Corrosion reinforced concrete bonding strength prediction method and equipment and storage medium

Abstract

The invention provides a rusted reinforced concrete bonding strength prediction method. The method comprises the following steps: acquiring related data of a to-be-detected rusted reinforced concrete structural member; inputting the related data into a pre-constructed rusted reinforced concrete bonding strength prediction model, wherein the pre-constructed rusted reinforced concrete bonding strength prediction model comprises a first correction coefficient calculation model, a second correction coefficient calculation model and a third correction coefficient calculation model; respectively obtaining first, second and third correction coefficients; and combining the first correction coefficient, the second correction coefficient, the third correction coefficient and the bonding strength of the unrusted reinforced concrete structural member to obtain the bonding strength of the rusted reinforced concrete structural member to be detected. According to the method, on the basis of an existing model, a third correction coefficient for representing the influence of the concrete strength and the relation between the anchoring length and the longitudinal bar diameter on the bonding strength of the rusted reinforced concrete is added, and the calculation accuracy of the model is improved; and the test and calculation cost is saved, and the method has wide social and economic benefits.

Description

Technical Field

[0001] The invention relates to a method, equipment and storage medium for predicting the bonding strength of corroded reinforced concrete, and belongs to the technical field of civil engineering. Background Art

[0002] The impact of steel bar corrosion on the durability of reinforced concrete structures is mainly reflected in the following three aspects: First, corrosion will lead to a reduction in the cross-sectional area of ​​the steel bar, resulting in pitting and cavitation, which will reduce the strength and ductility of the steel bar; Second, the product of steel bar corrosion is rust, which is generally 2-6 times the original volume. Rust accumulates continuously at the junction, and the stress generated will cause the concrete around the steel bar to produce circumferential tensile stress, which in severe cases will cause the concrete protective layer to crack or even peel off. ; Third, good bonding performance is a necessary condition for the normal operation of the structure, but the bonding performance between concrete and steel bars will deteriorate due to the corrosion of steel bars, which will affect the normal use and ultimate bearing capacity of the structure, and even the structure may suffer unpredictable brittle failure. In order to better evaluate the durability of corroded reinforced concrete through theoretical analysis or numerical simulation, it is necessary to fully understand the impact of corrosion on bonding performance.

[0003] The existing model does not consider the influence of factors such as longitudinal reinforcement corrosion rate, stirrup corrosion rate, protective layer thickness, concrete strength, longitudinal reinforcement diameter, stirrup spacing, and anchorage length and longitudinal reinforcement diameter. In particular, there is a lack of research on the relationship between concrete strength and anchorage length and longitudinal reinforcement diameter and other factors on the bond strength of corroded steel bars and concrete. It is generally believed that in the stage of slight corrosion of steel bars, since concrete does not produce rust expansion cracks, the volume expansion of corrosion products can increase friction and mechanical bite force to a certain extent, thereby enhancing the bonding performance of the interface layer. As corrosion increases, excessive rust expansion force will cause the concrete protective layer to tear, and cracks will reduce the lateral constraint capacity and thus reduce the bond strength. Existing studies have shown that the crack initiation time of the specimen is related to the anchorage length of the specimen. The longer the anchorage length, the earlier the crack will develop, and the crack width will gradually increase with the increase of corrosion rate. However, concrete strength is highly correlated with the ultimate bond stress before corrosion, so it is usually not used as part of the overall parameter to represent the lateral constraint. This leads to the fact that when using relative bond strength to characterize the reduction of bond stress due to corrosion, the empirical formula obtained often ignores the effect of concrete strength on bond strength degradation.

[0004] Therefore, failure to consider the concrete strength and the relationship between the anchorage length and the longitudinal bar diameter will result in inaccurate prediction of the bond strength of corroded steel bars and concrete. Summary of the invention

[0005] The purpose of the present invention is to overcome the deficiencies in the prior art and provide a method for predicting the bond strength of corroded steel bars and concrete. By adding a correction coefficient that characterizes the influence of concrete strength and the relationship between anchorage length and longitudinal reinforcement diameter on the bond strength of corroded steel bars and concrete, the problem of inaccurate prediction of the bond strength of corroded steel bars and concrete is solved.

[0006] To achieve the above object, the present invention is implemented by adopting the following technical solutions:

[0007] In a first aspect, the present invention provides a method for predicting the bond strength of corroded steel bars and concrete, comprising:

[0008] Obtain the longitudinal reinforcement corrosion rate, stirrup corrosion rate, protective layer thickness, concrete strength, longitudinal reinforcement diameter, stirrup spacing, anchorage length of the corroded reinforced concrete structural component to be tested, and the bond strength of the non-corroded reinforced concrete structural component;

[0009] Inputting the longitudinal reinforcement corrosion rate, stirrup reinforcement corrosion rate, protective layer thickness, concrete strength, longitudinal reinforcement diameter, stirrup reinforcement spacing, anchorage length and bonding strength of non-corroded reinforced concrete structural components into a pre-constructed corroded reinforced concrete bonding strength prediction model, wherein the pre-constructed corroded reinforced concrete bonding strength prediction model includes: a first correction coefficient calculation model, a second correction coefficient calculation model and a third correction coefficient calculation model;

[0010] The first correction coefficient is calculated using the first correction coefficient calculation model according to the longitudinal reinforcement corrosion rate, the protective layer thickness, the longitudinal reinforcement diameter and the stirrup spacing to obtain the first correction coefficient;

[0011] The second correction coefficient is obtained by calculating the second correction coefficient according to the corrosion rate of the stirrups using the second correction coefficient calculation model;

[0012] The third correction coefficient is calculated by using the third correction coefficient calculation model according to the anchorage length, the longitudinal reinforcement diameter and the concrete strength to obtain the third correction coefficient;

[0013] The bond strength of the corroded reinforced concrete structural member to be tested is obtained by combining the first correction coefficient, the second correction coefficient, the third correction coefficient and the bond strength of the non-corroded reinforced concrete structural member.

[0014] Furthermore, the construction of the prediction model for the bond strength of corroded steel bars and concrete includes:

[0015] Establish a basic data set; the basic data set includes the bond strength in a corroded state, the bond strength in a non-corroded state and the values ​​of influencing factors corresponding to a plurality of specimens; wherein the influencing factors include: longitudinal reinforcement corrosion rate, stirrup corrosion rate, protective layer thickness, concrete strength, longitudinal reinforcement diameter, stirrup spacing and anchorage length;

[0016] A prediction model for the bond strength of corroded reinforced concrete is constructed by introducing a correction coefficient into the bond strength of non-corroded reinforced concrete; the correction coefficient comprises: a first correction coefficient, a second correction coefficient and a third correction coefficient;

[0017] The first correction coefficient represents the influence of the corrosion rate of the longitudinal reinforcement, the thickness of the protective layer, the diameter of the longitudinal reinforcement and the spacing of the stirrups on the bond strength of the corroded reinforced concrete;

[0018] The second correction coefficient represents the influence of the corrosion rate of stirrups on the bond strength of corroded steel bars and concrete;

[0019] The third correction coefficient represents the influence of the concrete strength and the relationship between the anchorage length and the longitudinal bar diameter on the bond strength of corroded steel bars and concrete;

[0020] Constructing each correction coefficient calculation model according to the representation meaning of each correction coefficient;

[0021] Solving the parameters of each correction coefficient calculation model according to the basic data set to obtain a correction coefficient calculation model with determined parameters;

[0022] The prediction model of bond strength of corroded reinforced concrete is obtained by combining the correction coefficient calculation model of determined parameters.

[0023] Furthermore, the first correction coefficient calculation model is: ; in, ; In the formula, is the longitudinal reinforcement corrosion rate, is the degradation coefficient, is the first parameter, is the second parameter, is the third parameter, is the thickness of the protective layer, d is the diameter of the longitudinal reinforcement, is the cross-sectional area of ​​the stirrups, is the number of anchor steel bars, is the stirrup spacing.

[0024] Furthermore, the second correction coefficient calculation model is: ; In the formula, is the stirrup corrosion rate, Is the fourth parameter.

[0025] Furthermore, the third correction coefficient calculation model is: ; In the formula, is the anchorage length, is the concrete strength, is the fifth parameter, is the sixth parameter, It is the seventh parameter.

[0026] Furthermore, the prediction model of the bond strength of corroded steel bars and concrete is: ; In the formula, is the bond strength of uncorroded reinforced concrete.

[0027] Furthermore, solving the parameters of each correction coefficient calculation model according to the basic data set includes:

[0028] The bond strength in the corroded state, the bond strength in the uncorroded state, the longitudinal reinforcement corrosion rate, the stirrup corrosion rate, the protective layer thickness, the concrete strength, the longitudinal reinforcement diameter, the stirrup spacing and the anchorage length values ​​corresponding to all the specimens in the basic data set are stored in a software compiled based on Matlab;

[0029] A symbol library is established in the software compiled based on Matlab, a symbol regression analysis tree is constructed, and the parameter value corresponding to each specimen is calculated by regression method. ;

[0030] For each parameter, an average value is calculated for the values ​​of the parameter corresponding to all the test pieces, and the average value is used as the value of the parameter in the correction coefficient calculation model.

[0031] In a second aspect, the present invention provides an electronic device, comprising: a processor and a memory, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the method for predicting the bond strength of corroded steel bars and concrete as described in the first aspect is implemented.

[0032] In a third aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the method for predicting the bond strength of corroded steel bars and concrete as described in the first aspect is implemented.

[0033] Compared with the prior art, the present invention has the following beneficial effects:

[0034] (1) The method for predicting the bond strength of corroded steel bars and concrete provided by the present invention adds a third correction coefficient to the existing model, which characterizes the influence of concrete strength and the relationship between anchorage length and longitudinal bar diameter on the bond strength of corroded steel bars and concrete. It comprehensively considers the influence of concrete strength, anchorage length, longitudinal bar corrosion, stirrup corrosion, protective layer thickness, longitudinal bar diameter and stirrup spacing on the bond strength of corroded steel bars and concrete, thereby increasing the applicability of the prediction model for the bond strength of corroded steel bars and concrete and improving the calculation accuracy of the prediction model for the bond strength of corroded steel bars and concrete.

[0035] (2) The method for predicting the bond strength of corroded reinforced concrete provided by the present invention can significantly save the test and calculation costs, provide a reference for the durability assessment of engineering structures, and has broad social and economic benefits. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 Flow chart of the method for predicting the bond strength of corroded reinforced concrete provided in Example 1 of the present invention;

[0037] Figure 2 This is a schematic diagram of the concentrated pull-out specimen and beam specimen test collected in Example 2 of the present invention;

[0038] Figure 3 The calculation results and test results after normalization of the existing model in Example 3 of this invention are shown;

[0039] Figure 4 These are the normalized calculation results and test results of the prediction model provided by the present invention in Example 3 of the present invention. DETAILED DESCRIPTION

[0040] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices. The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all of the embodiments.

[0041] Example 1

[0042] According to a first aspect of the present invention, the present invention provides a method for predicting the bond strength of corroded reinforced concrete. Figure 1 As shown, the method comprises the following steps:

[0043] Step 1: Obtain relevant data of the corroded reinforced concrete structural component to be tested.

[0044] Specifically, the bond strength of corroded steel bars and concrete was obtained through field tests. , Bond strength of uncorroded steel bars and concrete , longitudinal reinforcement corrosion rate , stirrup corrosion rate , protective layer thickness , concrete strength , longitudinal reinforcement diameter , stirrup spacing , stirrup cross-sectional area And anchor length .

[0045] Step 2: Input the relevant data into the pre-built prediction model of bond strength of corroded steel bars and concrete, including:

[0046] Step 21: Utilize the first correction coefficient included in the prediction model to calculate the model according to the longitudinal reinforcement corrosion rate , protective layer thickness , longitudinal reinforcement diameter and stirrup spacing Calculate and obtain a first correction coefficient;

[0047] Specifically, the first correction coefficient calculation model is: ; in, ; In the formula, is the degradation coefficient, is the first parameter, is the second parameter, Is the third parameter.

[0048] Step 22: Utilize the second correction coefficient included in the prediction model to calculate the model based on the stirrup corrosion rate Calculate and obtain a second correction coefficient;

[0049] Specifically, the second correction coefficient calculation model is: ; In the formula, Is the fourth parameter.

[0050] Step 23: Calculate the model based on the anchor length using the third correction coefficient included in the prediction model , longitudinal reinforcement diameter and concrete strength Calculate and obtain the third correction coefficient;

[0051] Specifically, the third correction coefficient calculation model is: ; In the formula, is the fifth parameter, is the sixth parameter, It is the seventh parameter.

[0052] Step 3: The bond strength of the corroded reinforced concrete structural member to be tested is obtained by combining the first correction coefficient, the second correction coefficient, the third correction coefficient and the bond strength of the non-corroded reinforced concrete structural member.

[0053] Specifically, the prediction model of the bond strength of corroded steel bars and concrete is: ;

[0054] It should be noted that the first to seventh parameters in this embodiment are known quantities, and the values ​​of the parameters are determined when the bond strength prediction model of corroded reinforced concrete is constructed.

[0055] Example 2

[0056] Based on Example 1, this example provides a method for constructing a prediction model for the bond strength of corroded steel bars and concrete. The construction of the prediction model for the bond strength of corroded steel bars and concrete includes:

[0057] S1: Establish basic data set.

[0058] Specifically, by collecting basic data of corroded reinforced concrete specimens of relevant tests in publicly published literature, the basic data set includes the bond strength in a corroded state, the bond strength in a non-corroded state, the longitudinal reinforcement corrosion rate, the stirrup corrosion rate, the protective layer thickness, the concrete strength, the longitudinal reinforcement diameter, the stirrup spacing and the anchorage length corresponding to each specimen.

[0059] like Figure 2 As described above, the basic data set specimen types established in this embodiment include pull-out specimens and beam specimens.

[0060] In this embodiment, a total of 240 data sets were established, of which 153 data reached critical corrosion. The corrosion rate of the longitudinal reinforcement of the specimens was between 0 and 21%, the corrosion rate of the stirrups was between 0 and 42.3%, the anchorage length ranged from 2d to 10d, the specimen width varied from 150 to 300mm, and the accelerated corrosion method was electrochemical accelerated corrosion.

[0061] The specific data are shown in Table 1:

[0062] Table 1 Bond strength degradation test data set at different corrosion rates

[0063] S2: A prediction model for the bond strength of corroded reinforced concrete is constructed by introducing three correction coefficients to the bond strength of non-corroded reinforced concrete;

[0064] Specifically, the present invention establishes a prediction model for the bond strength of corroded steel bars and concrete by reducing the bond strength of non-corroded steel bars and concrete. Furthermore, by introducing a correction coefficient to represent the degree of reduction of the bond strength of non-corroded steel bars and concrete, and taking into account the mutual influence of multiple influencing factors, the present invention adopts three correction coefficients to characterize the influence of different influencing factors on the bond strength of corroded steel bars and concrete.

[0065] S3: constructing each correction coefficient calculation model according to the representation meaning of each correction coefficient.

[0066] Specifically, considering the low corrosion rate of longitudinal reinforcement ( ), the bond strength of reinforced concrete remains unchanged or slightly increases, and as the corrosion rate of the longitudinal reinforcement increases, the bond strength of reinforced concrete will decrease. The expression of the first correction coefficient is established as: ; in, is the degradation coefficient, which is determined by the thickness of the protective layer , longitudinal reinforcement diameter , stirrup spacing , stirrup cross-sectional area and number of anchor bars Therefore, the first parameter, the second parameter and the third parameter are introduced to establish the degradation coefficient expression as follows: ;

[0067] In summary, the first correction coefficient characterizes the influence of longitudinal reinforcement corrosion rate, cover thickness, longitudinal reinforcement diameter and stirrup spacing on the bond strength of corroded reinforced concrete.

[0068] Specifically, the second correction coefficient represents the influence of the corrosion rate of stirrups on the bond strength of corroded steel bars and concrete; therefore, the fourth parameter is introduced to establish the expression of the second correction coefficient: ;

[0069] Specifically, since concrete strength plays a leading role in bonding performance, and the crack opening time of the specimen is related to the specimen anchoring length, the longer the anchoring length, the earlier the cracks start, and the crack width gradually increases with the increase in corrosion rate. Therefore, the fifth parameter, the sixth parameter, and the seventh parameter are introduced to establish the third correction coefficient expression: ;

[0070] Therefore, the third correction factor characterizes the influence of concrete strength and the relationship between anchorage length and longitudinal bar diameter on the bond strength of corroded steel bars and concrete.

[0071] S4: solving the parameters of each correction coefficient calculation model according to the basic data set to obtain a correction coefficient calculation model with determined parameters. Specifically, it includes:

[0072] The bond strength in the corroded state, the bond strength in the uncorroded state, the longitudinal reinforcement corrosion rate, the stirrup corrosion rate, the protective layer thickness, the concrete strength, the longitudinal reinforcement diameter, the stirrup spacing and the anchorage length values ​​of the 240 specimens were stored in the software compiled based on Matlab.

[0073] A symbol library is established in the software compiled based on Matlab, a symbol regression analysis tree is constructed, and the parameter value corresponding to each specimen is calculated by regression method. ;

[0074] The average value of the same parameter corresponding to all specimens is taken as the value of the parameter in the correction coefficient calculation model, and the result is The values ​​are: -2.68, -0.51, -5.38, -0.49, 1.13, -0.0022, 0.85 respectively.

[0075] S5: The prediction model of the bond strength of corroded reinforced concrete is obtained by combining the correction coefficient calculation model with the determined parameters.

[0076] Specifically, the prediction model of the bond strength of corroded steel bars and concrete is: ; in, ; ; ; .

[0077] Example 3

[0078] This example provides the performance of the method of the present invention in predicting the bond strength of corroded reinforced concrete.

[0079] In order to more intuitively illustrate the accuracy of the prediction model for the bond strength of corroded steel bars and concrete provided by the present invention, the quantitative error index IAE is used to compare the accuracy of the existing model and the prediction model provided by the present invention. The smaller the IAE, the higher the accuracy. The calculation formula of IAE is: ; In the formula, is the predicted value of the bond strength of corroded steel bars and concrete, is the true value of the bond strength of corroded steel bars and concrete.

[0080] Figure 3 The normalized calculation results and test results of the existing model. It can be seen from the figure that the IAE value of the existing model is 0.17.

[0081] Figure 4 The normalized calculation results and test results of the prediction model provided by the present invention are shown in Table 1. The IAE value of the prediction model provided by the present invention is 0.11.

[0082] By comparison, it can be seen that the prediction model provided by the present invention is in good agreement with the test value, and the prediction method for the bond strength of corroded reinforced concrete proposed by the present invention has significantly improved prediction accuracy compared with the existing prediction methods.

[0083] Example 4

[0084] According to the second aspect of the present invention, this embodiment provides an electronic device, including: a processor and a memory, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the method for predicting the bond strength of corroded steel bars and concrete as described in Example 1 is implemented.

[0085] Example 5

[0086] According to a third aspect of the present invention, a computer storage medium is also provided, on which a computer program is stored, and when the computer program is executed by a processor, the method for predicting the bond strength of corroded reinforced concrete as described in Example 1 is implemented. The storage medium may include, for example, a storage component of a tablet computer, a hard disk of a computer, a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a portable compact disk read-only memory (CD-ROM), a USB memory, or any combination of the above storage media. The computer storage medium may be any combination of one or more computer storage media.

[0087] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for predicting the bond strength of corroded steel bars and concrete. It is characterized in that include: Obtain the longitudinal reinforcement corrosion rate, stirrup corrosion rate, protective layer thickness, concrete strength, longitudinal reinforcement diameter, stirrup spacing, anchorage length of the corroded reinforced concrete structural component to be tested, and the bond strength of the non-corroded reinforced concrete structural component; Inputting the longitudinal reinforcement corrosion rate, stirrup reinforcement corrosion rate, protective layer thickness, concrete strength, longitudinal reinforcement diameter, stirrup reinforcement spacing, anchorage length and bonding strength of non-corroded reinforced concrete structural components into a pre-constructed corroded reinforced concrete bonding strength prediction model, wherein the pre-constructed corroded reinforced concrete bonding strength prediction model includes: a first correction coefficient calculation model, a second correction coefficient calculation model and a third correction coefficient calculation model; The first correction coefficient is calculated using the first correction coefficient calculation model according to the longitudinal reinforcement corrosion rate, the protective layer thickness, the longitudinal reinforcement diameter and the stirrup spacing to obtain the first correction coefficient; The second correction coefficient is obtained by calculating the second correction coefficient according to the corrosion rate of the stirrups using the second correction coefficient calculation model; The third correction coefficient is calculated by using the third correction coefficient calculation model according to the anchorage length, the longitudinal reinforcement diameter and the concrete strength to obtain the third correction coefficient; The bond strength of the corroded reinforced concrete structural member to be tested is obtained by combining the first correction coefficient, the second correction coefficient, the third correction coefficient and the bond strength of the non-corroded reinforced concrete structural member.

2. The method for predicting bond strength of corroded reinforced concrete according to claim 1, It is characterized in that The construction of the prediction model for the bond strength of corroded reinforced concrete includes: Establish a basic data set; the basic data set includes the bond strength in a corroded state, the bond strength in a non-corroded state and the values ​​of influencing factors corresponding to a plurality of specimens; wherein the influencing factors include: longitudinal reinforcement corrosion rate, stirrup corrosion rate, protective layer thickness, concrete strength, longitudinal reinforcement diameter, stirrup spacing and anchorage length; A prediction model for the bond strength of corroded reinforced concrete is constructed by introducing a correction coefficient into the bond strength of non-corroded reinforced concrete; the correction coefficient comprises: a first correction coefficient, a second correction coefficient and a third correction coefficient; The first correction coefficient represents the influence of the corrosion rate of the longitudinal reinforcement, the thickness of the protective layer, the diameter of the longitudinal reinforcement and the spacing of the stirrups on the bond strength of the corroded reinforced concrete; The second correction coefficient represents the influence of the corrosion rate of stirrups on the bond strength of corroded steel bars and concrete; The third correction coefficient represents the influence of the concrete strength and the relationship between the anchorage length and the longitudinal bar diameter on the bond strength of corroded steel bars and concrete; Constructing each correction coefficient calculation model according to the representation meaning of each correction coefficient; Solving the parameters of each correction coefficient calculation model according to the basic data set to obtain a correction coefficient calculation model with determined parameters; The prediction model of bond strength of corroded reinforced concrete is obtained by combining the correction coefficient calculation model of determined parameters.

3. The method for predicting bond strength of corroded reinforced concrete according to claim 2, It is characterized in that The first correction coefficient calculation model is: ； in, ； In the formula, is the longitudinal reinforcement corrosion rate, is the degradation coefficient, is the first parameter, is the second parameter, is the third parameter, is the thickness of the protective layer, d is the diameter of the longitudinal reinforcement, is the cross-sectional area of ​​the stirrups, is the number of anchor steel bars, is the stirrup spacing.

4. The method for predicting bond strength of corroded reinforced concrete according to claim 3, It is characterized in that The second correction coefficient calculation model is: ； In the formula, is the stirrup corrosion rate, Is the fourth parameter.

5. The method for constructing a prediction model for bond strength of corroded reinforced concrete according to claim 4, It is characterized in that The third correction coefficient calculation model is: ； In the formula, is the anchorage length, is the concrete strength, is the fifth parameter, is the sixth parameter, It is the seventh parameter.

6. The method for constructing a prediction model for bond strength of corroded reinforced concrete according to claim 4, It is characterized in that The prediction model of bond strength of corroded reinforced concrete is: ； In the formula, is the bond strength of uncorroded reinforced concrete.

7. The method for constructing a prediction model for bond strength of corroded reinforced concrete according to claim 5, It is characterized in that Solving the parameters of each correction coefficient calculation model according to the basic data set includes: The bond strength in the corroded state, the bond strength in the uncorroded state, the longitudinal reinforcement corrosion rate, the stirrup corrosion rate, the protective layer thickness, the concrete strength, the longitudinal reinforcement diameter, the stirrup spacing and the anchorage length values ​​corresponding to all the specimens in the basic data set are stored in the software compiled based on Matlab; A symbol library is established in the software compiled based on Matlab, a symbol regression analysis tree is constructed, and the parameter value corresponding to each specimen is calculated by regression method. ; For each parameter, an average value is calculated for the values ​​of the parameter corresponding to all the test pieces, and the average value is used as the value of the parameter in the correction coefficient calculation model.

8. An electronic device, It is characterized in that include: A processor and a memory, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the method for predicting the bond strength of corroded reinforced concrete according to any one of claims 1 to 7 is implemented.

9. A computer-readable storage medium, It is characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the method for predicting the bond strength of corroded reinforced concrete according to any one of claims 1 to 7 is implemented.

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