Prestressed concrete bridge damage detection method based on FWD

Abstract

The invention relates to an FWD-based prestressed concrete bridge damage detection method. The method comprises the following steps: S1, acquiring an actually measured displacement value of a target prestressed concrete bridge; s2, establishing a finite element forward model of the target prestressed concrete bridge; s3, adopting a forward difference method to obtain a calculation displacement value; s4, constructing a sensitivity matrix and an error vector matrix according to the actually measured displacement value and the calculated displacement value; s5, acquiring a parameter adjustment amount according to a ratio of the error vector matrix to the sensitivity matrix; s6, performing parameter adjustment on the finite element forward model according to the parameter adjustment amount, adding one to the number of iterations, returning to S3 until the calculated peak value and the actually measured peak value reach the control precision, and obtaining different types of damage indexes after iteration; and S7, judging the damage degree of the bridge according to the ratio of the iterated different types of damage indexes to the initially preset different types of damage indexes. According to the invention, real-time monitoring and rapid evaluation of the bridge state can be realized.

Description

Technical Field

[0001] The invention relates to the technical field of bridge damage detection, and in particular to a prestressed concrete bridge damage detection method based on FWD. Background Art

[0002] With the rapid development of the transportation industry, the construction of roads and bridges has increased significantly, especially prestressed concrete bridges, which are widely used due to their superior mechanical properties and economic benefits. However, with the increase in service life, these bridges face problems such as fatigue, environmental erosion and material aging, which lead to structural damage and seriously affect driving safety and service life. Therefore, damage detection and health assessment of prestressed concrete bridges are particularly important to provide reliable data support for bridge maintenance and management.

[0003] Traditional bridge inspection methods mostly rely on manual visual inspection, acoustic inspection or ultrasonic technology. Although these methods have certain application value, they have problems such as low inspection efficiency, narrow inspection coverage and complex operation. In addition, with the increasing complexity of bridge structures, traditional inspection methods are difficult to fully reflect the actual health status of the structure. Therefore, there is an urgent need to develop a new, efficient and economical inspection technology to meet the needs of modern bridge health monitoring.

[0004] In recent years, the drop-weight deflectometer, as a vibration-based nondestructive testing device, has been widely used in road and bridge inspection and evaluation because it simulates the actual vehicle load well, has fast measurement speed and high accuracy. This device measures the response of the pavement structure through the shock wave generated by the drop-weight, can effectively evaluate the stiffness and bearing capacity of the pavement structure, and judge the degree of damage to the structure through data information.

[0005] At present, the evaluation technology of falling weight deflectometer (FWD) in pavement health monitoring has been relatively mature and has been widely promoted and used in practical applications. However, for the identification of bridge damage, especially prestressed bridges, the existing methods and technical means still cannot effectively meet the actual needs. Summary of the invention

[0006] The purpose of the present invention is to provide a prestressed concrete bridge damage detection method based on FWD, so as to realize real-time monitoring and rapid evaluation of the bridge status.

[0007] To achieve the above object, the present invention provides the following solutions:

[0008] A prestressed concrete bridge damage detection method based on FWD, comprising:

[0009] S1. Apply pulse load to the target prestressed concrete bridge to obtain the measured displacement value;

[0010] S2. Establishing a finite element forward model of the target prestressed concrete bridge and determining a damage index of the target prestressed concrete bridge;

[0011] S3, setting an initial value, using a forward difference method, and calculating the dynamic displacement values ​​of different types of damage indicators in this iteration according to the finite element forward model to obtain a calculated displacement value;

[0012] S4, obtaining a data matrix according to the measured deflection value and the calculated displacement value, and constructing a sensitivity matrix and an error vector matrix according to the data matrix;

[0013] S5. Obtaining a parameter adjustment amount according to a ratio of the error vector matrix to the sensitivity matrix;

[0014] S6, adjusting the parameters of the finite element forward model according to the parameter adjustment amount, increasing the number of iterations by one and returning to S3 until the calculated peak value and the measured peak value reach the control accuracy to obtain different types of damage indicators after iteration;

[0015] S7. Determine the degree of damage to the bridge according to the ratio of the different types of damage indicators after iteration to the different types of damage indicators initially preset.

[0016] Optionally, applying a pulse load to the target prestressed concrete bridge in S1 to obtain the measured displacement value includes: applying a pulse load to the target prestressed concrete bridge using a drop weight deflectometer to obtain the measured displacement value.

[0017] Optionally, the damage index includes: the local top plate stiffness of the target prestressed concrete bridge, the remaining full bridge stiffness and the residual prestress.

[0018] Optionally, the data matrix in S4 is:

[0019]

[0020] Among them, D n is the data matrix at the nth iteration, is the calculated dynamic displacement of the ith measuring point along the radial direction at the mth type, where m is the number of damage types.

[0021] Optionally, constructing a sensitivity matrix according to the data matrix in S4 includes:

[0022] A sensitivity calculation method is used to obtain the sensitivity of the calculated displacement value to the adjusted damage type index, and the sensitivity matrix is ​​constructed;

[0023] The sensitivity matrix is:

[0024]

[0025] Among them, F n is the sensitivity matrix, Indicates the iterative calculation offset value of the i-th measuring point at the n-th iteration. They respectively represent the iteration step size of the m-th damage parameter at the n-th iteration.

[0026] Optionally, obtaining an error vector matrix according to the data matrix in S4 includes: subtracting the second row of data from the first row of data in the data matrix of each iteration to obtain the error vector matrix.

[0027] Optionally, adjusting parameters of the finite element forward model according to the parameter adjustment amount in S6 includes: obtaining model parameters of the mth type of damage indicator in this iteration according to the model parameters and parameter adjustment amount of the mth type of damage indicator in the previous iteration, and adjusting parameters of the finite element forward model.

[0028] The beneficial effects of the present invention are:

[0029] 1. Intelligent assessment: Combining the drop weight deflectometer with bridge damage detection can quickly assess the use status of the components and overall structure of the prestressed concrete bridge. At the same time, combined with the system identification inversion technology, it can accurately determine the location and extent of the damage, providing more scientific guidance for the subsequent design, construction and maintenance of prestressed concrete bridges;

[0030] 2. High-precision detection: The drop-weight deflectometer can provide accurate deflection data (displacement value). Combined with system identification technology, the detection error is further reduced to less than 5%. This method combines dynamic monitoring and in-depth analysis to help accurately assess the degree and mode of bridge damage;

[0031] 3. Non-destructive testing: This method uses non-destructive means to conduct testing, which will not cause any damage to the bridge structure, thus ensuring the safety of the bridge;

[0032] 4. Economical and efficient: Compared with traditional bridge inspection methods, the combination of drop weight deflectometer and system identification technology usually has lower costs, and performs well in inspection speed and accuracy, greatly improving work efficiency and safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0034] Figure 1This is a flow chart of a prestressed concrete bridge damage detection method based on FWD according to an embodiment of the present invention;

[0035] Figure 2 A schematic diagram of a system identification inversion process according to an embodiment of the present invention;

[0036] Figure 3 Schematic diagram of a finite element forward model according to an embodiment of the present invention. DETAILED DESCRIPTION

[0037] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0038] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0039] This embodiment provides a prestressed concrete bridge damage detection method based on FWD, including:

[0040] S1. Apply pulse load to the target prestressed concrete bridge to obtain the measured displacement value;

[0041] S2. Establish a finite element forward model of the target prestressed concrete bridge and determine the damage index of the target prestressed concrete bridge;

[0042] S3. Using the forward difference method, the dynamic displacement values ​​of different types of damage indicators in this iteration are calculated according to the finite element forward model to obtain the calculated displacement values;

[0043] S4. Obtain a data matrix according to the measured deflection values ​​and the calculated displacement values, and construct a sensitivity matrix and an error vector matrix according to the data matrix;

[0044] S5. Obtain parameter adjustment amounts according to a ratio of the error vector matrix to the sensitivity matrix;

[0045] S6. Adjust the parameters of the finite element forward model according to the parameter adjustment amount, increase the number of iterations by one and return to S3 until the calculated peak value and the measured peak value reach the control accuracy, and obtain different types of damage indicators after iteration;

[0046] S7. Determine the degree of damage to the bridge according to the ratio of the different types of damage indicators after iteration to the different types of damage indicators initially preset.

[0047] In this embodiment, obtaining the measured displacement value includes: setting a suitable weight load level, using a drop weight deflectometer to test and record the dynamic response of the prestressed concrete bridge in the local detection area of ​​interest, extracting the displacement value of each radial measuring point, and sorting the response data, i.e., the displacement value, to obtain the target actual eigenvector f k .

[0048] f k =[f1 k ,f2 k ,...,f i k ]

[0049] In the formula, f k is the measured true value, and i is the corresponding acquisition point number along the radial direction.

[0050] The dynamic finite element method is used to establish a finite element forward model of the prestressed concrete bridge structure, and the dynamic displacement simulation drop weight displacement value of the bridge under the pulse load of FWD is calculated, including:

[0051] obtaining design documents for the bridge and response data during operation of the bridge;

[0052] According to the bridge design documents and the corresponding mechanical data, a prestressed concrete refined model is established using finite element software ABAQUS, which is used as the basic forward model of the present invention to wait for numerical simulation calculation;

[0053] By applying the pulse load of actual FWD, the theoretical displacement of prestressed concrete is calculated based on the dynamic implicit finite element theory.

[0054] Furthermore, the damage type indicators include: local top plate stiffness of the target prestressed concrete bridge, the remaining full bridge stiffness, and the residual prestress.

[0055] Furthermore, the data matrix in S4 is:

[0056]

[0057] Among them, D n is the data matrix at the nth iteration, is the calculated dynamic displacement of the ith measuring point in the radial direction at the mth type, where m is the number of damage types. When m = 1, the forward model parameters adopt the top plate stiffness benchmark trial value. When m=2, the remaining full bridge stiffness benchmark calculation values When m=3, the residual prestressing value is calculated based on the baseline The first iteration of each benchmark value takes the initial trial value; when m = 1, the forward model parameters use the top plate stiffness iteration value The remaining parameters remain unchanged; and so on.

[0058] Specifically, the damage type index of prestressed concrete bridges is established, and the calculated dynamic displacement values ​​of different damage type indexes in the iteration process are designed by the forward difference method. The actual displacement values ​​measured by the drop weight deflectometer and the displacement values ​​calculated by the finite element model are sorted out to obtain a data matrix, which specifically includes:

[0059] According to the damage type of the prestressed concrete bridge, the relevant damage index is determined, and the number is 3, including the local top plate stiffness of the prestressed concrete bridge, the remaining stiffness of the whole bridge and the residual prestress;

[0060] According to the calculation range of concrete elastic modulus of the top slab of the prestressed concrete bridge and the whole bridge and the range of prestress level, the initial calculation value of the top slab in the drop weight area is determined respectively. The rest of the full bridge initial calculation values Initial calculation value of residual prestress

[0061] Design a mathematical function model f(p) of the output parameter p of the system based on the forward model construction

[0062] f(p)=f(p1,p2,...,p m ,x i ,t i )

[0063] In the formula, f i (p) is a nonlinear function of the model parameters, p m is the output parameter of the mth damage type, x i ,t i are independent spatial and temporal variables.

[0064] The forward difference method is used to design a suitable iteration step size, and the response values ​​of the three types of damage in the iteration process are calculated respectively. The response data are sorted to obtain a data matrix.

[0065] Furthermore, in S4, based on the data matrix, a sensitivity matrix is ​​constructed including:

[0066] The sensitivity calculation method is used to obtain the sensitivity of the calculated displacement value to the adjusted damage type index and construct a sensitivity matrix;

[0067] The sensitivity matrix is:

[0068]

[0069] Among them, F n is the sensitivity matrix, Indicates the iterative calculation offset value of the i-th measuring point at the n-th iteration. They respectively represent the iteration step size of the m-th damage parameter at the n-th iteration.

[0070] Specifically, based on the obtained data matrix, the sensitivity analysis method is used to calculate the sensitivity of the response to the parameters of the adjusted damage type and obtain the partial derivatives of the system output to the model parameters to construct the sensitivity matrix F.

[0071] Furthermore, obtaining the error vector matrix according to the data matrix in S4 includes: subtracting the second row of data from the first row of data in the data matrix of each iteration to obtain the error vector matrix.

[0072] Furthermore, adjusting the parameters of the finite element forward model according to the parameter adjustment amount in S6 includes: obtaining the model parameters of the mth type of damage indicator in this iteration according to the model parameters and parameter adjustment amount of the mth type of damage indicator in the previous iteration, and adjusting the parameters of the finite element forward model.

[0073] The model parameters are iteratively adjusted through the parameter adjustment method, and finally the control parameter adjustment amount is used to characterize the convergence of the iterative model, so as to judge the degree of various types of bridge damage according to the iterative convergence results.

[0074] The above analysis method can quickly evaluate the local top plate stiffness of the prestressed bridge, the stiffness of the rest of the bridge, and the size of the residual prestress based on the dynamic response data collected from the actual bridge, accurately reflect the usage status of each component and the overall structure of the prestressed bridge, and provide guidance for the subsequent design, construction and maintenance of prestressed concrete bridges.

[0075] The present invention will be further described below in conjunction with the accompanying drawings:

[0076] like Figure 1-Figure 2 As shown, a prestressed concrete bridge damage detection method based on FWD specifically includes the following steps:

[0077] Step 1: In the field test, the FWD device weight load level was selected as 25T, and 7 sensors were installed along the load plate at different horizontal positions (i.e. 0cm, 20cm, 30cm, 45cm, 60cm, 90cm and 120cm) from the load center.

[0078] Furthermore, a drop weight deflectometer is used to measure the dynamic displacement of the local area of ​​interest on the prestressed concrete bridge and record the dynamic response of the prestressed concrete bridge, from which the dynamic displacement value of each radial measuring point is extracted, and the maximum response value of each measuring point in the dynamic displacement time history curve, i.e., the displacement peak value, is sorted out to obtain the target actual eigenvector f k .

[0079] f k =[f1 k,f2 k ,...,f i k ]

[0080] Among them, f k is the measured true value, i is the corresponding acquisition point number along the radial direction

[0081] Step 2: Obtain the design documents of the bridge and the response data during the operation of the bridge. According to the bridge design documents and the corresponding mechanical data, the finite element software ABAQUS is used to establish a refined model of prestressed concrete, which is used as the basic forward model of this embodiment to be used for numerical simulation calculation. The finite element forward model is as follows: Figure 3 shown.

[0082] Step 3: According to the damage type of the prestressed concrete bridge, determine the number of related damage index types m, which is 3, including the local top plate stiffness of the prestressed concrete bridge, the remaining full bridge stiffness and the residual prestress.

[0083] Furthermore, in combination with a specific bridge engineering example, the benchmark values ​​of various damage index parameters are formulated, that is, the value range of the above damage parameters is determined, and the initial trial values ​​of various damage indicators are determined, among which the initial trial value is the value for starting iteration, and the experimental design value is the value for judging the degree of convergence of the final iteration. The smaller the difference between the iteration result and the experimental design value, the higher the accuracy. The range of variation of various damage parameters and the values ​​of the initial trial values ​​in this example are shown in Table 1:

[0084] Table 1

[0085]

[0086] Furthermore, a mathematical function model f(p) of the damage type parameter p is designed based on the forward model:

[0087] f(p)=f(p1,p2,...,p m ,x i ,t i )

[0088] Among them, f i (p) is a nonlinear function of the model parameters, p m is the output parameter of the mth damage type, x i ,t i are independent spatial and temporal variables.

[0089] Furthermore, the initial value, i.e., the initial trial value, is set, the forward difference method is used, and an appropriate iteration step is selected. The displacement values ​​of the three types of damage in the iteration process are calculated based on the forward model. In this example, the iteration step of each type of damage parameter in a single iteration is equal to 5% of the benchmark trial value of that iteration.

[0090] Furthermore, the displacement data under a single iteration is sorted to obtain the data matrix D n :

[0091]

[0092] Among them, D n is the data matrix at the nth iteration, is the calculated dynamic displacement of the i-th measuring point in the radial direction at the m-th type, obtained by calculating the mathematical function model of parameter p, where m is the number of damage types. When m = 1, the forward model parameters use the top plate stiffness benchmark trial value When m=2, the remaining full bridge stiffness benchmark calculation values When m=3, the residual prestressing value is calculated based on the baseline The first iteration of each benchmark value takes the initial trial value; when m = 1, the forward model parameters use the top plate stiffness iteration value The remaining parameters remain unchanged; and so on.

[0093] Step 4: Based on the data matrix obtained in step 3, the sensitivity analysis method is used to calculate the sensitivity of the response to the parameters of the adjusted damage type and obtain the partial derivatives of the system output to the model parameters to construct the sensitivity matrix F:

[0094]

[0095] in, Indicates the iterative calculation offset value of the i-th measuring point at the n-th iteration; They respectively represent the iteration step size of the m-th damage parameter at the n-th iteration.

[0096] Furthermore, the data matrix D of each iteration is n Subtract the second row of data from the first row of data to get the error vector matrix r n :

[0097]

[0098] Furthermore, the inverse equation of the bridge structure damage parameters is constructed, and the singular value decomposition method is used to solve the parameter adjustment α:

[0099] F n α n =r n

[0100] Step 5: Based on Python and Abaqus, develop an automatic iteration program to iteratively adjust the model parameters through the parameter adjustment method. The adjustment equation is as follows:

[0101]

[0102] in, is the model parameter of the mth type of damage indicator at the nth iteration, is the model parameter of the mth type of damage index at the n-1th iteration, is the parameter adjustment amount calculated after the n-1th iteration for the mth type damage indicator parameter.

[0103] Furthermore, to ensure that the difference between the calculated peak value and the measured peak value is within the control accuracy requirement, a root mean square error function is defined to quantify the deviation between the calculated results and the measured data as the optimization target in the iterative process.

[0104]

[0105] Among them, r n is the error vector, n is the number of iterations, and i is the number of measurement points.

[0106] Furthermore, during the iteration process, the speed and stability of error convergence can be controlled by adjusting the change in relative parameters. The calculation formula is as follows:

[0107]

[0108] Among them, PT represents the relative parameter adjustment amount, represents the iterative value of the mth type damage parameter at the n-1th iteration, It represents the iteration value of the mth type damage parameter at the nth iteration.

[0109] Furthermore, the error and model parameters of each iteration are monitored, and the degree of damage of the bridge is evaluated by judging the convergence status. When the change of the mean square error between two consecutive iterations or the relative parameter adjustment is less than 5%, that is, the system has reached the required accuracy. When the system reaches the convergence standard, it indicates that the required calculation accuracy has been met, thereby completing the effective identification and damage assessment of the model. The degree of damage to the bridge is judged based on the ratio of different types of damage indicators after the iteration is completed to the initial preset different types of damage indicators, where the initial preset different types of damage indicators are the initial damage indicators of the bridge material, which are obtained according to the bridge design parameters.

[0110] Furthermore, according to the above method, the damage parameter adjustment values ​​of various prestressed concrete beams can be obtained, as shown in Table 2.

[0111] Table 2

[0112]

[0113] Among them, parameter p1 represents the local top plate stiffness, parameter p2 represents the remaining full bridge stiffness (MPa), and parameter p3 represents the residual prestress (MPa)

[0114] Furthermore, through the calculation results of the above-mentioned damage parameter adjustment tables for various prestressed concrete beams, it can be seen that the various damage parameters are basically consistent with their experimental set values, indicating that the calculation accuracy of this method is high. At the same time, it can be seen that the local top plate stiffness, which is most sensitive to the dynamic response of the bridge, converges quickly, while the remaining stiffness of the entire bridge, which is least sensitive to it, converges slowly.

[0115] In order to ensure the reliability and wide applicability of the FWD test method and the damage assessment method for prestressed concrete bridges, several different damage conditions were supplemented according to the design values ​​of different model parameters. Table 3 shows the inversion results and accuracy analysis table under different design conditions.

[0116] Table 3

[0117]

[0118] Furthermore, the back-calculation error of the local top stiffness identified by the system identification method is the smallest, which is 0.23%; the back-calculation error of the remaining stiffness of the entire bridge is the largest, which is 1.23%, but both are kept within 5%, indicating that this method can achieve high accuracy in the inverse analysis of damage parameters of prestressed concrete bridges, proving its reliability and versatility.

[0119] The embodiments described above are only descriptions of the preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Without departing from the design spirit of the present invention, various modifications and improvements made to the technical solutions of the present invention by ordinary technicians in this field should all fall within the protection scope determined by the claims of the present invention.

Claims

1. A prestressed concrete bridge damage detection method based on FWD, characterized in that: include: S1. Apply pulse load to the target prestressed concrete bridge to obtain the measured displacement value; S2. Establishing a finite element forward model of the target prestressed concrete bridge and determining a damage index of the target prestressed concrete bridge; S3, using the forward difference method, respectively calculating the dynamic displacement values ​​of different types of damage indicators in this iteration according to the finite element forward model, and obtaining the calculated displacement values; S4, obtaining a data matrix according to the measured displacement values ​​and the calculated displacement values, and constructing a sensitivity matrix and an error vector matrix according to the data matrix; S5. Obtaining a parameter adjustment amount according to a ratio of the error vector matrix to the sensitivity matrix; S6, adjusting the parameters of the finite element forward model according to the parameter adjustment amount, increasing the number of iterations by one and returning to S3 until the calculated peak value and the measured peak value reach the control accuracy, and obtaining different types of damage indicators after iteration; S7. Determine the degree of damage to the bridge according to the ratio of the different types of damage indicators after iteration to the different types of damage indicators initially preset.

2. The FWD-based prestressed concrete bridge damage detection method according to claim 1 is characterized in that: In S1, applying a pulse load to the target prestressed concrete bridge to obtain the measured displacement value includes: applying a pulse load to the target prestressed concrete bridge using a drop weight deflectometer to obtain the measured displacement value.

3. The FWD-based prestressed concrete bridge damage detection method according to claim 1, characterized in that: The damage index includes: the local top plate stiffness of the target prestressed concrete bridge, the remaining stiffness of the entire bridge and the residual prestress.

4. The prestressed concrete bridge damage detection method based on FWD according to claim 1 is characterized in that: The data matrix in S4 is: Among them, D n is the data matrix at the nth iteration, is the calculated dynamic displacement of the i-th measuring point in the radial direction at the m-th type, m is the number of damage types, and f i k is the true value of the measurement.

5. The FWD-based prestressed concrete bridge damage detection method according to claim 1, characterized in that: In S4, constructing a sensitivity matrix according to the data matrix includes: A sensitivity calculation method is used to obtain the sensitivity of the calculated displacement value to the adjusted damage type index, and the sensitivity matrix is ​​constructed; The sensitivity matrix is: Among them, F n is the sensitivity matrix, Indicates the iterative calculation offset value of the ith measurement point at the nth iteration. They respectively represent the iteration step size of the m-th damage parameter at the n-th iteration.

6. The prestressed concrete bridge damage detection method based on FWD according to claim 1 is characterized in that: In S4, obtaining an error vector matrix according to the data matrix includes: subtracting the second row of data from each row of data in the data matrix to obtain an error vector matrix.

7. The FWD-based prestressed concrete bridge damage detection method according to claim 1, characterized in that: The step of adjusting the parameters of the finite element forward model according to the parameter adjustment amount in S6 includes: obtaining the model parameters of the mth type of damage indicator in this iteration according to the model parameters and parameter adjustment amount of the mth type of damage indicator in the previous iteration to adjust the parameters of the finite element forward model.

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