock mass risk level of the anchoring project is classified based on the comprehensive risk assessment value.

[0012] In one embodiment, the expression for the anchorage failure risk probability assessment model is:

[0013]

[0014]

[0015] In the formula, To determine the probability of failure in anchoring projects. The cumulative distribution function of the standard normal distribution. For the relative lifespan of the anchoring project, The mean parameters are those of the probability assessment model for anchorage project failure risk. The standard deviation parameter is used for the probability assessment model of anchorage failure risk. For the actual service life of the anchoring project, This refers to the theoretical lifespan of the anchoring project.

[0016] In one embodiment, the method for constructing a rock mass risk index system for anchoring projects further includes:

[0017] Obtain the anchorage failure sample set, which includes the actual life and theoretical life of the anchorage failure samples.

[0018] The relative life of the anchorage sample is calculated by dividing the actual life of the anchorage sample by the theoretical life of the anchorage sample.

[0019] The mean and standard deviation parameters of the anchorage failure risk probability assessment model are obtained based on the relative life calculation of anchorage project samples.

[0020] In one embodiment, the annual corrosion rate is calculated based on the annual average number of wet-dry cycles, stress environment label, and corrosion environment label during the anchor cable's service life, including:

[0021] Call the baseline annual corrosion rate model corresponding to the corrosion environment label; where the corrosion environment label includes weak corrosion environment label, moderate corrosion environment label and strong corrosion environment label, and the baseline annual corrosion rate model includes weak corrosion environment baseline annual corrosion rate model, moderate corrosion environment baseline annual corrosion rate model and strong corrosion environment baseline annual corrosion rate model.

[0022] The average number of dry and wet cycles per year during the service life of the anchor cable is input into the baseline annual corrosion rate model to calculate the baseline annual corrosion rate.

[0023] If the stress environment label is present, input the baseline annual corrosion rate into the stress influence correction model to calculate the annual corrosion rate;

[0024] If the stress environment label is an unstressed environment label, set the annual corrosion rate to the baseline annual corrosion rate.

[0025] In one embodiment, a rock mass risk index for the anchoring project is obtained, and this index is input into a fuzzy mapping model for the severity of anchoring project failure losses to obtain the severity level of anchoring project failure, including:

[0026] Obtain the rock mass risk index of each anchoring project, and input the rock mass risk index of each anchoring project into the normalization component in the fuzzy mapping model of the severity of failure loss of anchoring project for normalization preprocessing to obtain the normalized rock mass risk index of each anchoring project.

[0027] Each normalized rock mass risk index of the anchoring project is input into the membership function component of the corresponding fuzzy mapping model of the severity of anchoring project failure loss, and the membership degree of each index of the fuzzy subset of the severity of each risk index corresponding to each normalized rock mass risk index of the anchoring project is calculated.

[0028] The membership degree of each indicator is input into the indicator weight allocation component in the fuzzy mapping model of the severity of failure loss of anchoring project. The weighted membership degree of each indicator is obtained by multiplying the membership degree of each indicator by the correlation weight of each rock mass risk indicator of anchoring project.

[0029] The fuzzy rule base in the fuzzy mapping model of the severity of anchorage failure loss is invoked, and the activated fuzzy rules in the fuzzy rule base are identified based on the weighted membership degree; where the activated fuzzy rules are the fuzzy rules in the fuzzy rule base that are activated by the weighted membership degree.

[0030] Obtain the activation membership degree of each activation fuzzy rule output corresponding to the fuzzy subset of anchorage failure severity, and take the maximum value among the activation membership degrees of each fuzzy subset of anchorage failure severity as the risk membership degree of each fuzzy subset of anchorage failure severity, thus obtaining the fuzzy distribution of anchorage failure risk.

[0031] The fuzzy distribution of anchorage failure risk is defuzzified to obtain the anchorage failure risk value, and the severity level of anchorage failure is obtained by mapping the anchorage failure risk value.

[0032] In one embodiment, environmental indicators include oxygen, soil moisture content, temperature, humidity, pH, chloride ion concentration, sulfate concentration, stray current, average annual number of wet-dry cycles, wet-dry cycle period, ambient temperature fluctuation range, atmospheric pressure, carbon dioxide concentration, wind speed, sunshine duration, number of freeze-thaw cycles, groundwater level, groundwater flow velocity, and environmental corrosion level.

[0033] Rock and soil property indicators include rock mass cohesion, internal friction angle, uniaxial compressive strength, elastic modulus, fracture development, number of sliding surfaces, depth of sliding surfaces, and density.

[0034] Material design indicators include anchor cable anti-corrosion structure type, grout strength grade, anchor cable prestress level, steel strand breaking force, anchor cable spacing, anchorage length, free section protective layer thickness, and relative life of the anchorage project.

[0035] Anchorage construction indicators include anchor hole inclination angle deviation, anchorage section embedment depth deviation, tension force deviation, tensioning sequence, grout density, and grout void rate.

[0036] The fuzzy subsets of risk indicator severity include: oxygen index severity fuzzy subsets, soil and rock moisture content index severity fuzzy subsets, temperature index severity fuzzy subsets, humidity index severity fuzzy subsets, pH index severity fuzzy subsets, chloride ion concentration index severity fuzzy subsets, sulfate concentration index severity fuzzy subsets, stray current index severity fuzzy subsets, annual average wet-dry cycle number index severity fuzzy subsets, wet-dry cycle period index severity fuzzy subsets, ambient temperature fluctuation amplitude index severity fuzzy subsets, atmospheric pressure index severity fuzzy subsets, carbon dioxide concentration index severity fuzzy subsets, wind speed index severity fuzzy subsets, sunshine duration index severity fuzzy subsets, freeze-thaw cycle number index severity fuzzy subsets, groundwater level index severity fuzzy subsets, groundwater flow velocity index severity fuzzy subsets, environmental corrosion level index severity fuzzy subsets, rock mass cohesion index severity fuzzy subsets, and rock mass internal friction angle index severity fuzzy subsets. The following subsets are included: Fuzzy subsets of severity levels for rock uniaxial compressive strength index, rock mass elastic modulus index, rock mass fracture development index, slip surface quantity index, slip surface burial depth index, soil and rock density index, anchor cable corrosion protection structure type index, grout strength grade index, anchor cable prestress level index, steel strand breaking force index, anchor cable spacing index, anchorage length index, free section protective layer thickness index, anchorage engineering relative life index, anchor cable hole inclination angle deviation index, anchorage section embedment depth deviation index, tension force deviation index, tensioning sequence index, grout density index, and grout void rate index.

[0037] In one embodiment, the method for constructing a rock mass risk index system for anchoring projects further includes:

[0038] Obtain a corrosion sample set for anchoring projects. The corrosion samples in the anchoring project corrosion sample set include the sample corrosion rate and the sample risk index corresponding to the rock mass risk index of each anchoring project.

[0039] Calculate the Pearson correlation coefficient between the risk index and the corrosion rate of each sample;

[0040] The analytic hierarchy process (AHP) judgment matrix is ​​constructed based on the absolute values ​​of each Pearson correlation coefficient, and the main eigenvector of the AHP judgment matrix is ​​iteratively calculated to obtain the weight vector.

[0041] Normalize the weight vector to obtain the correlation weights;

[0042] The expressions for the weight vector and the analytic hierarchy process (AHP) judgment matrix are as follows:

[0043]

[0044]

[0045]

[0046] In the formula, For the first The weight vector of the next iteration To determine the matrix using the analytic hierarchy process (AHP), For Manhattan norm, For the iterative convergence condition, Let be the convergence threshold, and let be the th . The rock mass risk index of the anchoring project is relative to the first The importance scale of rock mass risk indicators for anchoring projects This represents the total number of rock mass risk indicators for the anchoring project. For the first The absolute value of the Pearson correlation coefficient of the rock mass risk index for the anchoring project. For the first The absolute value of the Pearson correlation coefficient of the rock mass risk index for the anchoring project.

[0047] In one embodiment, the severity level of anchorage failure includes a minor level, a major level, a severe level, a very severe level, and a catastrophic level;

[0048] The fuzzy subset of anchorage failure severity includes the fuzzy subset of minor anchorage failure severity, the fuzzy subset of major anchorage failure severity, the fuzzy subset of severe anchorage failure severity, the fuzzy subset of very severe anchorage failure severity, and the fuzzy subset of catastrophic anchorage failure severity.

[0049] Secondly, this application also provides a system for constructing a rock mass risk index system for anchoring engineering, including:

[0050] The permissible corrosion rate setting module is used to obtain the permissible corrosion rate of steel strand breaking force, permissible corrosion rate of anchoring force, and permissible corrosion rate of steel strength, and set the final permissible corrosion rate to the minimum value among the permissible corrosion rate of steel strand breaking force, permissible corrosion rate of anchoring force, and permissible corrosion rate of steel strength;

[0051] The annual corrosion rate calculation module is used to obtain the annual average number of wet and dry cycles, stress environment label and corrosion environment label during the service life of the anchor cable. Based on the annual average number of wet and dry cycles, stress environment label and corrosion environment label during the service life of the anchor cable, the annual corrosion rate is calculated. The theoretical life of the anchoring project is calculated by dividing the final allowable corrosion rate by the annual corrosion rate.

[0052] The failure risk probability assessment module is used to obtain the actual service time of the anchoring project. The relative service time of the anchoring project is divided by the theoretical service life of the anchoring project to calculate the relative service life of the anchoring project. The relative service life of the anchoring project is input into the failure risk probability assessment model of the anchoring project to calculate the failure risk probability of the anchoring project. Based on the failure risk probability of the anchoring project, the failure risk probability level of the anchoring project is divided.

[0053] The failure severity assessment module is used to obtain the rock mass risk index of the anchoring project and input the rock mass risk index of the anchoring project into the fuzzy mapping model of the failure loss severity of the anchoring project to obtain the failure severity level of the anchoring project; among them, the rock mass risk index of the anchoring project includes environmental indexes, geotechnical property indexes, material design indexes and anchoring construction indexes;

[0054] The risk level comprehensive assessment module is used to calculate the comprehensive risk evaluation value of the rock mass of the anchoring project based on the probability level and severity level of the anchoring project failure, and to classify the rock mass risk level of the anchoring project based on the comprehensive risk evaluation value.

[0055] Thirdly, this application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the method as described in any of the first aspects of this application.

[0056] Fourthly, this application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in any of the first aspects of this application.

[0057] The aforementioned methods, systems, equipment, and media for constructing the rock mass risk index system for anchoring projects, by building a safety threshold system based on the breaking force of steel strands, anchoring force, and allowable corrosion rate of steel strength, can accurately locate the weak links in the performance of anchor cable materials and improve the reliability of risk assessment results. By constructing a multi-dimensional rock mass risk index system composed of environmental, geotechnical, material design, and anchoring construction indicators, it can systematically integrate key influencing factors throughout the entire life cycle of anchoring projects, thereby enhancing the comprehensiveness and systematic nature of risk assessment. By establishing a theoretical life calculation model based on corrosion kinetics and environmental parameters, it can achieve dynamic prediction of anchor cable service life and quantitative characterization of failure probability, thereby improving the accuracy of life assessment and the foresight of failure early warning, and enhancing the pertinence and effectiveness of risk control strategies. Through a risk assessment framework that integrates multi-source heterogeneous data and quantitative models, it can achieve systematic modeling and dynamic management of anchoring project risks, providing closed-loop management support for the safe operation of anchoring projects. Attached Figure Description

[0058] To more clearly illustrate the technical solutions in the embodiments or related technologies of this application, the accompanying drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0059] Figure 1 A flowchart illustrating a method for constructing a rock mass risk index system for anchoring engineering, provided as an embodiment of this application;

[0060] Figure 2 This is a schematic diagram of a system for constructing a rock mass risk index system for anchoring engineering, provided as an embodiment of this application. Detailed Implementation

[0061] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0062] In one exemplary embodiment of this application, such as Figure 1As shown, a method for constructing a rock mass risk index system for anchoring engineering is provided. This embodiment illustrates the application of this method to a rock mass risk assessment terminal for anchoring engineering. It is understood that this method can also be applied to a rock mass risk assessment server for anchoring engineering, and further to an anchoring engineering rock mass risk assessment system that includes both a rock mass risk assessment terminal and a rock mass risk assessment server, and is implemented through the interaction between the two. In this embodiment, the method includes the following steps:

[0063] Step S101: Obtain the allowable corrosion rate of the steel strand breaking force, the allowable corrosion rate of the anchoring force, and the allowable corrosion rate of the steel strength, and set the final allowable corrosion rate as the minimum value among the allowable corrosion rate of the steel strand breaking force, the allowable corrosion rate of the anchoring force, and the allowable corrosion rate of the steel strength.

[0064] Specifically, the rock mass risk assessment terminal for anchoring projects can calculate the allowable corrosion rate of steel strand breaking force, allowable corrosion rate of anchoring force, and allowable corrosion rate of steel strength based on the steel strand breaking force reduction coefficient, anchoring force reduction coefficient, and actual steel strength utilization coefficient, and set the final allowable corrosion rate as the minimum value among the steel strand breaking force allowable corrosion rate, anchoring force allowable corrosion rate, and steel strength allowable corrosion rate.

[0065] Optionally, the expressions for the steel strand breaking strength reduction coefficient, anchoring force reduction coefficient, and actual steel strength utilization coefficient can be:

[0066]

[0067]

[0068]

[0069] In the formula, , and These are the reduction coefficients for breaking force of steel strand, anchorage force, and actual steel strength utilization, respectively. , and These are the allowable corrosion rates based on the breaking force of the steel strand, the allowable corrosion rate based on the anchoring force, and the allowable corrosion rate based on the strength of the steel. The breaking force after corrosion. The original breaking force, The relative length of the corroded section. For the anchoring force after corrosion, This represents the original anchoring force.

[0070] Optionally, the final allowable corrosion rate can be expressed as:

[0071]

[0072] In the formula, The final allowable corrosion rate.

[0073] Step S102: Obtain the annual average number of wet and dry cycles, stress environment label and corrosion environment label during the service life of the anchor cable. Calculate the annual corrosion rate based on the annual average number of wet and dry cycles, stress environment label and corrosion environment label during the service life of the anchor cable. Divide the final allowable corrosion rate by the annual corrosion rate to calculate the theoretical life of the anchoring project.

[0074] Specifically, the rock mass risk assessment terminal for anchoring projects can obtain the annual average number of wet-dry cycles, stress environment label, and corrosion environment label during the service life of the anchor cable. Based on these data, the terminal can calculate the annual corrosion rate. Finally, the terminal can calculate the theoretical lifespan of the anchoring project by dividing the final allowable corrosion rate by the annual corrosion rate.

[0075] Optionally, the expression for the theoretical life of the anchoring project can be:

[0076]

[0077] In the formula, For the theoretical lifespan of the anchoring project, The annual corrosion rate.

[0078] Step S103: Obtain the actual usage time of the anchoring project, divide the actual usage time of the anchoring project by the theoretical life of the anchoring project to calculate the relative life of the anchoring project, input the relative life of the anchoring project into the anchoring project failure risk probability assessment model, calculate the failure risk probability of the anchoring project, and classify the failure risk probability level of the anchoring project based on the failure risk probability of the anchoring project.

[0079] Specifically, the rock mass risk assessment terminal for anchoring projects can obtain the actual service life of the anchoring project. It can then calculate the relative lifespan of the anchoring project by dividing the actual service life by its theoretical lifespan. This relative lifespan can be input into the anchoring project failure risk probability assessment model to calculate the failure risk probability and, based on this probability, classify the likelihood of anchoring project failure into different levels.

[0080] Optionally, the probability level of anchorage failure risk may include, but is not limited to, extremely unlikely, impossible, possible, very likely, and extremely likely levels.

[0081] Step S104: Obtain the rock mass risk index of the anchoring project, and input the rock mass risk index of the anchoring project into the fuzzy mapping model of the severity of failure loss of the anchoring project to obtain the severity level of failure of the anchoring project.

[0082] Specifically, the rock mass risk assessment terminal for anchoring projects can obtain rock mass risk indicators for anchoring projects and input these indicators into a fuzzy mapping model for the severity of failure losses in anchoring projects to obtain the severity level of anchoring project failures.

[0083] Optionally, the severity level of anchorage failure can include minor, major, severe, very severe, and catastrophic levels.

[0084] Optionally, rock mass risk indicators for anchoring projects may include environmental indicators, soil and rock property indicators, material design indicators, and anchoring construction indicators.

[0085] Step S105: Calculate the comprehensive risk assessment value of the rock mass of the anchoring project based on the probability level of anchoring project failure and the severity level of anchoring project failure, and classify the rock mass risk level of the anchoring project based on the comprehensive risk assessment value of the rock mass of the anchoring project.

[0086] Specifically, the rock mass risk assessment terminal for anchoring projects can calculate a comprehensive risk evaluation value for the rock mass of the anchoring project based on the probability level and severity level of the anchoring project failure. The terminal can then classify the rock mass risk level of the anchoring project based on this comprehensive risk evaluation value.

[0087] Optionally, the expression for the comprehensive evaluation value of rock mass risk in anchoring projects can be:

[0088]

[0089] In the formula, is the comprehensive evaluation value of rock mass risk in the anchoring project, is the probability level value of anchoring project failure risk corresponding to the probability level of anchoring project failure, and is the severity level value of anchoring project failure corresponding to the severity level of anchoring project failure.

[0090] Optionally, when the probability level of anchorage failure includes extremely unlikely, impossible, possible, very likely, and highly probable levels, the probability level value of anchorage failure is... Among them, the extremely unlikely level can correspond to The severity levels of anchorage failure are categorized into minor, significant, severe, very severe, and catastrophic levels, and increase sequentially. Among them, the severity level can correspond to And increase sequentially.

[0091] Furthermore, the rock mass risk assessment terminal for anchoring projects can classify the rock mass risk level of anchoring projects into different categories based on the range of the comprehensive evaluation value of the rock mass risk. .in, To minimize risk, This represents the highest risk.

[0092] Optionally, when the probability level of anchorage project failure includes levels of extremely unlikely, impossible, possible, very likely, and highly probable occurrence, and the severity level of anchorage project failure includes levels of minor, significant, severe, very severe, and catastrophic, the anchorage project rock mass risk assessment terminal can output a comprehensive evaluation value of the anchorage project rock mass risk. Classified as rock mass risk level for anchoring projects The anchoring project rock mass risk assessment terminal can generate a comprehensive evaluation value of the anchoring project rock mass risk. Classified as rock mass risk level for anchoring projects The anchoring project rock mass risk assessment terminal can generate a comprehensive evaluation value of the anchoring project rock mass risk. Classified as rock mass risk level for anchoring projects The anchoring project rock mass risk assessment terminal can generate a comprehensive evaluation value of the anchoring project rock mass risk. Classified as rock mass risk level for anchoring projects The anchoring project rock mass risk assessment terminal can generate a comprehensive evaluation value of the anchoring project rock mass risk. Classified as rock mass risk level for anchoring projects .

[0093] In the aforementioned method for constructing a rock mass risk index system for anchoring projects, by integrating the breaking force of the steel strand, the anchoring force, and the allowable corrosion rate related to the steel strength and taking the minimum value, the allowable corrosion rate can fully cover the tolerance bottom line of the key performance dimensions of the anchor cable, avoiding assessment bias caused by a single-dimensional corrosion standard and improving the data accuracy of the risk assessment system. By calculating the annual corrosion rate and deriving the theoretical life of the anchoring project based on the ratio of the final allowable corrosion rate to the annual corrosion rate, the system can accurately reflect the true rate of anchor cable performance degradation under different environmental and stress states, improving the scenario adaptability of the risk assessment. By calculating the relative life of the anchoring project and inputting it into the failure risk probability, the system can accurately reflect the actual rate of anchor cable performance degradation under different environmental and stress states, improving the scenario adaptability of the risk assessment. The assessment model and classification of failure risk probability levels can transform life decay data into failure risk probability indicators, accurately match the probability of risk occurrence, and improve the pertinence and effectiveness of risk prevention and control. By integrating multi-dimensional rock mass risk indicators for anchoring projects and combining them with failure risk probability levels to calculate a comprehensive risk evaluation value and classify risk levels, it can comprehensively cover the key dimensions affecting the failure loss of anchoring projects. By incorporating various core influencing factors into the assessment system, it can avoid misjudging the severity of losses, achieve multi-dimensional quantitative assessment of risks, provide comprehensive and reliable technical support for the accurate management and control of engineering risks, and realize a systematic assessment of rock mass risks in anchoring projects.

[0094] In an optional embodiment of this application, the expression for the anchorage project failure risk probability assessment model can be:

[0095]

[0096]

[0097] In the formula, To determine the probability of failure in anchoring projects. The cumulative distribution function of the standard normal distribution. For the relative lifespan of the anchoring project, The mean parameters are those of the probability assessment model for anchorage project failure risk. The standard deviation parameter is used for the probability assessment model of anchorage failure risk. For the actual service life of the anchoring project, This refers to the theoretical lifespan of the anchoring project.

[0098] In an optional embodiment of this application, the method for constructing a rock mass risk index system for anchoring engineering may further include:

[0099] Specifically, the rock mass risk assessment terminal for anchoring projects can obtain a set of anchoring project failure samples, which includes the actual lifespan and theoretical lifespan of the anchoring project samples.

[0100] Optionally, the failure sample set of anchoring projects may include, but is not limited to, the historical failure sample set of anchoring projects and the test failure sample set of anchoring projects.

[0101] Specifically, the relative life of the anchorage engineering rock mass risk assessment terminal can be calculated by dividing the actual life of the anchorage engineering sample by the theoretical life of the anchorage engineering sample.

[0102] Specifically, the rock mass risk assessment terminal for anchoring projects can calculate the mean and standard deviation parameters of the failure risk probability assessment model for anchoring projects based on the relative life of the anchoring project samples.

[0103] In an optional embodiment of this application, the annual corrosion rate is calculated based on the annual average number of wet-dry cycles, stress environment label, and corrosion environment label during the service life of the anchor cable, and may include:

[0104] Specifically, the rock mass risk assessment terminal for anchoring projects can call the baseline annual corrosion rate model corresponding to the corrosion environment label.

[0105] Optionally, the corrosion environment label includes a weak corrosion environment label, a moderate corrosion environment label, and a strong corrosion environment label, and the baseline annual corrosion rate model includes a weak corrosion environment baseline annual corrosion rate model, a moderate corrosion environment baseline annual corrosion rate model, and a strong corrosion environment baseline annual corrosion rate model.

[0106] Furthermore, the expressions for the baseline annual corrosion rate models for weakly corrosive environments, moderately corrosive environments, and strongly corrosive environments can be:

[0107]

[0108]

[0109]

[0110] In the formula, , and These are, respectively, the baseline annual corrosion rate models for weakly corrosive environments, moderately corrosive environments, and strongly corrosive environments. Based on the annual corrosion rate, This represents the average number of wet and dry cycles per year during the service life of the anchor cable.

[0111] Specifically, the rock mass risk assessment terminal for anchoring projects can input the average number of dry and wet cycles per year during the service life of the anchor cable into the baseline annual corrosion rate model to calculate the baseline annual corrosion rate.

[0112] Specifically, if the stress environment label is present, the anchoring project rock mass risk assessment terminal can input the benchmark annual corrosion rate into the stress influence correction model to calculate the annual corrosion rate.

[0113] Optionally, the expression for the stress influence correction model can be:

[0114]

[0115]

[0116] In the formula, This is the stress influence correction factor.

[0117] Specifically, if the stress environment label is an unstressed environment label, the rock mass risk assessment terminal for anchoring projects can set the annual corrosion rate as the benchmark annual corrosion rate.

[0118] In an optional embodiment of this application, obtaining the rock mass risk index of the anchoring project and inputting the rock mass risk index of the anchoring project into the fuzzy mapping model of the severity of anchoring project failure loss to obtain the severity level of anchoring project failure may include:

[0119] Specifically, the rock mass risk assessment terminal for anchoring projects can obtain the rock mass risk indicators of each anchoring project and input them into the normalization component of the fuzzy mapping model of the severity of failure loss in anchoring projects for normalization preprocessing to obtain the normalized rock mass risk indicators of each anchoring project.

[0120] Specifically, the anchoring project rock mass risk assessment terminal can input each normalized anchoring project rock mass risk index into the membership function component in the corresponding anchoring project failure loss severity fuzzy mapping model, and calculate the membership degree of each index in the fuzzy subset of the severity of each risk index corresponding to each normalized anchoring project rock mass risk index.

[0121] Specifically, the anchoring project rock mass risk assessment terminal can input the membership degree of each indicator into the indicator weight allocation component in the fuzzy mapping model of the severity of anchoring project failure loss. The membership degree of each indicator is multiplied by the correlation weight of each anchoring project rock mass risk indicator to obtain the weighted membership degree corresponding to each indicator membership degree.

[0122] Specifically, the rock mass risk assessment terminal for anchoring projects can call the fuzzy rule base in the fuzzy mapping model of the severity of failure loss in anchoring projects, and identify the active fuzzy rules in the fuzzy rule base based on weighted membership degree.

[0123] Optionally, the fuzzy rule to be activated can be a fuzzy rule in the fuzzy rule base that is activated by weighted membership.

[0124] Specifically, the anchoring project rock mass risk assessment terminal can obtain the activation membership degree of each activated fuzzy rule output corresponding to the fuzzy subset of the anchoring project failure severity, and take the maximum value among the activation membership degrees of each fuzzy subset of the anchoring project failure severity as the risk membership degree of each fuzzy subset of the anchoring project failure severity, thus obtaining the fuzzy distribution of anchoring project failure risk.

[0125] Specifically, the rock mass risk assessment terminal for anchoring projects can defuzzify the fuzzy distribution of anchoring project failure risk to obtain the anchoring project failure risk value, and map the anchoring project failure risk value to obtain the severity level of anchoring project failure.

[0126] In an optional embodiment of this application, environmental indicators may include oxygen levels, soil and rock moisture content, temperature, humidity, pH, chloride ion concentration, sulfate concentration, stray current, average annual wet-dry cycle count, wet-dry cycle period, ambient temperature fluctuation range, atmospheric pressure, carbon dioxide concentration, wind speed, sunshine duration, freeze-thaw cycle count, groundwater level, groundwater flow velocity, and environmental corrosion level. Soil and rock property indicators may include rock mass cohesion, internal friction angle, uniaxial compressive strength, elastic modulus, fracture development, number of slip surfaces, slip surface depth, and soil and rock density. Material design indicators may include anchor cable corrosion protection structure type, grout strength grade, anchor cable prestress level, steel strand breaking force, anchor cable spacing, anchorage length, free section protective layer thickness, and relative lifespan of the anchorage project. Anchorage construction indicators may include anchor hole inclination deviation, anchorage section embedment depth deviation, tension force deviation, tensioning sequence, grout density, and grout void rate.

[0127] Furthermore, the fuzzy subset of risk indicator severity can include the following: oxygen index severity fuzzy subset, soil moisture content index severity fuzzy subset, temperature index severity fuzzy subset, humidity index severity fuzzy subset, pH index severity fuzzy subset, chloride ion concentration index severity fuzzy subset, sulfate concentration index severity fuzzy subset, stray current index severity fuzzy subset, annual average wet-dry cycle number index severity fuzzy subset, wet-dry cycle period index severity fuzzy subset, ambient temperature fluctuation amplitude index severity fuzzy subset, atmospheric pressure index severity fuzzy subset, carbon dioxide concentration index severity fuzzy subset, wind speed index severity fuzzy subset, sunshine duration index severity fuzzy subset, freeze-thaw cycle number index severity fuzzy subset, groundwater level index severity fuzzy subset, groundwater flow velocity index severity fuzzy subset, environmental corrosion level index severity fuzzy subset, rock mass cohesion index severity fuzzy subset, and rock mass internal friction angle index severity. The following subsets are included: Fuzzy subsets of severity for rock uniaxial compressive strength index, rock mass elastic modulus index, rock mass fracture development index, slip surface quantity index, slip surface burial depth index, soil and rock density index, anchor cable corrosion protection structure type index, grout strength grade index, anchor cable prestress level index, steel strand breaking force index, anchor cable spacing index, anchorage length index, free section protective layer thickness index, anchorage engineering relative life index, anchor cable hole inclination angle deviation index, anchorage section embedment depth deviation index, tension force deviation index, tensioning sequence index, grout density index, and grout void rate index.

[0128] In an optional embodiment of this application, the method for constructing a rock mass risk index system for anchoring engineering may further include:

[0129] Specifically, the anchoring project rock mass risk assessment terminal can obtain the anchoring project corrosion sample set. The anchoring project corrosion sample set includes the sample corrosion rate and the sample risk index corresponding to each anchoring project rock mass risk index.

[0130] Specifically, the rock mass risk assessment terminal for anchoring projects can calculate the Pearson correlation coefficient between the risk indicators of each sample and the sample corrosion rate.

[0131] Specifically, the rock mass risk assessment terminal for anchoring projects can construct a analytic hierarchy process (AHP) judgment matrix based on the absolute values ​​of each Pearson correlation coefficient, and iteratively calculate the principal eigenvector of the AHP judgment matrix to obtain the weight vector.

[0132] Optionally, the expressions for the weight vector and the analytic hierarchy process (AHP) judgment matrix can be:

[0133]

[0134]

[0135]

[0136] In the formula, For the first The weight vector of the next iteration To determine the matrix using the analytic hierarchy process (AHP), For Manhattan norm, For the iterative convergence condition, Let be the convergence threshold, and let be the th . The rock mass risk index of the anchoring project is relative to the first The importance scale of rock mass risk indicators for anchoring projects This represents the total number of rock mass risk indicators for the anchoring project. For the first The absolute value of the Pearson correlation coefficient of the rock mass risk index for the anchoring project. For the first The absolute value of the Pearson correlation coefficient of the rock mass risk index for the anchoring project.

[0137] Optional, convergence threshold It can be an extremely small positive real number.

[0138] Specifically, the rock mass risk assessment terminal for anchoring projects can normalize the weight vector to obtain the correlation weight.

[0139] In an optional embodiment of this application, the fuzzy subset of the severity of anchorage failure may include, but is not limited to, a fuzzy subset of the severity of minor anchorage failure, a fuzzy subset of the severity of major anchorage failure, a fuzzy subset of the severity of severe anchorage failure, a fuzzy subset of the severity of very severe anchorage failure, and a fuzzy subset of the severity of catastrophic anchorage failure.

[0140] It should be understood that although the steps in the flowcharts of the embodiments described above are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the flowcharts of the embodiments described above may include multiple steps or multiple stages. These steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least some of the steps or stages of other steps.

[0141] Based on the same inventive concept, this application also provides a system for constructing a rock mass risk index system for anchoring engineering, which is used to implement the above-mentioned method for constructing a rock mass risk index system for anchoring engineering. The solution provided by this system is similar to the solution described in the above method. Therefore, the specific limitations of one or more embodiments of the system for constructing a rock mass risk index system for anchoring engineering provided below can be found in the limitations of the method for constructing a rock mass risk index system for anchoring engineering above, and will not be repeated here.

[0142] In one exemplary embodiment, such as Figure 2 As shown, a system 200 for constructing a rock mass risk index system for anchoring engineering is provided, including:

[0143] The allowable corrosion rate setting module 201 can be used to obtain the allowable corrosion rate of steel strand breaking force, the allowable corrosion rate of anchoring force, and the allowable corrosion rate of steel strength, and set the final allowable corrosion rate as the minimum value among the allowable corrosion rate of steel strand breaking force, the allowable corrosion rate of anchoring force, and the allowable corrosion rate of steel strength.

[0144] The annual corrosion rate calculation module 202 can be used to obtain the annual average number of wet and dry cycles, stress environment label and corrosion environment label during the service life of the anchor cable. Based on the annual average number of wet and dry cycles, stress environment label and corrosion environment label during the service life of the anchor cable, the annual corrosion rate is calculated, and the theoretical life of the anchoring project is calculated by dividing the final allowable corrosion rate by the annual corrosion rate.

[0145] The failure risk probability assessment module 203 can be used to obtain the actual service time of the anchoring project, divide the actual service time of the anchoring project by the theoretical life of the anchoring project, calculate the relative life of the anchoring project, input the relative life of the anchoring project into the failure risk probability assessment model of the anchoring project, calculate the failure risk probability of the anchoring project, and classify the failure risk probability level of the anchoring project based on the failure risk probability of the anchoring project.

[0146] The failure severity assessment module 204 can be used to obtain rock mass risk indicators for anchoring projects and input these indicators into a fuzzy mapping model for the severity of anchoring project failure losses to obtain the failure severity level of the anchoring project. The rock mass risk indicators for anchoring projects include environmental indicators, soil and rock property indicators, material design indicators, and anchoring construction indicators.

[0147] The risk level comprehensive assessment module 205 can be used to calculate the comprehensive risk evaluation value of the rock mass of the anchoring project based on the probability level of anchoring project failure and the severity level of anchoring project failure, and to classify the rock mass risk level of the anchoring project based on the comprehensive risk evaluation value of the rock mass of the anchoring project.

[0148] In an optional embodiment of this application, the anchoring engineering rock mass risk index system construction system 200 can also be used for:

[0149] Obtain a failure sample set for anchoring projects. The failure sample set for anchoring projects includes the actual lifespan and the theoretical lifespan of the anchoring project samples.

[0150] The relative life of the anchorage sample is calculated by dividing the actual life of the anchorage sample by the theoretical life of the anchorage sample.

[0151] The mean and standard deviation parameters of the anchorage failure risk probability assessment model are obtained based on the relative life calculation of anchorage project samples.

[0152] In an optional embodiment of this application, the annual corrosion rate calculation module 202 can also be used for:

[0153] Call the baseline annual corrosion rate model corresponding to the corrosion environment label.

[0154] The average number of dry and wet cycles per year during the service life of the anchor cable is input into the baseline annual corrosion rate model to calculate the baseline annual corrosion rate.

[0155] If the stress environment label is present, input the baseline annual corrosion rate into the stress influence correction model to calculate the annual corrosion rate.

[0156] If the stress environment label is an unstressed environment label, set the annual corrosion rate to the baseline annual corrosion rate.

[0157] In an optional embodiment of this application, the failure severity assessment module 204 can also be used for:

[0158] Obtain the rock mass risk index of each anchoring project, and input the rock mass risk index of each anchoring project into the normalization component of the fuzzy mapping model of the severity of failure loss of the anchoring project for normalization preprocessing to obtain the normalized rock mass risk index of each anchoring project.

[0159] Each normalized rock mass risk index of the anchoring project is input into the membership function component of the corresponding fuzzy mapping model of the severity of anchoring project failure loss, and the membership degree of each index of the fuzzy subset of the severity of each risk index corresponding to each normalized rock mass risk index of the anchoring project is calculated.

[0160] The membership degree of each indicator is input into the indicator weight allocation component in the fuzzy mapping model of the severity of anchorage project failure loss. The weighted membership degree of each indicator is obtained by multiplying the membership degree of each indicator by the correlation weight of each anchorage project rock mass risk indicator.

[0161] The fuzzy rule base in the fuzzy mapping model of the severity of anchorage failure losses is invoked, and the activating fuzzy rules in the fuzzy rule base are identified based on weighted membership degrees. The activating fuzzy rules are the fuzzy rules in the fuzzy rule base that are activated by weighted membership degrees.

[0162] Obtain the activation membership degree of each activation fuzzy rule output corresponding to the fuzzy subset of anchorage failure severity, and take the maximum value among the activation membership degrees of each fuzzy subset of anchorage failure severity as the risk membership degree of each fuzzy subset of anchorage failure severity, thus obtaining the fuzzy distribution of anchorage failure risk.

[0163] The fuzzy distribution of anchorage failure risk is defuzzified to obtain the anchorage failure risk value, and the severity level of anchorage failure is obtained by mapping the anchorage failure risk value.

[0164] In an optional embodiment of this application, the anchoring engineering rock mass risk index system construction system 200 can also be used for:

[0165] Obtain a corrosion sample set for anchoring projects. The corrosion samples in the anchoring project corrosion sample set include the sample corrosion rate and the sample risk index corresponding to the rock mass risk index of each anchoring project.

[0166] Calculate the Pearson correlation coefficient between the risk index and the corrosion rate of each sample.

[0167] The analytic hierarchy process (AHP) judgment matrix is ​​constructed based on the absolute values ​​of each Pearson correlation coefficient, and the principal eigenvectors of the AHP judgment matrix are iteratively calculated to obtain the weight vector.

[0168] The weight vector is normalized to obtain the correlation weights.

[0169] In one embodiment, a computer device is provided, including a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the steps of the method for constructing a rock mass risk index system for anchoring engineering as described above.

[0170] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps in the above method embodiments.

[0171] For the device embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to in the description of the method embodiments. The device embodiments described above are merely illustrative. The components described as separate parts may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this disclosure according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0172] The above-described embodiments are merely illustrative of several implementation methods of the embodiments of this application, and their descriptions are relatively specific and detailed. However, they should not be construed as limiting the scope of the patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the embodiments of this application, and these modifications and improvements all fall within the protection scope of the embodiments of this application.

Claims

1. A method for constructing an anchor engineering rock mass risk index system, characterized in that, The method comprises: obtaining a steel strand breaking force allowable corrosion rate, an anchoring force allowable corrosion rate and a steel strength allowable corrosion rate, and setting a final allowable corrosion rate as a minimum value among the steel strand breaking force allowable corrosion rate, the anchoring force allowable corrosion rate and the steel strength allowable corrosion rate; obtaining an annual average dry-wet cycle number in a service period of the anchor cable, a stress environment label and a corrosion environment label, calculating an annual corrosion rate based on the annual average dry-wet cycle number in the service period of the anchor cable, the stress environment label and the corrosion environment label, and calculating an anchoring engineering theoretical service life by dividing the final allowable corrosion rate by the annual corrosion rate; obtaining an anchoring engineering actual service time, calculating an anchoring engineering relative service life by dividing the anchoring engineering actual service time by the anchoring engineering theoretical service life, inputting the anchoring engineering relative service life into an anchoring engineering failure risk probability evaluation model to calculate an anchoring engineering failure risk probability, and dividing the anchoring engineering failure risk probability to obtain an anchoring engineering failure risk possibility level; obtaining an anchoring engineering rock mass risk index, and inputting the anchoring engineering rock mass risk index into an anchoring engineering failure loss severity fuzzy mapping model to obtain an anchoring engineering failure severity level; wherein the anchoring engineering rock mass risk index comprises an environment index, a geotechnical property index, a material design index and an anchoring construction index; calculating an anchoring engineering rock mass risk comprehensive evaluation value based on the anchoring engineering failure risk possibility level and the anchoring engineering failure severity level, and dividing the anchoring engineering rock mass risk comprehensive evaluation value to obtain an anchoring engineering rock mass risk level.

2. The method of claim 1, wherein, The expression of the anchoring engineering failure risk probability evaluation model is: wherein, is the failure risk probability of the anchoring project, is the cumulative distribution function of the standard normal distribution, is the relative life of the anchoring project, is the mean parameter of the failure risk probability evaluation model of the anchoring project, is the standard deviation parameter of the failure risk probability evaluation model of the anchoring project, is the actual service time of the anchoring project, is the theoretical life of the anchoring project.

3. The method of claim 2, wherein, The method further comprises: obtaining an anchoring engineering failure sample set, wherein an anchoring engineering failure sample in the anchoring engineering failure sample set comprises an anchoring engineering sample actual service life and an anchoring engineering sample theoretical service life; calculating an anchoring engineering sample relative service life by dividing the anchoring engineering sample actual service life by the anchoring engineering sample theoretical service life; calculating the mean parameter and the standard deviation parameter of the anchoring engineering failure risk probability evaluation model based on the anchoring engineering sample relative service life.

4. The method of claim 1, wherein, The calculating of the annual corrosion rate based on the annual average dry-wet cycle number in the service period of the anchor cable, the stress environment label and the corrosion environment label comprises: calling a benchmark annual corrosion rate model corresponding to the corrosion environment label; wherein the corrosion environment label comprises a weak corrosion environment label, a moderate corrosion environment label and a strong corrosion environment label, and the benchmark annual corrosion rate model comprises a weak corrosion environment benchmark annual corrosion rate model, a moderate corrosion environment benchmark annual corrosion rate model and a strong corrosion environment benchmark annual corrosion rate model; inputting the annual average dry-wet cycle number in the service period of the anchor cable into the benchmark annual corrosion rate model to calculate a benchmark annual corrosion rate; if the stress environment label is an existing stress environment label, inputting the benchmark annual corrosion rate into a stress influence correction model to calculate the annual corrosion rate; If the stress environment tag is an unstressed environment tag, the annual corrosion rate is set as the reference annual corrosion rate.

5. The method according to any one of claims 1 to 4, characterized in that, The anchoring engineering rock mass risk index is obtained, and the anchoring engineering rock mass risk index is input into the anchoring engineering failure loss severity fuzzy mapping model to obtain an anchoring engineering failure severity grade, including: Each of the anchoring engineering rock mass risk indexes is obtained, and each of the anchoring engineering rock mass risk indexes is input into a normalization component in the anchoring engineering failure loss severity fuzzy mapping model to perform normalization preprocessing to obtain each normalized anchoring engineering rock mass risk index; Each of the normalized anchoring engineering rock mass risk indexes is input into a membership function component in the corresponding anchoring engineering failure loss severity fuzzy mapping model, and each index membership degree of each risk index severity fuzzy subset corresponding to each of the normalized anchoring engineering rock mass risk indexes is calculated; Each of the index membership degrees is input into an index weight distribution component in the anchoring engineering failure loss severity fuzzy mapping model, and each weighted membership degree corresponding to each of the index membership degrees is obtained by multiplying each of the index membership degrees by a correlation weight of each of the anchoring engineering rock mass risk indexes; The fuzzy rule base in the anchoring engineering failure loss severity fuzzy mapping model is called, and based on the weighted membership degrees, an activated fuzzy rule in the fuzzy rule base is identified; wherein the activated fuzzy rule is a fuzzy rule in the fuzzy rule base activated by the weighted membership degrees; Each activated membership degree output by each of the activated fuzzy rules corresponding to an anchoring engineering failure severity fuzzy subset is obtained, and a maximum value of each of the activated membership degrees of each anchoring engineering failure severity fuzzy subset is taken as a risk membership degree of each of the anchoring engineering failure severity fuzzy subsets to obtain an anchoring engineering failure risk fuzzy distribution; The anchoring engineering failure risk fuzzy distribution is de-fuzzied to obtain an anchoring engineering failure risk value, and based on the anchoring engineering failure risk value, the anchoring engineering failure severity grade is mapped.

6. The method of claim 5, wherein: the environment type indexes include oxygen indexes, rock-soil moisture content indexes, temperature indexes, humidity indexes, pH indexes, chloride ion concentration indexes, sulfate concentration indexes, stray current indexes, annual average dry-wet cycle frequency indexes, dry-wet cycle period indexes, environmental temperature fluctuation amplitude indexes, atmospheric pressure indexes, carbon dioxide concentration indexes, wind speed indexes, sunshine duration indexes, freeze-thaw cycle frequency indexes, groundwater level indexes, groundwater flow velocity indexes, and environmental corrosion grade indexes; the rock-soil property type indexes include rock mass cohesion indexes, rock mass internal friction angle indexes, rock uniaxial compressive strength indexes, rock mass elastic modulus indexes, rock mass fracture development degree indexes, slip surface number indexes, slip surface burial depth indexes, and rock-soil body density indexes. The material design type indexes include an anchor cable anticorrosion structure type index, a grouting body strength grade index, an anchor cable prestress level index, a steel strand breaking force index, an anchor cable spacing index, an anchoring segment length index, a free segment protection layer thickness index, and a relative service life of the anchoring project; The anchoring construction type indexes include an anchor cable hole inclination angle deviation index, an anchoring segment embedding depth deviation index, a tensioning force deviation index, a tensioning sequence index, a grouting body density index, and a grouting body hollow rate index; The risk index severity fuzzy subsets include an oxygen index severity fuzzy subset, a geotechnical water content index severity fuzzy subset, a temperature index severity fuzzy subset, a humidity index severity fuzzy subset, a pH index severity fuzzy subset, a chloride ion concentration index severity fuzzy subset, a sulfate concentration index severity fuzzy subset, a stray current index severity fuzzy subset, an annual average dry-wet cycle frequency index severity fuzzy subset, a dry-wet cycle period index severity fuzzy subset, an environmental temperature fluctuation amplitude index severity fuzzy subset, an atmospheric pressure index severity fuzzy subset, a carbon dioxide concentration index severity fuzzy subset, a wind speed index severity fuzzy subset, a sunshine duration index severity fuzzy subset, a freeze-thaw cycle frequency index severity fuzzy subset, a groundwater level index severity fuzzy subset, a groundwater flow velocity index severity fuzzy subset, an environmental corrosion grade index severity fuzzy subset, a rock mass cohesion index severity fuzzy subset, a rock mass internal friction angle index severity fuzzy subset, a rock uniaxial compressive strength index severity fuzzy subset, a rock mass elastic modulus index severity fuzzy subset, a rock mass fracture development degree index severity fuzzy subset, a slip surface number index severity fuzzy subset, a slip surface burial depth index severity fuzzy subset, a geotechnological density index severity fuzzy subset, an anchor cable anticorrosion structure type index severity fuzzy subset, a grouting body strength grade index severity fuzzy subset, an anchor cable prestress level index severity fuzzy subset, a steel strand breaking force index severity fuzzy subset, an anchor cable spacing index severity fuzzy subset, an anchoring segment length index severity fuzzy subset, a free segment protection layer thickness index severity fuzzy subset, a relative service life of the anchoring project index severity fuzzy subset, an anchor cable hole inclination angle deviation index severity fuzzy subset, an anchoring segment embedding depth deviation index severity fuzzy subset, a tensioning force deviation index severity fuzzy subset, a tensioning sequence index severity fuzzy subset, a grouting body density index severity fuzzy subset, and a grouting body hollow rate index severity fuzzy subset.

7. The method of claim 5, wherein, The method further includes: obtaining an anchoring project corrosion sample set, each anchoring project corrosion sample in the anchoring project corrosion sample set including a sample corrosion rate and each sample risk index corresponding to each anchoring project rock mass risk index; calculating a Pearson correlation coefficient of each sample risk index and the sample corrosion rate; and An analytic hierarchy process judgment matrix is constructed based on absolute values of the Pearson correlation coefficients, and a main eigenvector of the analytic hierarchy process judgment matrix is iteratively calculated to obtain a weight vector; The weight vector is normalized to obtain the correlation weight; The weight vector and the analytic hierarchy process judgment matrix are expressed as: In the formula, For the first The weight vector of the next iteration. The analytic hierarchy process (AHP) is used to determine the matrix. For Manhattan norm, For the iterative convergence condition, Let be the convergence threshold, and let be the th . The rock mass risk index of the anchoring project mentioned in item [1] is relative to the [2]th [3]. The importance scale of the rock mass risk indicators for the anchoring project mentioned above. This represents the total number of rock mass risk indicators for the anchoring project. For the first The absolute value of the Pearson correlation coefficient of the rock mass risk index for the anchoring project mentioned in the item. For the first The absolute value of the Pearson correlation coefficient of the rock mass risk index of the anchoring project mentioned in the item.

8. A system for constructing an anchor engineering rock mass risk index system, characterized in that, The system comprises: An allowable corrosion rate setting module is configured to obtain a steel strand breaking force allowable corrosion rate, an anchoring force allowable corrosion rate, and a steel strength allowable corrosion rate, and set a final allowable corrosion rate as the minimum value among the steel strand breaking force allowable corrosion rate, the anchoring force allowable corrosion rate, and the steel strength allowable corrosion rate; An annual corrosion rate calculation module is configured to obtain an annual average dry-wet cycle number in a service period of the anchor cable, a stress environment tag, and a corrosion environment tag, calculate an annual corrosion rate based on the annual average dry-wet cycle number in the service period of the anchor cable, the stress environment tag, and the corrosion environment tag, and calculate a theoretical service life of the anchoring project by dividing the final allowable corrosion rate by the annual corrosion rate; A failure risk probability evaluation module is configured to obtain an actual use duration of the anchoring project, calculate a relative service life of the anchoring project by dividing the actual use duration of the anchoring project by the theoretical service life of the anchoring project, input the relative service life of the anchoring project into an anchoring project failure risk probability evaluation model to calculate a failure risk probability of the anchoring project, and divide the failure risk probability of the anchoring project to obtain a failure risk possibility level of the anchoring project; A failure severity evaluation module is configured to obtain an anchoring project rock mass risk index, and input the anchoring project rock mass risk index into an anchoring project failure loss severity fuzzy mapping model to obtain a failure severity level of the anchoring project; the anchoring project rock mass risk index comprises an environmental index, a geotechnical property index, a material design index, and an anchoring construction index; A risk level comprehensive evaluation module is configured to calculate an anchoring project rock mass risk comprehensive evaluation value based on the failure risk possibility level of the anchoring project and the failure severity level of the anchoring project, and divide the anchoring project rock mass risk comprehensive evaluation value to obtain an anchoring project rock mass risk level. 9.A computer device, comprising a memory and a processor, wherein the memory stores a computer program, and the computer device is configured to perform the method according to any one of claims 1-8. The processor executes the computer program to implement the method of any one of claims 1 to 7.

10. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to implement the method of any one of claims 1 to 7.

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