Corrosion concrete beam time-varying reliability prediction method fusing magnetic monitoring information

Abstract

The invention discloses a rusted concrete beam time-varying reliability prediction method fusing magnetic monitoring information, and relates to the technical field of civil engineering. Comprising the following steps: scanning a spontaneous leakage magnetic field of the corroded concrete beam, obtaining time-varying spatial distribution monitoring information of the spontaneous leakage magnetic field, generating a spontaneous leakage magnetic quantitative index sequence, obtaining a spatial distribution result of the spontaneous leakage magnetic quantitative index of the corroded concrete beam, dividing the corroded concrete beam, and forming a beam section series system model. Dividing and correcting the spontaneous magnetic flux leakage quantitative index sequence by using a beam section series system model to obtain spontaneous magnetic flux leakage quantitative index sequence subgroups, further generating a probabilistic estimation result of the maximum section corrosion rate of the reinforcing steel bar, calculating time-varying reliability in combination with an external load, obtaining time-sequence spontaneous magnetic flux leakage evolution information of the to-be-predicted corroded concrete beam, and predicting the corrosion rate of the to-be-predicted corroded concrete beam according to the time-sequence spontaneous magnetic flux leakage evolution information of the to-be-predicted corroded concrete beam. And predicting the time-varying reliability of the rusted concrete beam based on the time sequence spontaneous magnetic flux leakage evolution information. The magnetic information acquisition and analysis are simple and convenient, and the method is easy to implement and adapts to complex and changeable actual engineering environments.

Description

Technical Field

[0001] The present invention relates to the technical field of civil engineering, and in particular to a time-varying reliability prediction method for corroded concrete beams integrating magnetic monitoring information. Background Art

[0002] Among a large number of infrastructure facilities, concrete beams are the most widely used structural form. As a metal material, the steel bars in concrete beams will be corroded under the action of oxygen and moisture in the external environment, reducing the cross-sectional area of the steel bars and causing cracking damage to the concrete, resulting in a significant reduction in the reliability and durability of the concrete beams. To ensure the safety of concrete beams, it is necessary to accurately estimate their reliability and durability.

[0003] Currently, the reliability and durability assessment methods for corroded concrete beams are mainly based on theoretical predictions or parametric statistical models. The method based on the theoretical prediction model mainly estimates the steel bar corrosion rate according to environmental parameters and concrete beam material parameters, and uses it in the theoretical model to calculate the time-varying reliability index curve of the corroded concrete beam. The method based on the parametric statistical model mainly establishes a probability distribution model of the steel bar corrosion rate index through sampling of corroded steel bars and numerical statistical analysis of the cross-sectional area, and substitutes it into the calculation model during analysis to obtain the time-varying reliability index curve of the concrete beam. Since the key steel bar corrosion rate information is obtained through theoretical predictions or statistical model analysis, the results of these two methods for the time-varying reliability assessment of existing concrete beams are inaccurate, and it is difficult to adapt to the complex and changeable actual engineering environment, which is not conducive to guiding engineering practice.

[0004] Therefore, providing a time-varying reliability prediction method for corroded concrete beams integrating magnetic monitoring information, which can truly reflect the time-varying characteristics of the reliability and durability of corroded concrete beams in the actual complex environment, is an urgent problem to be solved by those skilled in the art. Summary of the Invention

[0005] In view of this, the present invention provides a time-varying reliability prediction method for corroded concrete beams integrating magnetic monitoring information. The acquisition and analysis of magnetic information are simple, convenient, non-destructive, and easy to implement, and can well adapt to the complex and changeable actual engineering environment.

[0006] To achieve the above object, the present invention adopts the following technical solutions:

[0007] A time-varying reliability prediction method for corroded concrete beams integrating magnetic monitoring information, comprising the following steps:

[0008] S1. Obtain a corroded concrete beam and an external load;

[0009] S2. Scan the spontaneous leakage magnetic field of the corroded concrete beam to obtain the monitoring information of the time-varying spatial distribution of the spontaneous leakage magnetic field;

[0010] S3. Obtain the spontaneous magnetic leakage quantization index sequence based on the monitoring information of the time-varying spatial distribution of the spontaneous magnetic leakage field, and obtain the spatial distribution result of the spontaneous magnetic leakage quantization index of the corroded concrete beam based on the spontaneous magnetic leakage quantization index sequence;

[0011] S4. Divide the corroded concrete beam to form a series system model of beam segments;

[0012] S5. Use the series system model of beam segments to divide and correct the spontaneous magnetic leakage quantization index sequence, obtain the subgroup of the spontaneous magnetic leakage quantization index sequence, and obtain the probabilistic estimation result of the maximum cross-section corrosion rate of the steel bar based on the subgroup of the spontaneous magnetic leakage quantization index sequence;

[0013] S6. Calculate the time-varying reliability by combining the probabilistic estimation result of the maximum cross-section corrosion rate of the steel bar with the external load;

[0014] S7. Obtain the time-series spontaneous magnetic leakage evolution information of the corroded concrete beam to be predicted, and predict the time-varying reliability of the corroded concrete beam based on the time-series spontaneous magnetic leakage evolution information.

[0015] Optionally, the spontaneous magnetic leakage quantization index sequence obtained in S3 includes: extracting the spontaneous magnetic leakage field change information sequence caused by corrosion and calculating and correcting the spontaneous magnetic leakage quantization index Ixm(ti) sequence.

[0016] Optionally, the division and correction of the spontaneous magnetic leakage quantization index sequence in S5 includes:

[0017] At the time series node t i , divide the I xm (t i ) sequence into m subgroups according to the spatial position of the beam segments to obtain the subgroup of the spontaneous magnetic leakage quantization index sequence.

[0018] Optionally, the probabilistic estimation result of the maximum cross-section corrosion rate of the steel bar obtained in S5 includes:

[0019] S51. Take the maximum value of each subgroup of the spontaneous magnetic leakage quantization index sequence to obtain the maximum value sequence [I i (1), I i (2), I i (3), …, I i (m)];

[0020] S52. Determine the likelihood function f[I i (k)|η i that characterizes the mapping relationship between the maximum cross-section corrosion rate of the steel bar and the maximum value of the spontaneous magnetic leakage quantization index;

[0021] S53. Calculate the probabilistic estimation result π[η i |I i (k)];

[0022] S54. Repeat S52 - S53 for m times to obtain the probabilistic estimation results of the maximum cross - section corrosion rate of the steel bars in m beam segments of the corroded concrete beam, π[η i |I i (1)], π[η i |I i (2)], π[η i |I i (3)], …, π[η i |I i (m)].

[0023] Optionally, the calculation of the time - varying reliability in S6 includes:

[0024] S61: Calculate the bending moment effect value within the clear span of the concrete beam according to the external load on the corroded concrete beam;

[0025] S62: Let the time - series node be t i , and extract the coordinates x xm (t i ) of the maximum value of the I 1 , x 2 , x 3 , …, x m in the m beam segments;

[0026] S63: Determine the bending moment effect values M 1 , M 2 , M 3 , …, M m at the coordinates x S1 , M S2 , M S3 , …, M Sm ;

[0027] S64: Based on the probabilistic estimation results of the maximum cross - section corrosion rate, π[η i |I i (1)], π[η i |I i (2)], π[η i |I i (3)], …, π[η i |I i (m)], conduct random sampling to obtain a set of steel bar cross - section corrosion rate sequences [η i (1), η i (2), η i (3), …, η i (m)];

[0028] S65: Apply the calculation theory of the flexural bearing capacity of the concrete beam section. According to the section size of the corroded concrete beam, the strength of the concrete and steel bars, and the cross - section corrosion rate sequence [ηi (1), η i (2), η i (3), …, η i (m)], calculate the flexural bearing capacity values M U1 、M U2 、M U3 、…、M Um ;

[0029] S66: Compare the bending moment effect values M S1 、M S2 、M S3 、…、M Sm and the flexural bearing capacity values M U1 、M U2 、M U3 、…、M Um one by one. When the value of M U is less than the value of M S , it is considered that the corroded concrete beam fails, and let the number of times n f = 1, otherwise take n f = 0;

[0030] S67: Repeat S64 - S66 a total of 1,000,000 times, and count the total number N f of the failure times n f ;

[0031] S68: Calculate the reliability index value β of the corroded concrete beam at the time series node t i ;

[0032] S69: Arrange the reliability index values β of different time series nodes in time series to obtain the time-varying reliability assessment result of the corroded concrete beam integrated with magnetic monitoring information.

[0033] Optionally, predicting the time-varying reliability of the corroded concrete beam in S7 includes:

[0034] S71: Calculate the difference sequence [ΔI(1), ΔI(2), ΔI(3), …, ΔI(m)] between the maximum spontaneous magnetic leakage index sequences [I n and t n-1 (1), I n (2), n (3), …, I

[0035] I n (m)] at the time series nodes t n ;

[0036] S72: Calculate the predicted maximum spontaneous magnetic leakage index sequence [I n+1 at the time series node t n (1) + ΔI(1),

[0037] I n (2) + ΔI(2), I n (3) + ΔI(3), …, I n (m) + ΔI(m)];

[0038] S73: According to [I n (1) + ΔI(1), I n (2) + ΔI(2), I n (3) + ΔI(3), …, I n (m) + ΔI(m)], repeat S51 - S54, S61 - S68 to obtain the prediction result of the reliability index value at the time sequence node t n+1 and realize the time - varying reliability prediction of the corroded concrete beam.

[0039] As can be seen from the above - mentioned technical solutions, compared with the prior art, the present invention provides a method for predicting the time - varying reliability of a corroded concrete beam by integrating magnetic monitoring information, and has the following beneficial effects: 1) The present invention uses the magnetic flux leakage technique to nondestructively detect the distribution characteristics of the corrosion rate of the internal steel bars of the concrete beam and applies it to the time - varying reliability analysis and prediction of the concrete beam, which can well adapt to the complex and changeable actual engineering environment; 2) The present invention does not require theoretical prediction, and the acquisition and analysis of magnetic information are simple, convenient and nondestructive, and are easy to implement; 3) The time - varying reliability results of the corroded concrete beam obtained by the present invention have high accuracy and conform to the actual situation, and are highly applicable to guiding engineering practice. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only the embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained according to the provided drawings.

[0041] Figure 1 is a flowchart of a method for predicting the time - varying reliability of a corroded concrete beam by integrating magnetic monitoring information disclosed by the present invention;

[0042] Figure 2 is a schematic principle diagram of a method for predicting the time - varying reliability of a corroded concrete beam by integrating magnetic monitoring information disclosed by the present invention;

[0043] Figure 3 is a schematic diagram of the detection work disclosed by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0044] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0045] Referring Figure 1 and Figure 2 as shown, the present invention discloses a time-varying reliability prediction method for corroded concrete beams integrating magnetic monitoring information, including the following steps:

[0046] S1. Obtain the corroded concrete beam and external loads;

[0047] S2. Scan the self-induced leakage magnetic field of the corroded concrete beam to obtain the monitoring information of the time-varying spatial distribution of the self-induced leakage magnetic field;

[0048] S3. Obtain the self-induced leakage magnetic quantization index sequence based on the monitoring information of the time-varying spatial distribution of the self-induced leakage magnetic field, and obtain the spatial distribution result of the self-induced leakage magnetic quantization index of the corroded concrete beam based on the self-induced leakage magnetic quantization index sequence;

[0049] S4. Divide the corroded concrete beam to form a series system model of beam segments;

[0050] S5. Use the series system model of beam segments to correct the division of the self-induced leakage magnetic quantization index sequence to obtain subgroups of the self-induced leakage magnetic quantization index sequence, and obtain the probabilistic estimation result of the maximum cross-sectional corrosion rate of the steel bars based on the subgroups of the self-induced leakage magnetic quantization index sequence;

[0051] S6. Calculate the time-varying reliability by combining the probabilistic estimation result of the maximum cross-sectional corrosion rate of the steel bars with the external loads;

[0052] S7. Obtain the time-series self-induced leakage magnetic evolution information of the corroded concrete beam to be predicted, and predict the time-varying reliability of the corroded concrete beam based on the time-series self-induced leakage magnetic evolution information.

[0053] Further, referring Figure 3 as shown, the scanning of the self-induced leakage magnetic field of the corroded concrete beam in S2 includes:

[0054] S21. Select a self-induced leakage magnetic time-series monitoring path covering the entire clear span on the concrete surface outside the tensile steel bars at the bottom of the concrete beam;

[0055] S22: At the time series node t 0 without corrosion, scan and record the self-induced leakage magnetic field variation information of the tensile steel bars at the bottom of the corroded concrete beam along the selected path;

[0056] S23: As the corrosion of the steel bars at the bottom of the beam occurs and develops, at different time series nodes t1 , t 2 , t 3 , …, t n Scan and record the spontaneous leakage magnetic field variation information of the tension reinforcement at the bottom of the corroded concrete beam along the selected path.

[0057] Furthermore, the sequence of spontaneous leakage magnetic quantization indexes obtained in S3 includes: extracting the sequence of spontaneous leakage magnetic field variation information caused by corrosion and calculating the corrected spontaneous leakage magnetic quantization index I xm (t i ) sequence.

[0058] Furthermore, the expression for extracting the sequence of spontaneous leakage magnetic field variation information caused by corrosion is:

[0059]

[0060] Among them, H zx (t i ) and H zz (t i ) are the sequences of the tangential and normal components of the spontaneous leakage magnetic field at the time series node t i . H x (t i ) and H z (t i ) are the sequences of the measured values of the spontaneous leakage magnetic field intensity at the time series node t i . H x (t 0 ) and H z (t 0 ) are the sequences of the measured values of the spontaneous leakage magnetic field intensity at the non-corroded time series node t 0 ;

[0061] Furthermore, calculating the sequence of the corrected spontaneous leakage magnetic quantization index I xm (t i ) sequence includes calculating the sequence of the spontaneous leakage magnetic quantization index I x (t i ) sequence and calculating the sequence of the corrected spontaneous leakage magnetic quantization index I xm (t i ) sequence, and the expression is:

[0062]

[0063] Among them, l is the length of the corroded concrete beam, I xm (l) and I xm (1.5) are the I x theoretical values at the midpoints of the ideal longitudinally magnetized steel bars with lengths of lm and 1.5m respectively.

[0064] Furthermore, forming the beam segment series system model in S4 includes:

[0065] S4: Measure the clear span length of the corroded concrete beam;

[0066] S42: Divide the clear span of the corroded concrete beam into m beam segments with a length of 10 cm each, and regard the corroded concrete beam as a series system model of beam segments.

[0067] Furthermore, the division and correction of the spontaneous magnetic leakage quantification index sequence in S5 include:

[0068] At the time series node t i when, divide the I xm (t i ) sequence into m subgroups according to the spatial position of the beam segments to obtain the subgroup of the spontaneous magnetic leakage quantification index sequence.

[0069] Furthermore, the probabilistic estimation result of the maximum cross-section corrosion rate of the steel bar obtained in S5 includes:

[0070] S51. Take the maximum value of each subgroup of the spontaneous magnetic leakage quantification index sequence to obtain the maximum value sequence [I i (1), I i (2), I i (3), …, I i (m)];

[0071] S52. Determine the likelihood function f[I i (k)|η i that characterizes the mapping relationship between the maximum cross-section corrosion rate of the steel bar and the maximum value of the spontaneous magnetic leakage quantification index;

[0072] S53. Calculate the probabilistic estimation result π[η i |I i (k)], and the expression is:

[0073]

[0074] where π(η i ) is the prior distribution, and Θ is the parameter space (the value range of η i );

[0075] S54. Repeat S52 - S53 a total of m times to obtain the probabilistic estimation results of the maximum cross-section corrosion rate of the steel bar in the m beam segments of the corroded concrete beam π[η i |I i (1)], π[η i |I i (2)], π[η i |I i (3)], …, π[η i |I i (m)].

[0076] Furthermore, the calculation of time-varying reliability in S6 includes:

[0077] S61: Calculate the bending moment effect value within the clear span of the concrete beam according to the external load on the corroded concrete beam;

[0078] S62: Let the time series node be t i , and extract the coordinates x xm (t i ) of the maximum value in the sequence subgroup of I 1 、x 2 、x 3 、…、x m ;

[0079] S63: Determine the bending moment effect values M 1 、M 2 、M 3 、…、M m at the coordinates x S1 、M S2 、M S3 、…、M Sm ;

[0080] S64: Based on the probabilistic estimation results of the maximum cross-section corrosion rate π[η i |I i (1)], π[η i |I i (2)], π[η i |I i (3)], …, π[η i |I i (m)], conduct random sampling to obtain a sequence of steel bar cross-section corrosion rates [η i (1), η i (2), η i (3), …, η i ;

[0081] S65: Apply the calculation theory of the flexural bearing capacity of the concrete beam section, and calculate the flexural bearing capacity values M i (1), M i (2), M i (3), …, M i (m) of the m beam segments according to the cross-section dimensions of the corroded concrete beam, the strengths of the concrete and steel bars, and the sequence of cross-section corrosion rates [η U1 、M U2 、M U3 、…、M Um ;

[0082] S66: Compare the bending moment effect values M S1 、M S2 、M S3 、…、MSm and the flexural bearing capacity value M U1 、M U2 、M U3 、…、M Um are compared one by one. When the value of M U is less than the value of M S , it is considered that the corroded concrete beam fails, and the number of times n f is set to 1. Otherwise, n f is set to 0;

[0083] S67: Repeat S64 - S66 for 1,000,000 times. The sum of the failure times n f for 1,000,000 simulations is N f ;

[0084] S68: Calculate the reliability index value β of the corroded concrete beam at the time series node t i . The expression is:

[0085]

[0086] S69: Arrange the reliability index values β at different time series nodes in time series to obtain the time-varying reliability evaluation result of the corroded concrete beam integrating magnetic monitoring information.

[0087] Furthermore, predicting the time-varying reliability of the corroded concrete beam in S7 includes:

[0088] S71: Calculate the difference sequence [ΔI(1), ΔI(2), ΔI(3), …, ΔI(m)] between the maximum spontaneous magnetic leakage index sequences [I n (1), I n-1 (2), n I n (2),

[0089] I n (3), …, I n (m)] at the time series nodes t

[0090] S72: Calculate the predicted maximum spontaneous magnetic leakage index sequence [I n+1 (1) + ΔI(1), n (1) + ΔI(1),

[0091] I n (2) + ΔI(2), I n (3) + ΔI(3), …, I n (m) + ΔI(m)] at the time series node t

[0092] S73: According to [I n (1) + ΔI(1), I n (2) + ΔI(2), I n(3) + ΔI(3), …, I n (m) + ΔI(m)], repeat S51 - S54, S61 - S68 to obtain the prediction result of the reliability index value at time node t n+1 and realize the time - varying reliability prediction of corroded concrete beams.

[0093] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be obvious to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention will not be limited to these embodiments shown herein, but rather to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for predicting time-varying reliability of corroded concrete beams by integrating magnetic monitoring information, characterized in that: The following steps are involved: S1. Obtain corroded concrete beams and external loads; S2, scanning the spontaneous leakage magnetic field of the corroded concrete beam to obtain the monitoring information of the time-varying spatial distribution of the spontaneous leakage magnetic field; S3. Based on the monitoring information of the time-varying spatial distribution of the spontaneous magnetic leakage field, a spontaneous magnetic leakage quantitative index sequence is obtained, and based on the spontaneous magnetic leakage quantitative index sequence, a spatial distribution result of the spontaneous magnetic leakage quantitative index of the corroded concrete beam is obtained; S4, dividing the corroded concrete beam to form a beam segment series system model; S5. Using the beam-segment series system model, the spontaneous magnetic leakage quantitative index sequence is divided and modified to obtain a subgroup of the spontaneous magnetic leakage quantitative index sequence, and a probabilistic estimation result of the maximum cross-sectional corrosion rate of the steel bar is obtained based on the subgroup of the spontaneous magnetic leakage quantitative index sequence; S6. Calculate the time-varying reliability by using the probabilistic estimation result of the maximum cross-section corrosion rate of the steel bar combined with the external load; S7. Obtaining time-series spontaneous magnetic leakage evolution information of the corroded concrete beam to be predicted, and predicting the time-varying reliability of the corroded concrete beam based on the time-series spontaneous magnetic leakage evolution information.

2. The method for predicting time-varying reliability of corroded concrete beams integrating magnetic monitoring information according to claim 1 is characterized in that: The sequence of spontaneous magnetic leakage quantitative indexes obtained in S3 includes: extracting the spontaneous magnetic leakage field variation information sequence caused by corrosion and calculating and correcting the spontaneous magnetic leakage quantitative index I xm (t i )sequence.

3. The method for predicting time-varying reliability of corroded concrete beams integrating magnetic monitoring information according to claim 1 is characterized in that: The sequence of quantitative indicators for the modified spontaneous magnetic leakage in S5 includes: At timing node t i When I xm (t i ) sequence is divided into m subgroups according to the spatial position of the beam segment, and the spontaneous magnetic leakage quantitative index sequence subgroups are obtained.

4. The method for predicting time-varying reliability of corroded concrete beams integrating magnetic monitoring information according to claim 3 is characterized in that: The probabilistic estimation results of the maximum cross-sectional corrosion rate of steel bars obtained in S5 include: S51, taking the maximum value of each spontaneous magnetic leakage quantitative index sequence subgroup, and obtaining the maximum value sequence [I i (1),I i (2),I i (3),…,I i (m)]; S52, determine the likelihood function f[I i (k)|η i ]; S53, calculate the probabilistic estimate of the corrosion rate of the steel bar section π[η i |I i (k)]; S54, repeat S52-S53 for m times, and obtain the probabilistic estimation result π[η of the maximum cross-sectional corrosion rate of the steel bars in the m beam sections of the corroded concrete beam i |I i (1)],π[η i |I i (2)]、π[η i |I i (3)], …, π[η i |I i (m)].

5. The method for predicting time-varying reliability of corroded concrete beams integrating magnetic monitoring information according to claim 4 is characterized in that: The calculation of time-varying reliability in S6 includes: S61: Calculate the bending moment effect value within the clear span of the concrete beam based on the external load of the corroded concrete beam; S62: Let the timing node be t i , extract m beam segments to obtain I xm (t i ) The coordinates of the maximum values ​​of the subgroups of the sequence x1, x2, x3, ..., x m ; S63: Determine coordinates x1, x2, x3, ..., x m The bending moment effect value M S1 、M S2 、M S3 , …, M Sm ; S64: Based on the probabilistic estimation result of the maximum cross-section corrosion rate π[η i |I i (1)],π[η i |I i (2)]、π[η i |I i (3)], …, π[η i |I i (m)] to obtain a set of steel bar section corrosion rate series [η i (1),η i (2),η i (3),…,η i (m)]; S65: Apply the calculation theory of concrete beam section bending bearing capacity, according to the cross-sectional size of corroded concrete beam, concrete and steel strength and cross-sectional corrosion rate sequence [η i (1),η i (2),η i (3),…,η i (m)], calculate the bending bearing capacity M of m beam segments U1 、M U2 、M U3 , …, M Um ; S66: The bending moment effect value M S1 、M S2 、M S3 , …, M Sm and bending bearing capacity M U1 、M U2 、M U3 , …, M Um Compare them one by one. When M U Value less than M S value, it is considered that the corroded concrete beam has failed, and the number of times n f =1, otherwise take n f =0; S67: Repeat S64-S66 1,000,000 times, and count the number of failures n in 1,000,000 simulations f The sum is N f ; S68: Calculate timing node t i The reliability index value of the corroded concrete beam is β; S69: Arrange the reliability index values ​​β of different time series nodes in time series to obtain the time-varying reliability evaluation result of the corroded concrete beam integrated with the magnetic monitoring information.

6. The method for predicting time-varying reliability of corroded concrete beams integrating magnetic monitoring information according to claim 5 is characterized in that: The time-varying reliability of corroded concrete beams predicted in S7 includes: S71: Calculate timing node t n and t n-1 The maximum value sequence of spontaneous magnetic flux leakage index [I n (1),I n (2), I n (3),…,I n (m)]; the difference sequence between them [ΔI(1), ΔI(2), ΔI(3), …, ΔI(m)]; S72: Calculate timing node t n+1 The maximum prediction sequence of spontaneous magnetic flux leakage index [I n (1)+ΔI(1), I n (2)+ΔI(2),I n (3)+ΔI(3),…,I n (m)+ΔI(m)]; S73: According to [I n (1)+ΔI(1),I n (2)+ΔI(2),I n (3)+ΔI(3),…,I n (m)+ΔI(m)], repeat S51-S54, S61-S68, and obtain the timing node t n+1 The reliability index value prediction results are used to realize the time-varying reliability prediction of corroded concrete beams.

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