Bridge wind speed monitoring data correction method considering bridge deck interference

Abstract

The present application relates to a kind of bridge wind speed monitoring data correction method considering bridge deck interference, it is suitable for bridge engineering wind speed monitoring data cleaning field, especially when installing on the wind speed sensor of bridge deck, the wind speed measured is affected by the shielding effect of bridge deck structure, need to be adaptively corrected to disturbed data, the present method proposes that the average wind speed and turbulence intensity measured by real value and disturbance component two parts constitute, and disturbance component can be expressed as the product of real value and disturbance coefficient, this disturbance coefficient is completely calculated by relative average wind speed, and there is symmetry between upstream and downstream of bridge deck, further proposes the data correction method considering disturbance effect, and according to upstream and downstream measured data, the least square solution of undetermined coefficient in correction formula is given.Compared with prior art, the present application can effectively realize the data correction of wind field characteristic parameters at the site of large-span bridge.

Description

Technical Field

[0001] This invention relates to the field of wind speed monitoring data cleaning technology for bridge engineering, and in particular to a method for correcting bridge wind speed monitoring data considering bridge deck interference. Background Technology

[0002] Because long-span bridges have relatively low stiffness and damping, they are prone to significant deformation and vibration under wind loads. Therefore, the wind resistance performance of long-span bridge structures is usually a controlling factor in structural design. During operation, understanding the changes in wind load parameters borne by the structure also helps in making routine maintenance decisions. Therefore, long-term observation of the wind field environment at or near the bridge site, and conducting probabilistic model studies based on on-site observation data, has significant practical implications.

[0003] The bridge structure health monitoring system installs numerous sensors at key structural locations (e.g., mid-span and quarter-span points), among which wind speed sensors enable real-time monitoring and recording of the wind field at the bridge site. Ideally, mean wind parameters (mean wind speed, mean wind direction, and angle of attack, etc.) and fluctuating wind parameters (fluctuating wind turbulence intensity, turbulence integral scale, gust factor, etc.) can be directly extracted from the raw observation data. However, due to the shielding effect of the bridge deck structure—that is, the interference of the structure itself on the wind field—the data recorded by the sensors is usually the disturbance value after the interaction between the wind and the bridge deck, especially when the sensor installation location is on the opposite side of the incoming wind direction from the bridge axis, where the degree of interference is greatest. Therefore, to ensure the accuracy of the analysis of the structural wind field characteristics, it is necessary to correct the wind parameters. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of the prior art, where the data recorded by the sensors is usually the disturbance value after the interaction between the wind and the bridge deck due to the shielding effect of the bridge deck structure, and to provide a bridge wind speed monitoring data correction method that takes into account bridge deck interference.

[0005] The objective of this invention can be achieved through the following technical solutions:

[0006] A method for correcting bridge wind speed monitoring data considering bridge deck interference includes:

[0007] Based on the observation data collected by the sensors on the bridge that are to be corrected, average data is obtained, and the relative average wind direction is determined.

[0008] For the parameter to be corrected, obtain the disturbance coefficient of the parameter to be corrected on the bridge under the relative average wind direction;

[0009] The average data is corrected by using the disturbance coefficient of the parameter to be corrected, and the corrected monitoring data is obtained.

[0010] Furthermore, sensors for parameters to be corrected are installed upstream and downstream of the bridge. The disturbance coefficients of the parameters to be corrected corresponding to the upstream and downstream sensors both exhibit translational symmetry, that is:

[0011] f u,U =f u,D (δ(β+π))

[0012] In the formula, f u,U f is the upstream parameter disturbance coefficient to be corrected. u,D δ is the downstream parameter disturbance coefficient to be corrected, β is the relative average wind direction, and δ(·) is the operator to convert any angle to [0, 2π).

[0013] The disturbance coefficient of the parameter to be corrected has continuity within the circular plane, that is...

[0014]

[0015] In the formula, f u (β) is the disturbance coefficient of the parameter to be corrected under the relative average wind direction β;

[0016] The undetermined form of the disturbance coefficients of the parameter to be corrected is a high-order polynomial considering continuity, namely:

[0017] f u,D (β)=|[β(β-2π)(p1β 2 +p2β+p3)+p4]|β∈[0,2π)

[0018] In the formula, p1, p2, p3 and p4 are all polynomial coefficients.

[0019] Furthermore, the disturbance coefficient of the parameter to be corrected is solved using the least squares method.

[0020] Furthermore, the parameter to be corrected is the average wind speed, and the correction expression for the average wind speed is:

[0021]

[0022] In the formula, U is the corrected average wind speed. U U D These represent the average wind speeds extracted from upstream and downstream sensor observation data, respectively; β represents the relative average wind direction with the bridge axis as zero, and f u,U (β),f u,D (β) represents the wind speed disturbance coefficients of the upstream and downstream sensors, respectively, when the relative average wind direction is β.

[0023] Furthermore, the process of solving for the undetermined coefficients of the higher-order polynomial of the disturbance coefficient of the average wind speed includes:

[0024] Set target value:

[0025]

[0026] In the formula, y i For the i-th target value, U D (t i U represents the average wind speed extracted from the downstream sensor observation data at time i. U (t i () represents the average wind speed extracted from the upstream sensor observation data at time i.

[0027] Fitted values:

[0028]

[0029] In the formula, f is the i-th fitted value. u,D (β i ) represents the wind speed disturbance coefficient of the downstream sensor under the i-th relative average wind direction;

[0030] Least squares solution:

[0031]

[0032] In the formula, Let be the undetermined coefficient for the i-th optimal value;

[0033] The optimal undetermined parameters are obtained by solving the problem using the least squares method.

[0034] Furthermore, the application environment for the average wind speed correction process is as follows:

[0035] Due to the shielding effect of the bridge deck structure, the average wind speed extracted from the field measurement data is the disturbed value;

[0036] The average wind speed decreases after being disturbed compared to the actual wind speed, and for the same wind direction angle, the decrease is proportional to the actual wind speed.

[0037] Furthermore, the parameter to be corrected is the turbulence intensity, and the correction expression for the turbulence intensity is:

[0038]

[0039] In the formula, For the corrected turbulence intensity, I U ,I D The turbulence intensities, f, are extracted from upstream and downstream sensor observation data, respectively. i,U (β),f i,D(β) represents the turbulence intensity disturbance coefficients of the upstream and downstream sensors when the relative average wind direction is β.

[0040] Furthermore, the process of solving for the undetermined coefficients of the higher-order polynomial of the turbulence intensity perturbation coefficient includes:

[0041] Set target value:

[0042]

[0043] In the formula, y i For the i-th target value, I D (t i Let I be the turbulence intensity extracted from the downstream sensor observation data at time i. U (t u ) represents the turbulence intensity extracted from the upstream sensor observation data at time i;

[0044] Fitted values:

[0045]

[0046] In the formula, f is the i-th fitted value. i,D (β i ) represents the turbulence intensity disturbance coefficient of the downstream sensor under the i-th relative average wind direction;

[0047] Least squares solution:

[0048]

[0049] In the formula, Let be the undetermined coefficient for the i-th optimal value;

[0050] The optimal undetermined parameters are obtained by solving the problem using the least squares method.

[0051] Furthermore, the application environment for the turbulence intensity correction process is as follows:

[0052] Due to the shielding effect of the bridge deck structure, the turbulence intensity extracted from the field measurement data is the disturbed value;

[0053] The intensity of turbulence increases after being disturbed compared to the actual turbulence intensity, and for the same wind direction angle, the increase is proportional to the actual turbulence intensity.

[0054] Furthermore, the method is embedded in computer software for execution.

[0055] Compared with the prior art, the present invention has the following advantages:

[0056] (1) This invention proposes a data correction method that considers disturbance effects, and based on upstream and downstream measured data, provides the least squares solution of the undetermined coefficients in the correction formula. This method can effectively correct the wind field characteristic parameters at the bridge site of long-span bridges and eliminate the interference of the bridge deck structure's shielding effect on the average wind speed and turbulence intensity.

[0057] (2) The present invention can obtain near-real average wind speed and turbulence intensity, and more accurately describe the wind field characteristics at the bridge site.

[0058] (3) The disturbance coefficient form proposed in this invention has a certain degree of universality and can be used on bridges of the same type.

[0059] (4) The unknown equation proposed in this invention is simple in form, easy to solve and easy to implement.

[0060] (5) The present invention is convenient for software development and can be embedded as a data cleaning algorithm into other wind parameter analysis tools. Attached Figure Description

[0061] Figure 1 This is a flowchart illustrating a method for correcting bridge wind speed monitoring data considering bridge deck interference, provided in an embodiment of the present invention.

[0062] Figure 2 This is a schematic diagram of a process for correcting the average wind speed and turbulence intensity at the bridge site, provided in an embodiment of the present invention.

[0063] Figure 3 This is a schematic diagram of a bridge deck wind speed sensor arrangement provided in an embodiment of the present invention;

[0064] Figure 4 This is a schematic diagram of the measured average wind speed upstream and downstream of a bridge surface provided in an embodiment of the present invention.

[0065] Figure 5 This is a schematic diagram of measured values ​​of turbulence intensity upstream and downstream of a bridge surface provided in an embodiment of the present invention;

[0066] Figure 6 This is a schematic diagram illustrating a correction value for the average wind speed upstream and downstream of a bridge surface, provided in an embodiment of the present invention.

[0067] Figure 7 This is a schematic diagram illustrating the correction values ​​for the upstream and downstream turbulence intensity of a bridge surface provided in an embodiment of the present invention;

[0068] In the figure, 1. Wind speed sensor located upstream of the bridge deck; 2. Wind speed sensor located downstream of the bridge deck; 3. Bridge deck structure; 4. Clockwise angle β0 between the bridge axis and due north. Detailed Implementation

[0069] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations.

[0070] Therefore, the following detailed description of the embodiments of the invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the invention without inventive effort are within the scope of protection of the invention.

[0071] It should be noted that similar labels and letters in the following figures indicate similar items. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0072] Example 1

[0073] like Figure 1 As shown, this embodiment provides a method for correcting bridge wind speed monitoring data considering bridge deck interference, including:

[0074] S1: Based on the observation data collected by the sensors of the parameters to be corrected on the bridge, obtain the average data and determine the relative average wind direction;

[0075] S2: For the parameter to be corrected, obtain the disturbance coefficient of the parameter to be corrected on the bridge under the relative average wind direction;

[0076] S3: The average data is corrected by using the disturbance coefficient of the parameter to be corrected, and the corrected monitoring data is obtained.

[0077] The disturbance coefficient has the following properties:

[0078] Sensors for the parameters to be corrected are installed both upstream and downstream of the bridge. The disturbance coefficients of the parameters to be corrected corresponding to the upstream and downstream sensors both exhibit translational symmetry, that is:

[0079] f u,U =f u,D (δ(β+π))

[0080] In the formula, f u,U f is the upstream parameter disturbance coefficient to be corrected. u,D δ is the downstream parameter disturbance coefficient to be corrected, β is the relative average wind direction, and δ(·) is the operator to convert any angle to [0, 2π).

[0081] The disturbance coefficients of the parameter to be corrected have continuity within the circular plane, that is...

[0082]

[0083] In the formula, f u (β) is the disturbance coefficient of the parameter to be corrected under the relative average wind direction β;

[0084] The undetermined form of the perturbation coefficients of the parameter to be corrected is a high-order polynomial considering continuity, namely:

[0085] f u,D (β)=|[β(β-2π)(p1β 2 +p2β+p3)+p4]|β∈[0,2π)

[0086] In the formula, p1, p2, p3 and p4 are all polynomial coefficients.

[0087] The disturbance coefficients of the parameters to be corrected are solved using the least squares method.

[0088] The least squares solution process, taking average wind speed as an example, includes:

[0089] Set the equation to be fitted:

[0090] Target value:

[0091] Fitted values:

[0092] Least squares solution:

[0093] The optimal undetermined parameters can be obtained by using the least squares method.

[0094] The following uses average wind speed and turbulence intensity as examples to illustrate the specific process of the above method, which mainly includes the following steps:

[0095] a) Extract the average wind speed, average wind direction, and turbulence intensity within the basic time interval;

[0096] b) Convert the average wind direction to a relative value with the bridge axis as zero;

[0097] c) Calculate the average relative average wind direction of the upstream and downstream sensors;

[0098] d) Calculate the disturbance coefficients of average wind speed and turbulence intensity using the least squares solution;

[0099] e) The corrected average wind speed and turbulence intensity are obtained by using the perturbation correction formula.

[0100] The wind speed sensors installed on the bridge deck can monitor the wind speed and direction at the bridge site in real time, obtaining second-by-second data. In wind field characteristic analysis, average parameters and fluctuation parameters can be extracted from the second-by-second data with a basic time interval of 10 minutes. The average wind speed is denoted as U, the average wind direction as β, and the turbulence intensity as I.

[0101] This embodiment uses relative average wind speed for ease of calculation, that is, with the bridge axis as zero degrees and clockwise as the positive direction, the relative average wind speed in this embodiment is expressed as:

[0102]

[0103] In this embodiment, β0 = 10.6°, and the function δ(·) is in the form of:

[0104]

[0105] in This is the floor function.

[0106] For wind speed sensors installed upstream and downstream of the bridge deck, the average wind speed and turbulence intensity extracted from the field measurement data are disturbed values ​​due to the shielding effect of the bridge deck structure, i.e., the interference of the structure itself on the wind field. Figure 4 and Figure 5 The average wind speed and turbulence intensity measured by upstream and downstream sensors are presented respectively. Ideally, the upstream and downstream data should be the same, i.e., the scatter points should be distributed around the straight line y = x. Figure 4 and Figure 5 The scatter plots all exhibit a dual-family pattern and are strongly correlated with the relative average wind direction.

[0107] For example, when the relative average wind direction is between 0 and 90°, the incoming wind direction is downstream, meaning that the data measured by downstream sensors is less disturbed, while the data measured by upstream sensors is more affected by the bridge deck structure. Figure 4 In the diagram, the lighter-colored scatter points are distributed below y=x, indicating that the measured average wind speed downstream is greater than that upstream. Figure 5 In the diagram, the lighter-colored scatter points are distributed above y=x, indicating that the measured downstream turbulence intensity is less than that upstream.

[0108] Therefore, this embodiment proposes that the average wind speed decreases compared to the actual wind speed after disturbance, and the turbulence intensity increases compared to the actual turbulence intensity after disturbance. This is expressed in the following forms respectively.

[0109] U m =U t -U d (3)

[0110] I m =I t +Id (4)

[0111] Where the subscript m represents the measured value, t represents the true value, and d represents the increase or decrease due to disturbance.

[0112] Because there are some differences in the wind direction angles measured by downstream sensors, this embodiment uses the average of the relative average wind directions of upstream and downstream sensors as the nominal relative average wind direction. The calculation formula proposed in this embodiment is as follows:

[0113]

[0114] The subscripts U and D represent the upstream and downstream sides of the bridge deck, respectively.

[0115] This embodiment proposes that the average wind speed decreases after being disturbed, and at the same wind direction angle, the decrease is proportional to the actual wind speed, expressed as:

[0116] U d =U t ·f u (β) (6)

[0117] This embodiment proposes that the turbulence intensity increases after being disturbed, and at the same wind direction angle, the increase is proportional to the true turbulence intensity, expressed as:

[0118] I d =I t ·f i (α) (7)

[0119] This embodiment defines f u ,f i These are the disturbance coefficients for average wind speed and turbulence intensity, respectively, and these coefficients are symmetrical between the upstream and downstream sensors:

[0120] f u,U (α)=f u,d (δ(α+π)) (8)

[0121] f i,U (α)=f i,D (δ(α+π)) (9)

[0122] Combining equations (6)-(9), we can obtain equations that eliminate the true average wind speed and turbulence intensity.

[0123]

[0124]

[0125] Considering the continuity of the disturbance coefficient across all angle ranges and the periodicity of wind direction, taking average wind speed as an example, the disturbance coefficient should satisfy:

[0126] lim β→2π -f u (β)=f u (0) β∈[0,2π) (12)

[0127] Therefore, the undetermined form of the perturbation coefficients is constructed using a higher-order polynomial as follows:

[0128] f u,D (β)=|[β(β-2π)(p1β 2 +p2β+p3)+p4]| β∈[0,2π) (13)

[0129] The disturbance coefficient f of the sensor on the other side of the bridge deck u,U (β) can be obtained based on the symmetry shown in equations (8) and (9).

[0130] Based on the undetermined form of the disturbance coefficient shown in equation (13), and combined with the solution process of the least squares solution, the correction values ​​of the upstream and downstream data can be obtained respectively, as shown in the figure. Figure 6 and Figure 7 As shown. Compared to before the correction ( Figure 4 and Figure 5 The scatter distributions of average wind speed and turbulence intensity both converge towards the straight line y = x, and the distribution patterns do not show a significant correlation with the relative average wind direction, indicating the correctness of the correction method.

[0131] Furthermore, the average of the upstream and downstream data correction values ​​is taken as the final correction value:

[0132]

[0133] Similarly, the correction value for turbulence intensity can also be obtained:

[0134]

[0135] The function construction form and coefficient calculation process in this embodiment are merely examples and can be easily modified.

[0136] This solution is convenient for software development and can be embedded as a data cleaning algorithm into other wind parameter analysis tools.

[0137] The preferred embodiments of the present invention have been described in detail above. It should be understood that those skilled in the art can make numerous modifications and variations based on the concept of the present invention without creative effort. Therefore, all technical solutions that can be obtained by those skilled in the art based on the concept of the present invention through logical analysis, reasoning, or limited experimentation on the basis of existing technology should be within the scope of protection defined by the claims.

Claims

1. A method for correcting bridge wind speed monitoring data considering bridge deck interference, characterized in that, include: Based on the observation data collected by the sensors on the bridge that are to be corrected, average data is obtained, and the relative average wind direction is determined. For the parameter to be corrected, obtain the disturbance coefficient of the parameter to be corrected on the bridge under the relative average wind direction; The average data is corrected using the disturbance coefficient of the parameter to be corrected to obtain the corrected monitoring data; Sensors for parameters to be corrected are installed upstream and downstream of the bridge. The disturbance coefficients of the parameters to be corrected corresponding to the upstream and downstream sensors both exhibit translational symmetry, i.e.: In the formula, The upstream parameter disturbance coefficient is the parameter to be corrected. The downstream parameter disturbance coefficient is to be corrected. The relative average wind direction To convert any angle to Operators; The disturbance coefficient of the parameter to be corrected has continuity within the circular plane, that is... In the formula, relative average wind direction The disturbance coefficient of the parameter to be corrected; The undetermined form of the disturbance coefficients of the parameter to be corrected is a high-order polynomial considering continuity, namely: In the formula, , , and All are polynomial coefficients.

2. The method for correcting bridge wind speed monitoring data considering bridge deck interference according to claim 1, characterized in that, The disturbance coefficients of the parameters to be corrected are solved using the least squares method.

3. The method for correcting bridge wind speed monitoring data considering bridge deck interference according to claim 1, characterized in that, The parameter to be corrected is the average wind speed, and the correction expression for the average wind speed is: In the formula, This is the corrected average wind speed. These are the average wind speeds extracted from upstream and downstream sensor observation data, respectively. This represents the relative average wind direction with the bridge axis as zero. The relative average wind direction is respectively At that time, the wind speed disturbance coefficients of upstream and downstream sensors.

4. The method for correcting bridge wind speed monitoring data considering bridge deck interference according to claim 3, characterized in that, The process of solving for the undetermined coefficients of the high-order polynomial of the disturbance coefficient of the average wind speed includes: Set target value: In the formula, For the i-th target value, The average wind speed is extracted from the downstream sensor observation data at time i. The average wind speed extracted from the upstream sensor observation data at time i; Fitted values: In the formula, For the i-th fitted value, Let be the wind speed disturbance coefficient of the downstream sensor under the i-th relative average wind direction; Least squares solution: In the formula, Let be the undetermined coefficient for the i-th optimal value; The optimal undetermined parameters are obtained by solving the problem using the least squares method.

5. The method for correcting bridge wind speed monitoring data considering bridge deck interference according to claim 3, characterized in that, The application environment for the average wind speed correction process is as follows: Due to the shielding effect of the bridge deck structure, the average wind speed extracted from the field measurement data is the disturbed value; The average wind speed decreases after being disturbed compared to the actual wind speed, and for the same wind direction angle, the decrease is proportional to the actual wind speed.

6. The method for correcting bridge wind speed monitoring data considering bridge deck interference according to claim 1, characterized in that, The parameter to be corrected is the turbulence intensity, and the correction expression for the turbulence intensity is: In the formula, The corrected turbulence intensity, These are the turbulence intensities extracted from upstream and downstream sensor observation data, respectively. These represent the relative average wind direction as follows: At that time, the turbulence intensity disturbance coefficients of the upstream and downstream sensors.

7. The method for correcting bridge wind speed monitoring data considering bridge deck interference according to claim 6, characterized in that, The process of solving for the undetermined coefficients of the high-order polynomial of the turbulence intensity perturbation coefficient includes: Set target value: In the formula, For the i-th target value, The turbulence intensity is extracted from the downstream sensor observation data at time i. The turbulence intensity is extracted from the upstream sensor observation data at time i. Fitted values: In the formula, For the i-th fitted value, Let be the turbulence intensity disturbance coefficient of the downstream sensor under the i-th relative average wind direction; Least squares solution: In the formula, Let be the undetermined coefficient for the i-th optimal value; The optimal undetermined parameters are obtained by solving the problem using the least squares method.

8. The method for correcting bridge wind speed monitoring data considering bridge deck interference according to claim 7, characterized in that, The application environment for the turbulence intensity correction process is as follows: Due to the shielding effect of the bridge deck structure, the turbulence intensity extracted from the field measurement data is the disturbed value; The intensity of turbulence increases after being disturbed compared to the actual turbulence intensity, and for the same wind direction angle, the increase is proportional to the actual turbulence intensity.

9. The method for correcting bridge wind speed monitoring data considering bridge deck interference according to claim 1, characterized in that, The method is embedded in computer software and executed.

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