Bridge health monitoring structure verification coefficient efficient calculation method

Abstract

The invention relates to the technical field of bridge health monitoring, in particular to a bridge health monitoring structure verification coefficient efficient calculation method. The method comprises the following steps: acquiring dynamic deflection measurement item data of all dynamic deflection monitoring points in a preset time period; preprocessing the dynamic deflection measurement item data to obtain deflection original data of each dynamic deflection monitoring point; processing the original deflection data to obtain high-frequency deflection data; obtaining a vehicle load effect data curve by using the high-frequency deflection data; picking up a peak value in the vehicle load effect data curve to obtain an actually measured deflection value of each vehicle; a vehicle load sequence formula is constructed, and first deflection theoretical values corresponding to different vehicle loads are obtained based on the vehicle load sequence formula; fitting the first deflection theoretical value to obtain a vehicle load and deflection fitting curve; and according to the vehicle load and deflection fitting curve and the actually measured deflection value of each vehicle, obtaining a structure inspection coefficient corresponding to each vehicle. The calculation efficiency of the structure inspection coefficient can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of bridge health monitoring, and in particular to an efficient calculation method for a bridge health monitoring structure calibration coefficient. Background Art

[0002] The signals obtained from long-term monitoring of bridge structure deflection include the effects of vehicle loads, wind loads, concrete shrinkage and creep, prestress loss, temperature changes, structural damage, and environmental noise.

[0003] Among the deflection components of bridge structures, the frequency of load effect is relatively high; the daily temperature difference effect refers to the change in structural deflection caused by the temperature change in one day, and its frequency is much smaller than the load deflection frequency; the long-term deflection and annual temperature difference deflection signal frequencies also belong to the low-frequency part, and are smaller than the daily temperature difference frequency. The impact scale of the annual temperature difference in the temperature effect is similar to the time scale of the long-term deflection of the structure, and there is an overlapping part.

[0004] The most direct and effective method and means for evaluating the quality of newly built bridges and the bearing capacity of existing bridges is the bridge load test. Its main purpose is to apply static loads to the bridge when the bridge bearing capacity cannot be clearly assessed through calculation and analysis, and to measure the structural response of the bridge structure under the test load. Based on this, the verification coefficient is determined to re-calculate the bearing capacity or directly determine whether the bridge bearing capacity meets the requirements. For the analysis of load test results, the verification coefficient is one of the most important evaluation indicators. Traditional load tests are costly, long, and the test data is small and scattered, resulting in low efficiency in obtaining the verification coefficient. Summary of the invention

[0005] In order to solve the above technical problems, the purpose of the present invention is to provide an efficient calculation method for the verification coefficient of the bridge health monitoring structure. The technical solution adopted is as follows:

[0006] An embodiment of the present invention provides a method for efficiently calculating a bridge health monitoring structure verification coefficient, the method comprising:

[0007] Obtaining the dynamic deflection measurement data of all dynamic deflection monitoring points within a preset period of time; preprocessing the dynamic deflection measurement data to obtain the original deflection data of each dynamic deflection monitoring point;

[0008] Processing the original deflection data to obtain high-frequency deflection data; using the high-frequency deflection data to obtain the vehicle load effect data curve; picking up the peak value in the vehicle load effect data curve to obtain the measured deflection value of each vehicle;

[0009] Constructing a vehicle load series formula, and obtaining the first deflection theoretical value corresponding to different vehicle loads based on the vehicle load series formula; fitting the first deflection theoretical value to obtain a vehicle load and deflection fitting curve;

[0010] The structural inspection coefficient corresponding to each vehicle is obtained according to the vehicle load and deflection fitting curve and the measured deflection value of each vehicle.

[0011] Preferably, obtaining the dynamic deflection measurement data of all dynamic deflection monitoring points within a preset period of time includes:

[0012] A dynamic deflection monitoring point is set in the middle of the main span of the bridge, and the dynamic deflection measurement data corresponding to all dynamic deflection monitoring points are obtained within a preset time period.

[0013] Preferably, the dynamic deflection measurement data is preprocessed to obtain the original deflection data of each dynamic deflection monitoring point, including:

[0014] The vertical data of the dynamic deflection measurement items of all dynamic deflection monitoring points are extracted, and the data are classified and time stamped according to the numbers of the dynamic deflection monitoring points to obtain the original deflection data of each dynamic deflection monitoring point.

[0015] Preferably, the raw deflection data is processed to obtain high-frequency deflection data, including:

[0016] The original deflection data is decomposed by wavelet transform to obtain high-frequency data and low-frequency data. The low-frequency data is discarded and the high-frequency data is retained. The high-frequency data is recorded as high-frequency deflection data.

[0017] Preferably, the vehicle load effect data curve is obtained using high frequency deflection data, including:

[0018] The high-frequency deflection data is reconstructed by wavelet and the vehicle load effect data curve is obtained.

[0019] Preferably, the peak value in the vehicle load effect data curve is picked to obtain the measured deflection value of each vehicle, including:

[0020] Obtain the peak value threshold and the peak spacing threshold, and obtain the peak value in the vehicle load effect data curve by using the peak value threshold and the peak spacing threshold based on the findpeaks function.

[0021] Preferably, a vehicle load series formula is constructed, and the first deflection theoretical values ​​corresponding to different vehicle loads are obtained based on the vehicle load series formula, including:

[0022] The vehicle load series formula is M = (49 + 5 × n),

[0023] Wherein, M represents the custom load of the vehicle; n represents a natural number;

[0024] According to the vehicle load series formula, the finite element analysis software Midas Civil is used to calculate the theoretical deflection value corresponding to the measuring point under the custom vehicle load condition, which is recorded as the first deflection theoretical value.

[0025] Preferably, fitting the first deflection theoretical value to obtain a vehicle load and deflection fitting curve includes:

[0026] The least square method is used to fit the first deflection theoretical value to obtain a fitting function of the relationship between the vehicle load and the deflection; and a fitting curve diagram of the vehicle load and the deflection is obtained according to the fitting function of the relationship between the vehicle load and the deflection.

[0027] Preferably, obtaining the structural inspection coefficient corresponding to each vehicle includes:

[0028] The load of the vehicle is obtained, and the corresponding theoretical value of deflection is obtained from the vehicle load and deflection fitting curve; the structural inspection coefficient is the ratio of the measured deflection value to the theoretical deflection value.

[0029] The embodiment of the present invention has at least the following beneficial effects: an efficient calculation method for the structural verification coefficient of bridge health monitoring provided in the embodiment of the present application first obtains the dynamic deflection measurement data of all dynamic deflection monitoring points within a preset time period; pre-processes the dynamic deflection measurement data to obtain the original deflection data of each dynamic deflection monitoring point; then uses wavelet transform to decompose the data, removes low-frequency data such as temperature effect and long-term effect, and reconstructs the high-frequency data components by wavelet to obtain the vehicle load effect data curve; then obtains the measured deflection value of each vehicle by picking up the peak value in the vehicle load effect data curve; furthermore, finds the corresponding relationship between the vehicle passing information and the data peak point in the weighing system through comprehensive judgment of time and vehicle speed information; then constructs a vehicle load series formula, and obtains the first deflection theoretical value corresponding to different vehicle loads based on the vehicle load series formula; fits the first deflection theoretical value to obtain the vehicle load and deflection fitting curve. Finally, the structural inspection coefficient corresponding to each vehicle is obtained according to the vehicle load and deflection fitting curve and the measured deflection value of each vehicle. This solution not only saves costs and performs real-time calculations, but also provides a large amount of data support for bridge bearing capacity assessment. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are 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.

[0031] Figure 1A method flow chart of an efficient calculation method for a bridge health monitoring structure calibration coefficient provided by an embodiment of the present invention;

[0032] Figure 2 A deflection time history curve diagram of an efficient calculation method for a bridge health monitoring structure verification coefficient provided by an embodiment of the present invention;

[0033] Figure 3 A time history graph of temperature effect and long-term effect of an efficient calculation method for a bridge health monitoring structure calibration coefficient provided by an embodiment of the present invention;

[0034] Figure 4 A vehicle load effect time history curve diagram of an efficient calculation method for a bridge health monitoring structure verification coefficient provided by an embodiment of the present invention;

[0035] Figure 5 A vehicle load effect time history curve diagram with peak value identification for an efficient calculation method for a bridge health monitoring structure calibration coefficient provided by an embodiment of the present invention;

[0036] Figure 6 A vehicle load and deflection fitting curve diagram of an efficient calculation method for bridge health monitoring structure verification coefficient provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0037] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the specific implementation method, structure, features and effects of a bridge health monitoring structure calibration coefficient efficient calculation method proposed by the present invention in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment. In addition, specific features, structures, or characteristics in one or more embodiments may be combined in any suitable form.

[0038] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0039] The specific scheme of the efficient calculation method of the bridge health monitoring structure calibration coefficient provided by the present invention is described in detail below with reference to the accompanying drawings.

[0040] Example:

[0041] The main application scenarios of the present invention are: in the field of bridge engineering, with the continuous increase in traffic volume and the extension of the service life of bridges, the monitoring and evaluation of the health status of bridge structures is particularly important. Traditional bridge health monitoring methods often rely on manual inspections and regular inspections. This method is not only inefficient, but also difficult to capture the dynamic changes of bridges in real time during operation. In order to overcome these shortcomings, in recent years, bridge health monitoring systems based on sensor technology and data analysis have been rapidly developed. However, in bridge health monitoring systems, how to accurately and efficiently calculate the structural calibration coefficient to evaluate the deviation between the actual response of the bridge under vehicle load and the theoretical prediction is still a technical problem. As an important indicator for measuring the safety of bridge structures, the accuracy and efficiency of the calculation results of the structural calibration coefficient directly affect the overall performance of the bridge health monitoring system. Most of the existing structural calibration coefficient calculation methods are based on complex numerical models and a large amount of computing resources, and experiments are required. The calculation process is cumbersome and time-consuming. In addition, these methods often find it difficult to effectively eliminate the influence of non-vehicle load factors such as temperature effects and long-term creep on bridge deflection data, resulting in large errors in the calculation results.

[0042] See also Figure 1 , which shows a method flow chart of an efficient calculation method for a bridge health monitoring structure calibration coefficient provided by an embodiment of the present invention, the method comprising the following steps:

[0043] Step S1, obtaining the dynamic deflection measurement data of all dynamic deflection monitoring points within a preset time period; preprocessing the dynamic deflection measurement data to obtain the original deflection data of each dynamic deflection monitoring point.

[0044] Step S2, processing the original deflection data to obtain high-frequency deflection data; using the high-frequency deflection data to obtain a vehicle load effect data curve; picking up the peak value in the vehicle load effect data curve to obtain the measured deflection value of each vehicle.

[0045] Step S3, constructing a vehicle load series formula, and obtaining the first deflection theoretical values ​​corresponding to different vehicle loads based on the vehicle load series formula; fitting the first deflection theoretical values ​​to obtain a vehicle load and deflection fitting curve.

[0046] Step S4, obtaining the structural inspection coefficient corresponding to each vehicle according to the vehicle load and deflection fitting curve and the measured deflection value of each vehicle.

[0047] In the embodiment of the present invention, the main line bridge of Zhoukou Yanghu Interchange on Shangnan Expressway is taken as an example for explanation. The main line bridge of Zhoukou Yanghu Interchange on Shangnan Expressway is located at K163+680 kilometers of Shangnan Expressway (S81). The left and right spans are arranged separately. The total length of a single span bridge is 351.15m, which is divided into four sections, with a span combination of 5-20m+4-20m+(25+45+25)m+4-20m. The main bridge is a partially prestressed concrete (Class A) continuous box girder bridge with a length of 95m, a span combination of (25+45+25)m, and a bridge width of 17.5m. The main beam is a single-box double-chamber section with a box top plate width of 17.5m and a bottom plate width of 9.0m. No. 50 concrete is used. The beam height of the cast-in-place section of the box girder mid-span and side span is 1.2m, and the beam height of the top of the box girder pier is 2.2m. From the mid-span to the root of the box girder, the box girder height changes in a quadratic parabola. The thickness of the side web of the box girder is 40cm and 70cm, and the thickness of the middle web is 30cm and 90cm. The top plate of the box girder is 25cm thick except for the 50cm thick root of the box girder. The bottom plate of the box girder is 65cm thick except for the 65cm thick root of the box girder. The thickness of the bottom plate of the box girder changes from 40cm thick at the root of the box girder to 25cm thick in the mid-span section along a 2.0 parabola. The 10# and 11# main piers are double-column piers, and the 9# and 12# transition piers are three-column piers, with bored cast-in-place piles. The basic earthquake intensity is VI. The design load of the bridge: automobile-super 20, trailer-120.

[0048] Step S1, obtaining the dynamic deflection measurement data of all dynamic deflection monitoring points within a preset time period; preprocessing the dynamic deflection measurement data to obtain the original deflection data of each dynamic deflection monitoring point.

[0049] A bridge health structure monitoring system has been installed on this section of the high-speed bridge to monitor the ambient temperature and humidity at the bridge site, vehicle load, main beam deflection, main beam dynamic deflection, key section strain, concrete component temperature, main beam vertical vibration acceleration and concrete structure cracks.

[0050] A target is set in the middle of the main span of the bridge, that is, a dynamic monitoring point is set. Multiple dynamic monitoring points will be set on the same section. The number of dynamic monitoring points needs to be determined by the implementer according to the actual situation. The number and position of dynamic monitoring points arranged on different bridges may be different. In addition, the displacement needs to be detected by video imaging method. The video imaging displacement monitoring equipment is located at the top of the middle span pier. The video imaging displacement monitoring equipment identifies the target image on the structure. When the measured structure undergoes a planar displacement, the target coordinates change accordingly, thereby measuring the horizontal and vertical bidirectional displacement of the measured object. The video imaging method is used to monitor the displacement equipment and targets for monitoring, with a sampling frequency of 20Hz, which can capture the deflection changes in the middle of the main span when the vehicle passes through the bridge deck in real time.

[0051] Further, a preset time period is set. In the embodiment of the present invention, the preset time period is to obtain the dynamic deflection measurement data between 00:00 on August 21, 2024 and 00:00 on August 22, 2024, that is, the length of the preset time period in the embodiment of the present invention is 24 hours, and all dynamic deflection measurement data can be obtained, wherein the dynamic deflection measurement data is high-frequency sampling data. The data of all dynamic deflection monitoring points collected are stored in the database as a whole, and the dynamic deflection measurement data of all dynamic deflection monitoring points need to be exported from the database, wherein the dynamic deflection measurement data includes the data of the dynamic deflection monitoring points in the vertical direction and the horizontal direction.

[0052] The dynamic deflection measurement data is preprocessed to obtain the original deflection data of each dynamic deflection monitoring point. Specifically, the vertical data of the dynamic deflection measurement data of all dynamic deflection monitoring points are extracted, and classified and timestamp converted according to the number of the dynamic deflection monitoring point to obtain the original deflection data of each dynamic deflection monitoring point. The curve corresponding to the original deflection data is shown in the figure below. Figure 2 The deflection time history curve is shown.

[0053] In this way, the original deflection data of each dynamic deflection monitoring point can be obtained for subsequent analysis.

[0054] Step S2, processing the original deflection data to obtain high-frequency deflection data; using the high-frequency deflection data to obtain a vehicle load effect data curve; picking up the peak value in the vehicle load effect data curve to obtain the measured deflection value of each vehicle.

[0055] The original deflection data includes high-frequency data and low-frequency data. The low-frequency data is the long-term effect and temperature effect. In the subsequent analysis, if the long-term effect and temperature effect are not eliminated, it will affect the subsequent analysis and cause errors in the subsequent analysis. The high-frequency data is the vehicle load effect.

[0056] Furthermore, the original deflection data is decomposed by wavelet transform to obtain high-frequency data and low-frequency data. The low-frequency data is removed and the high-frequency data is retained. The high-frequency data is recorded as high-frequency deflection data. In this way, the long-term effect and temperature effect in the original deflection data are removed and the vehicle load effect is retained to ensure the accuracy of subsequent analysis. The time history curves of temperature effect and long-term effect are shown in the figure below. Figure 3 shown.

[0057] Then, the high-frequency deflection data needs to be reconstructed. Specifically, the high-frequency deflection data is reconstructed by wavelet to obtain the vehicle load effect data curve, such as Figure 4 It should be noted that, in the embodiments of the present invention, the operations of wavelet transform and wavelet reconstruction are all performed in MATLAB, and the implementer can select a suitable method to perform the operations of wavelet transform and wavelet reconstruction according to the actual situation.

[0058] Next, before analyzing the vehicle load effect data curve, it is necessary to obtain the vehicle passing information of the bridge for subsequent analysis. The weighing sensor installed on the bridge can collect detailed vehicle information such as vehicle load, axle weight, speed, passing time, lane position, captured pictures and license plate number, thereby obtaining the passing vehicle information.

[0059] Then for the vehicle load effect data curve, it is necessary to extract the peak value therein. Specifically, in the MATLAB software platform, the findpeaks function is used to find the peak value in the vehicle load effect data curve. It is necessary to obtain the peak value in the vehicle load effect data curve according to the parameters such as the size of the peak value and the distance between the two peak values. Obtain the peak value threshold and the peak spacing threshold. Preferably, in the present invention, the peak value threshold is set based on the deflection value when the 49t vehicle passes through the bridge deck, thereby controlling the detection sensitivity of the peak value. It should be noted that the peak value threshold needs to be adjusted by the implementer according to the actual situation, and the value of the peak value threshold corresponding to different situations is different. At the same time, it is also necessary to obtain the peak spacing threshold. The minimum distance between the peak values ​​represents the shortest time interval between two vehicles passing through the main span in turn, which is determined by the distance and speed of the two vehicles in front and behind. The shortest time interval between the two vehicles in front and behind can be obtained by statistical analysis of a large number of vehicles monitored by vehicle information. The shortest time interval is the peak spacing threshold.

[0060] Based on the findpeaks function, the peak value threshold and the peak spacing threshold are used to obtain the peak value in the vehicle load effect data curve; if the distance between two peak values ​​is not less than the peak spacing threshold, only one peak value will be retained.

[0061] In the embodiment of the present invention, in order to conveniently represent the data peak point picking details, Figure 4 Take a part of the data (from 12:00 to 12:10 on August 21, 2024), take the opposite of the vertical coordinate of the curve (i.e., flip the curve symmetrically up and down), and use the findpeaks function in the MATLAB software platform to find the peak value in the vehicle load effect data curve. By adjusting the peak value threshold, the peak detection sensitivity can be controlled. After picking the peak value of the curve, the peak value is output in the order of appearance, and multiple peak values ​​(vehicle load effects) and their positions (time) are obtained. Vehicle load effect time history curve with peak recognition, see Figure 5 .

[0062] Vehicles will pass through the dynamic weighing system at the bridgehead roadbed and the bridge deck in the middle of the main span in turn. The deflection peak value corresponding to the vehicle is inferred using monitoring data such as vehicle speed, distance, and time interval, which is the load effect (measured deflection value) when the vehicle passes through the bridge deck. That is, the corresponding relationship between vehicle passing information and peak value is obtained based on the vehicle passing information, that is, which vehicle caused the peak value. In this way, the measured deflection value corresponding to each vehicle passing through the bridge within the preset time period can be obtained.

[0063] Step S3, constructing a vehicle load series formula, and obtaining the first deflection theoretical values ​​corresponding to different vehicle loads based on the vehicle load series formula; fitting the first deflection theoretical values ​​to obtain a vehicle load and deflection fitting curve.

[0064] Furthermore, it is necessary to obtain the theoretical value of deflection. When obtaining the theoretical value of deflection, it is necessary to customize the working condition of the vehicle. Set the custom load of the vehicle to M, and construct the vehicle load series formula, specifically: M = (49 + 5 × n) tons, where n is a natural number, and then obtain vehicles with different loads under different settings. When the vehicle load is M and the vehicle passes through the bridge deck, the finite element analysis software Midas Civil is used to calculate the corresponding theoretical deflection value at the measuring point under the custom vehicle load condition according to the vehicle load series formula, which is recorded as the first theoretical deflection value.

[0065] Furthermore, after obtaining the first deflection theoretical value corresponding to vehicles with different loads, the first deflection theoretical value is fitted by a data fitting method. The fitting method can be selected by the implementer according to the actual situation. In the embodiment of the present invention, the least square method is used for fitting, and then the relationship fitting function between the vehicle load and the deflection is obtained, which is specifically y=0.09M+0.0327, where y represents the theoretical deflection value; M represents the custom load. In this way, the fitting relationship between the vehicle load and the theoretical deflection value can be obtained.

[0066] Finally, the vehicle load and deflection fitting curve can be obtained according to the relationship fitting function, such as Figure 6 As shown in the figure, the corresponding relationship between vehicle load and theoretical deflection value is shown. From this, the deflection value when the vehicle passes through the bridge can be quickly obtained, and then subsequent analysis can be carried out.

[0067] Step S4, obtaining the structural inspection coefficient corresponding to each vehicle according to the vehicle load and deflection fitting curve and the measured deflection value of each vehicle.

[0068] After obtaining the vehicle load and deflection fitting curve, the theoretical value of the vehicle's corresponding deflection can be obtained in time when the vehicle passes through the bridge, and then the structural verification coefficient can be obtained.

[0069] Specifically, the load of the vehicle is obtained, and the corresponding theoretical value of deflection is obtained from the vehicle load and deflection fitting curve, wherein the structural inspection coefficient is the ratio of the measured deflection value to the theoretical deflection value.

[0070] By calculating the structural verification coefficient of the bridge deflection in real time during the data collection process, the present invention can evaluate and monitor the bridge structure performance in real time, conduct probability statistics on the structural verification coefficient to view its distribution law, and predict the remaining life rate of the reinforced concrete beam through the degradation of the deflection verification coefficient.

[0071] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The above is a description of a specific embodiment of this specification. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0072] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0073] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims

1. An efficient calculation method for bridge health monitoring structure verification coefficient, It is characterized in that The method includes: Obtaining the dynamic deflection measurement data of all dynamic deflection monitoring points within a preset period of time; preprocessing the dynamic deflection measurement data to obtain the original deflection data of each dynamic deflection monitoring point; Processing the original deflection data to obtain high-frequency deflection data; using the high-frequency deflection data to obtain the vehicle load effect data curve; picking up the peak value in the vehicle load effect data curve to obtain the measured deflection value of each vehicle; Constructing a vehicle load series formula, and obtaining the first deflection theoretical value corresponding to different vehicle loads based on the vehicle load series formula; fitting the first deflection theoretical value to obtain a vehicle load and deflection fitting curve; The structural inspection coefficient corresponding to each vehicle is obtained according to the vehicle load and deflection fitting curve and the measured deflection value of each vehicle.

2. According to claim 1, a bridge health monitoring structure verification coefficient efficient calculation method, It is characterized in that The step of obtaining the dynamic deflection measurement data of all dynamic deflection monitoring points within a preset period of time includes: A dynamic deflection monitoring point is set in the middle of the main span of the bridge, and the dynamic deflection measurement data corresponding to all dynamic deflection monitoring points are obtained within a preset time period.

3. According to claim 1, a bridge health monitoring structure calibration coefficient efficient calculation method, It is characterized in that The method of preprocessing the dynamic deflection measurement data to obtain the original deflection data of each dynamic deflection monitoring point includes: The vertical data of the dynamic deflection measurement items of all dynamic deflection monitoring points are extracted, and the data are classified and time stamped according to the numbers of the dynamic deflection monitoring points to obtain the original deflection data of each dynamic deflection monitoring point.

4. According to claim 1, a bridge health monitoring structure calibration coefficient efficient calculation method, It is characterized in that The step of processing the original deflection data to obtain high-frequency deflection data includes: The original deflection data is decomposed by wavelet transform to obtain high-frequency data and low-frequency data. The low-frequency data is discarded and the high-frequency data is retained. The high-frequency data is recorded as high-frequency deflection data.

5. According to claim 1, a bridge health monitoring structure calibration coefficient efficient calculation method, It is characterized in that The method of obtaining a vehicle load effect data curve using high frequency deflection data includes: The high-frequency deflection data is reconstructed by wavelet and the vehicle load effect data curve is obtained.

6. According to claim 1, a bridge health monitoring structure verification coefficient efficient calculation method, It is characterized in that The step of picking the peak value in the vehicle load effect data curve to obtain the measured deflection value of each vehicle includes: Obtain the peak value threshold and the peak spacing threshold, and obtain the peak value in the vehicle load effect data curve by using the peak value threshold and the peak spacing threshold based on the findpeaks function.

7. According to claim 1, a bridge health monitoring structure verification coefficient efficient calculation method, It is characterized in that The constructing of the vehicle load series formula, and obtaining the first deflection theoretical value corresponding to different vehicle loads based on the vehicle load series formula, includes: The vehicle load series formula is M = (49 + 5 × n), Wherein, M represents the custom load of the vehicle; n represents a natural number; According to the vehicle load series formula, the finite element analysis software Midas Civil is used to calculate the theoretical deflection value corresponding to the measuring point under the custom vehicle load condition, which is recorded as the first deflection theoretical value.

8. According to claim 1, a bridge health monitoring structure verification coefficient efficient calculation method, It is characterized in that The step of fitting the first deflection theoretical value to obtain a vehicle load and deflection fitting curve includes: The least square method is used to fit the first deflection theoretical value to obtain a fitting function of the relationship between the vehicle load and the deflection; and a fitting curve diagram of the vehicle load and the deflection is obtained according to the fitting function of the relationship between the vehicle load and the deflection.

9. According to claim 1, a bridge health monitoring structure verification coefficient efficient calculation method, It is characterized in that The obtaining of the structural inspection coefficient corresponding to each vehicle includes: The load of the vehicle is obtained, and the corresponding theoretical value of deflection is obtained from the vehicle load and deflection fitting curve; the structural inspection coefficient is the ratio of the measured deflection value to the theoretical deflection value.

Images