A rapid test and evaluation method for the bearing capacity of integral box girder bridges

Abstract

The present invention belongs to the technical field of structural safety detection, and discloses a rapid test and evaluation method for the bearing capacity of integral box girder bridges. It conducts rapid static and dynamic tests on box girder bridges, obtains a finite element model for bearing capacity evaluation benchmark of box girder bridges, and conducts structural bearing capacity evaluation based on the benchmark model. The present invention utilizes a moving load to quickly cross the bridge, realizing the rapid test and acquisition of the quasi-influence coefficient and dynamic characteristics of the bridge structure, effectively solving the problems of high cost and long time of traditional load experiments. The finite element model for bearing capacity evaluation benchmark of the bridge is obtained by using model correction technology, enabling the model to simultaneously match the overall and local static and dynamic characteristics of the actual bridge, and making up for the problem of distorted optimization results of a single objective function. In addition, the proposed bearing capacity evaluation method can consider the differences in the bearing capacities of different stressed members, solving the problem that traditional calculation coefficients are prone to poor consistency in the bearing capacity evaluation results of different members.

Description

Technical Field

[0001] The present invention belongs to the technical field of structural safety detection, and particularly relates to a rapid test and evaluation method for the load-bearing capacity of integral box girder bridges. Background Art

[0002] In the past few decades, the cause of bridge construction has witnessed vigorous development, and the number of bridges in our country has reached hundreds of thousands. Due to its strong spanning ability and good overall mechanical performance, integral box girder bridges are widely used in the construction of highway bridges. The designed service life of bridges is up to several decades or even a hundred years. During the operation period, environmental impacts, material aging, and the long-term action of vehicle loads will pose a great threat to the operation safety of bridges and have a great impact on the safe load-bearing capacity of bridges. Once an accident occurs, it will seriously hinder traffic, causing economic losses and casualties. Therefore, in order to ensure the safe operation of bridges, regularly evaluating the load-bearing capacity of bridges is an essential part of the bridge maintenance and management process.

[0003] Box girder bridges are usually important transportation hubs, and their load-bearing capacity is one of the most important performances of box girder bridges. At present, the evaluation of the load-bearing capacity of bridges is usually carried out in accordance with the Specifications for Inspection and Evaluation of Load-bearing Capacity of Highway Bridges (JTG J21-2011) and the Specifications for Load Test of Highway Bridges (JTG / T J21-01-2015), by combining technical investigation, load test and analysis and calculation. However, evaluating the load-bearing capacity through load tests requires long-term traffic closure and renting a large number of heavy trucks to load the bridge to make the control section reach the specified value, which is time-consuming and laborious, and there is a potential risk of damaging the bridge structure. Therefore, how to develop a rapid test method to replace the traditional load test has become an urgent problem to be solved in the evaluation of the load-bearing capacity of bridges.

[0004] In addition, in the traditional bearing capacity assessment method, the check calculation coefficient obtained by converting the results of the load test is used to correct the resistance effect, and then the bearing capacity assessment is carried out. This measure is to reflect the performance difference between the design model and the actual bridge. However, this measure simplifies the difference between the true and theoretical performance of the structure into the same coefficient for consideration, believing that the degradation conditions at different positions and different ultimate states of the bridge are the same, which also deviates from the actual situation and will cause the assessment results to be conservative or dangerous. In addition, the calculation of the load effect and the bridge assessment are both based on the design model or simplified model, which is inconsistent with the current bridge performance. Therefore, it is necessary to correct the resistance result through the load test. Therefore, if there is a model that can reflect the true state of the bridge, the load effect and resistance effect of the bridge can be directly compared using this model, so as to more accurately assess whether the bearing capacity of the bridge meets the standard. A more realistic model means that the different positions and different ultimate states of the bridge can be judged separately, avoiding the conservative or dangerous assessment results caused by correcting the resistance through the check calculation coefficient.

[0005] Therefore, to study a rapid test and assessment method for the bearing capacity of integral box girder bridges can not only effectively improve the bridge test efficiency and reduce the test cost, but also significantly improve the accuracy and rationality of the bridge bearing capacity by using the corrected finite element model. Therefore, the present invention is of great significance for assessing the bearing capacity of integral box girder bridges. Summary of the Invention

[0006] The object of the present invention is to provide a rapid test and assessment method for the bearing capacity of integral box girder bridges, and the specific steps are as follows:

[0007] Step 1. Rapid static and dynamic test of box girder bridge

[0008] (1.1) Obtain the quasi-influence coefficient through the moving load test

[0009] The quasi-influence coefficient is obtained by collecting the structural vehicle-induced response data generated by a two-axle test vehicle passing through the bridge; the mass of the test vehicle should make the bridge generate stable response data with a high signal-to-noise ratio;

[0010] The vehicle loading principle is to cover most of the driving areas of the bridge with fewer vehicle driving times; the loading process meets the following criteria: 1) The vehicle drives through the bridge at a low speed of no more than 5 km / h to minimize the dynamic effect of the vehicle on the structure; 2) The vehicle drives straight through the bridge in a single lane and cannot switch lanes midway; 3) According to the number of design lanes of the bridge, the vehicle must drive at least once completely in each lane;

[0011] The vehicle-induced response of the structure to be measured is the strain or deflection of the main girder. To improve the signal-to-noise ratio of the measured data of the vehicle-induced response of the structure, the measurement positions are selected at the mid-span and quarter-span sections of the main girder to ensure obtaining a larger vehicle-induced response. When measuring the deflection of the main girder, the distribution of the deflection is basically the same across the entire section, so at least 2 measuring points should be symmetrically arranged on the bottom surface of the main girder. When measuring the strain of the main girder, considering the large differences in the measured strain values on the same section of the box girder, the strain measuring points should be evenly arranged at the bottom plate of the box girder, and the number of strain sensors should be no less than 2n - 1, where n is the number of web members in the cross-section of the vector, to obtain a relatively complete strain distribution of the bottom plate of the main girder.

[0012] (1.2) Obtain the dynamic characteristics of the structure through dynamic tests

[0013] Identify the modal parameters of the bridge by collecting the acceleration response of the main girder under the forced vibration of the bridge structure. The excitation method for the bridge is wind load, applying random environmental unknown excitation or artificially applied known excitation, and identifying the modal parameters of this excitation.

[0014] The main measurement of the dynamic response is the acceleration response, which is obtained through accelerometers installed on the structure. The measuring points are arranged in a mesh form to obtain the acceleration response of the entire bridge and the complete vibration mode of the bridge deck. To obtain a relatively smooth vibration mode of the bridge deck, the measuring points should meet a certain density arrangement. The arrangement of the longitudinal bridge sensors should make the vibration mode curve relatively smooth, and the transverse bridge sensors should be arranged in at least two rows or more to identify the torsional vibration mode of the bridge.

[0015] Step 2. Obtain the evaluation model of the box girder bridge

[0016] (2.1) Finite element modeling method for box girder bridges;

[0017] The finite element model of the bridge is established using shell elements. The web, top plate, and bottom plate of the box girder section are all established by shell elements with the same actual thickness as the component. Spring elements are used to add additional stiffness at the bridge bearings to consider the situation where the constraint conditions of the bridge bearings are not ideal simply supported.

[0018] (2.2) Establish the objective function for correcting the finite element model of the bridge

[0019] There are differences between the initial finite element model of the bridge and the actual bridge structure. It is necessary to establish an objective function for model optimization and obtain a finite element model that conforms to the actual structure through the method of model correction. The objective function for optimizing the parameters of the initial finite element model of the bridge consists of three parts, namely the strain, frequency, and vibration mode objective functions.

[0020] Establish a multi - measurement - point strain objective function based on the principle of equal axial forces in the main girder bottom plate; there is a cubic function relationship between the strain of the box girder and the lateral position. Fit the strain obtained from the measurement points according to the cubic function to obtain the strain distribution of the entire bottom plate; integrate the strain to obtain the axial force T of the bottom plate, as shown in Equation (1):

[0021] T(y j ) = E·t·∫ε(x,y j )dx (1)

[0022] Where: E is the elastic modulus of the main girder bottom plate; t is the thickness of the bottom plate; x is the position coordinate of the bottom - plate strain point along the transverse bridge direction; y j is the driving position coordinate of the test vehicle along the longitudinal bridge direction corresponding to the j - th sampling of the strain data; ε(x,y j ) represents the bottom - plate strain varying with the longitudinal position of the test vehicle and the transverse position of the box - girder bottom plate. Therefore, establish the strain objective function F 1 as shown below:

[0023]

[0024] Where k is the order of the bridge - structure modal frequency involved in model modification; f i e and f i a are the measured value and the theoretically calculated value of the i - th order frequency of the structure respectively; Φ i e and Φ i a are the measured value and the theoretically calculated value of the i - th order mode - shape vector respectively; β and γ are weight coefficients, and the weight coefficients are taken as 1;

[0025] The frequency objective function F 2 and the mode - shape objective function F 3 are as follows:

[0026]

[0027]

[0028]

[0029] Where k is the order of the bridge - structure modal frequency involved in model modification; f i e and f i a are the measured value and the theoretically calculated value of the i - th order frequency of the structure respectively; Φ i e and Φ i aThey are the measured value and the theoretically calculated value of the i-th order vibration mode vector respectively; β and γ are weight coefficients, and the weight coefficients are taken as 1;

[0030] When combining each response objective function, a normalized method is adopted for combination, that is, the weight factor is set as the reciprocal of the initial value of each objective function. The modified objective function of the bridge finite element model after final combination is shown in Equation (6):

[0031]

[0032] where F i,0 is the initial value of the corresponding objective function F i of the bridge finite element model before modification.

[0033] (2.3) Finite element model modification for bearing capacity assessment of box girder bridges

[0034] Before modifying the bridge finite element model, it is necessary to determine the optimization parameters. The method for determining the parameters is the sensitivity analysis method. The material density, elastic modulus, deck pavement thickness, and additional stiffness of the bearing are selected as alternative optimization parameters, and the optimization parameters are finally determined according to the sensitivity analysis results; the formula for sensitivity analysis is as follows:

[0035]

[0036] where F(θ) is the objective function determined according to Equation (6); θ i is the i-th sample point of the alternative optimization parameters of the bridge, Δθ = 1%·θ, θ 1 and θ 2 are the upper and lower limits of the optimization parameters; the upper and lower limits of the optimization parameters are selected according to the possible variation range of the optimization parameters; the additional stiffness of the bearing is used as a mandatory optimization parameter, and its value range changes exponentially, resulting in a relatively small sensitivity compared with other parameters; therefore, the sensitivity comparison is carried out separately for different groups of additional stiffness of the bearing;

[0037] After the optimization parameters are selected, the Rosenbrock algorithm is used to optimize the objective function to reduce the error between the bridge finite element model and the actual structure; after performing the above optimization algorithm, a bridge structure finite element model that is in good agreement with the actual bridge structure is obtained, that is, it is used for subsequent bridge bearing capacity assessment;

[0038] Step 3. Bearing capacity assessment based on the benchmark model

[0039] After obtaining the modified bridge structure finite element model, the load effect is evaluated according to Equation (8):

[0040]

[0041] where CRF is the bridge condition assessment index; γ0 γ₀ is the structural importance coefficient; S is the load effect, which is obtained by applying the design load or the checked load on the modified model; R is the resistance effect of the control section, and the bearing capacity provided by the steel bars and concrete is calculated according to the design code and reduced according to the technical investigation results; when CRF < 1.05, it is determined that the bearing capacity of the bridge meets the requirements.

[0042] Advantages of the present invention:

[0043] 1. By using a moving load to quickly cross the bridge to obtain the quasi-influence coefficient of the strain or deflection of the main beam of the bridge, and supplementing it with the vibration data of the main beam obtained from the dynamic test, the disadvantages of long loading time, many measuring points and many loading vehicles in the traditional bridge load test are overcome;

[0044] 2. A multi-objective function for model modification is constructed by combining the spatial quasi-influence coefficient and the structural modal parameters. The key parameters to be optimized for the modification of the bridge bearing capacity model are determined through sensitivity analysis, and the bearing capacity evaluation model is obtained by optimizing based on the Rosenbrock method, making up for the problem of distortion of the optimization result of the single-objective function;

[0045] 3. A method for evaluating the bearing capacity based on the modified bridge model is proposed, and the load effect of the modified model is directly used for evaluation, considering the differences in the bearing capacity evaluation of different stressed members, and solving the problem of poor consistency of the bearing capacity checking coefficient in the code for the evaluation results of different members. Description of the drawings

[0046] Figure 1 Schematic diagram of the layout of strain and displacement sensors for the method adopted by the present invention;

[0047] Figure 2 Flowchart of the implementation of the method adopted by the present invention;

[0048] Figure 3 Two-span continuous box girder bridge in the embodiment of the method of the present invention: (a) Photo of the actual bridge; (b) General layout; (c) A-A section;

[0049] Figure 4 Schematic diagram of the moving load test path in the embodiment of the method of the present invention;

[0050] Figure 5 Schematic diagram of the installation position of the strain sensor in the embodiment of the method of the present invention;

[0051] Figure 6 Strain result diagram in the embodiment of the method of the present invention;

[0052] Figure 7 Schematic diagram of the installation position of the acceleration sensor in the embodiment of the method of the present invention;

[0053] Figure 8 Frequency and mode shape result diagram in the method embodiment of the present invention: (a) The 1st order: the frequency is 6.02 Hz; (b) The 2nd order: the frequency is 7.34 Hz; (c) The 3rd order: the frequency is 13.03 Hz; (d) The 4th order: the frequency is 14.40 Hz; (e) The 5th order: the frequency is 18.17 Hz; (f) The 6th order: the frequency is 18.78 Hz;

[0054] Figure 9 Static load test loading schematic diagram in the method embodiment of the present invention;

[0055] Figure 10 Sensitivity analysis result schematic diagram in the method embodiment of the present invention: (a) The first group of parameters; (b) The second group of parameters. Specific implementation manner

[0056] The following is further described in conjunction with the attached drawings and an embodiment.

[0057] As Figure 2 shown, a two-span reinforced concrete T-shaped rigid frame bridge with a span of 24 m + 24 m, the cross-section form adopts a concrete single-box single-cell variable cross-section box girder, the bridge deck width is 6 m, and the effective pedestrian passage width is 5.5 m. The design load is a crowd load of 5.0 kN / m 2 , and the superstructure and piers are both cast with C50 concrete. According to the Figure 3 steps shown, the moving load test and dynamic test are carried out on this bridge, and the model correction is completed based on the measured data. In addition, a static load test is carried out to verify the correctness of the model correction. Finally, the evaluation work is completed based on the corrected model.

[0058] (1) On-site test of box girder bridge

[0059] (1.1) Moving load test

[0060] In the moving load test, a trolley carrying a water tank slowly travels on the bridge, and the loading path is as Figure 4 shown. The total mass of the trolley and the pushing personnel is about 750 kg. Strain sensors are installed on the bottom plate and web of the mid-span section of the left span of the bridge, as Figure 5 shown. Due to data quality reasons, only the strain sensor data on the bottom plate is used for the next step of model correction. After the strain sensor data is filtered and drift-removed, it is as Figure 6 shown.

[0061] (1.2) Dynamic test

[0062] The extraction of dynamic characteristics is to extract the frequency and mode shape of the bridge by measuring the decay change of the acceleration response within the entire bridge under the excitation of external loads. A total of 54 bridge deck acceleration sensors are arranged, and the sensor layout schematic diagram is asFigure 7 As shown, the specific layout form is as follows: Each span of the bridge is longitudinally divided into 10 equal parts, and a total of 18 sensors are arranged in two spans, and 3 columns of sensors are arranged horizontally. The method for calculating the acceleration response frequency and vibration mode is the stochastic subspace method. The 1st to 6th order frequencies and vibration modes of the bridge structure obtained are as Figure 8 shown. Among them, the vibration modes of the 1st, 2nd, 4th, and 6th orders are mainly bending, and the 3rd and 5th orders are mainly torsional.

[0063] (1.3) Verification static load test

[0064] To verify the correctness of the subsequent optimization results, the bridge is loaded by means of water bag loading to obtain the displacement response at the mid - spans of the two spans of the bridge. The water bag loading positions are at the mid - span and the quarter - span positions of the east span of the bridge. The loading schematic is as Figure 9 shown. Displacement gauges are installed at the mid - span positions of the two spans to measure the mid - span deflection after the water bag loading.

[0065] (2) Evaluation model correction

[0066] The finite element model of the box - girder bridge is established using shell elements, and spring elements are added at the supports to simulate the situation where the supports are not ideal simply - supported. The alternative optimization parameters of this model include the mass, elastic moduli of the top plate, web plate, bottom plate, diaphragm, and pier, the deck pavement, the translational and rotational additional stiffnesses of the left and right supports and the middle pier. The sensitivity analysis is carried out using Equation (7). The mass, elastic moduli of the top plate, web plate, bottom plate, diaphragm, and pier, and the deck pavement are taken as the first group of parameters, numbered No.1 - 7 in sequence; the translational additional stiffnesses of the left and right supports and the middle pier, and the rotational additional stiffnesses of the left and right supports and the middle pier are the second group of parameters, numbered No.8 - 13 in sequence. The sensitivity analysis results are as Figure 10 shown. The finally determined optimization parameters are the mass, elastic moduli of the top plate, web plate, and bottom plate, and the translational and rotational additional stiffnesses of the left and right supports. This model uses the Rosenbrock algorithm for optimization to be closer to the actual situation. The optimization time is about 2 hours. The upper and lower limits of the optimization parameters and the optimization results are shown in Table 1. The displacement of the static load test is used to verify the model correction results, as shown in Table 2. The maximum error is about 10%, and the model is in good agreement with the measured data. This model can be used for the evaluation work of subsequent models.

[0067] Table 1 Model correction results

[0068]

[0069] Table 2 Static load test verification results

[0070]

[0071] (3) Bearing capacity evaluation

[0072] Apply the check load, i.e., the design load, to the corrected model under the most unfavorable conditions, and calculate the corresponding responses of the control sections. Taking the flexural bearing capacity of the normal section as an example, the control sections are located near the mid-span of each span. The most unfavorable load is applied to the entire bridge deck of the corresponding single span. The combined moment caused by its self-weight and the crowd load is 4094 kN·m, and the calculated flexural bearing capacity is 8740 kN·m. Then the bridge condition assessment index can be obtained.

[0073]

[0074] After calculation, the flexural bearing capacity of this box girder bridge fully meets the requirements, and there is a large bearing capacity reserve.

Claims

1. A rapid test and evaluation method for the bearing capacity of integral box girder bridges, characterized in that, the steps are as follows: Step 1. Rapid static and dynamic tests on box girder bridges (1.1) Obtain the quasi-influence coefficient through moving load tests (1.2) Obtain the structural dynamic characteristics through dynamic tests Step 2. Obtain the evaluation model of box girder bridges (2.1) Modeling method of box girder bridges The finite element model of the bridge is established using shell elements. The webs, decks, and bottom plates of the box girder cross-section are all established using shell elements with the same actual thickness as the components; spring elements are used to add additional stiffness at the bridge bearings to consider the case where the bridge bearing constraint conditions are not ideal simply supported. (2.2) Establish the objective function for modifying the bridge finite element model There are differences between the initial finite element model of the bridge and the actual bridge structure. It is necessary to establish an objective function for model optimization and obtain a finite element model that conforms to the actual structure through model modification; the objective function for optimizing the parameters of the initial finite element model of the bridge consists of three parts, namely the strain, frequency, and vibration mode objective functions; Establish a multi-measurement point strain objective function based on the principle of equal axial force on the bottom plate of the main girder; there is a cubic function relationship between the strain of the box girder and the lateral position. Fit the strain obtained at the measurement points according to the cubic function to obtain the strain distribution of the entire bottom plate; integrate the strain to obtain the axial force T of the bottom plate, as shown in Equation (1): T(y j ) = E·t·∫ε(x,y j )dx (1) Where: E is the elastic modulus of the main girder bottom plate; t is the thickness of the bottom plate; x is the position coordinate of the bottom plate strain point along the transverse bridge direction; y j is the driving position coordinate of the test vehicle along the longitudinal bridge direction corresponding to the j-th sampling of the strain data; ε(x, y j ) represents the bottom plate strain varying with the longitudinal position of the test vehicle and the transverse position of the box girder bottom plate; Therefore, the strain objective function F 1 is shown as follows: Where: m is the number of times the test vehicle crosses the bridge; n is the total number of strain sampling times during the period when the test vehicle crosses the bridge once; α i is the weight coefficient corresponding to the j-th time the test vehicle crosses the bridge, and the weight coefficient is taken as 1; T i e and T i a are the measured value and the theoretical calculated value of the axial force of the main girder bottom plate respectively; Frequency objective function F 2 and mode shape objective function F 3 are as follows: Among them, k is the order of the modal frequency of the bridge structure participating in model correction; f i e and f i a are respectively the measured value and the theoretically calculated value of the i-th order frequency of the structure; Φ i e and Φ i a are respectively the measured value and the theoretically calculated value of the i-th order mode shape vector; β and γ are weight coefficients, and the weight coefficients are taken as 1; When combining the response objective functions, normalization is used for combination, that is, the weight factor is set to the reciprocal of the initial value of each objective function. The final combined objective function for modifying the bridge finite element model is shown in Equation (6): Among them, F i,0 is the initial value of the objective function F corresponding to the finite element model of the bridge before correction i ; (2.3) Modify the finite element model for evaluating the bearing capacity of box girder bridges Before modifying the bridge finite element model, it is necessary to determine the optimization parameters. The method for determining the parameters is the sensitivity analysis method. Select the material density, elastic modulus, thickness of the bridge deck pavement, and additional stiffness of the bearings as alternative optimization parameters, and finally determine the optimization parameters according to the sensitivity analysis results; the formula for sensitivity analysis is as follows: where \(F(\theta)\) is the objective function determined according to formula (6); \(\theta\) i is the \(i\)-th sample point of the alternative optimization parameters of the bridge, \(\Delta\theta = 1\%\cdot\theta\), \(\theta\) 1 and \(\theta\) 2 are the upper and lower limits of the optimization parameters; the upper and lower limits of the optimization parameters are selected according to the possible variation range of the optimization parameters; the additional stiffness of the bearing is used as a required optimization parameter, and its value range changes exponentially, resulting in a very small sensitivity compared with other parameters; therefore, the sensitivity comparison is carried out separately for different groups of additional stiffness of the bearings. After the selection of the optimization parameters is completed, use the Rosenbrock algorithm to optimize the objective function and reduce the error between the bridge finite element model and the actual structure; after performing the above optimization algorithm, obtain a bridge structure finite element model that conforms well to the actual bridge structure, which is used for subsequent bridge bearing capacity evaluation; Step 3. Evaluate the bearing capacity of box girder bridges.

2. According to the rapid test and evaluation method for the bearing capacity of integral box girder bridges described in claim 1, characterized in that, step (1.1) is specifically as follows: The quasi-influence coefficient is obtained by collecting the structural vehicle-induced response data generated by a two-axle test vehicle passing through the bridge; the mass of the test vehicle should generate stable and high signal-to-noise ratio response data for the bridge. The vehicle loading principle is to cover most of the driving areas of the bridge with fewer vehicle driving times; the loading process satisfies the following criteria: 1) The vehicle drives slowly across the bridge at a speed not exceeding 5 km / h to minimize the dynamic effect of the vehicle on the structure. 2) The vehicle drives straight across the bridge in a single lane and cannot switch lanes midway; 3) According to the number of designed lanes of the bridge, the vehicle must drive at least once completely in each lane. The vehicle-induced response of the structure to be measured is the strain or deflection of the main girder; to improve the signal-to-noise ratio of the measured data of the vehicle-induced response of the structure, the measurement positions are selected at the mid-span and quarter-span sections of the main girder to ensure obtaining a larger vehicle-induced response; when measuring the deflection of the main girder, the distribution of the deflection is basically the same across the entire section, so at least 2 measuring points should be symmetrically arranged on the bottom surface of the main girder; when measuring the strain of the main girder, considering the large difference in the measured strain values on the same section of the box girder, the strain measuring points should be evenly arranged at the bottom plate of the box girder, and the number of strain sensors should be no less than 2n - 1, where n is the number of web members in the cross-section of the vector, to obtain a relatively complete strain distribution of the bottom plate of the main girder.

3. A rapid test and evaluation method for the load-carrying capacity of an integral box girder bridge according to claim 1, characterized in that step (1.2) is specifically as follows: identify the modal parameters of the bridge by collecting the acceleration response of the main girder under the forced vibration of the bridge structure; for the excitation method of the bridge, use wind load, apply a random environmental unknown excitation or a known excitation applied artificially, and identify the modal parameters of the excitation; The dynamic response mainly measures the acceleration response, which is obtained through accelerometers installed on the structure; the measuring points are arranged in a mesh form to obtain the acceleration response of the entire bridge and the complete deck vibration mode; to obtain a relatively smooth vibration mode of the deck, the measuring points should meet a certain density arrangement; the longitudinal bridge sensors should be arranged so that the vibration mode curve is relatively smooth, and the transverse bridge sensors should be arranged in at least two rows or more to identify the torsional vibration mode of the bridge.

4. A rapid test and evaluation method for the load-carrying capacity of an integral box girder bridge according to claim 1, characterized in that step 3 is specifically as follows: after obtaining the corrected finite element model of the bridge structure, evaluate the load effect according to formula (8): Among them, CRF is the bridge condition assessment index; γ 0 is the structural importance coefficient; S is the load effect, which is obtained by loading the modified model according to the design load or the checked load; R is the resistance effect of the control section, which calculates the bearing capacity provided by steel bars and concrete according to the design code and is reduced according to the technical investigation results; when CRF < 1.05, it is determined that the bearing capacity of the bridge meets the requirements.

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