Bridge multi-order frequency indirect identification method based on vehicle-road-bridge information decoupling

Abstract

The application is suitable for the field of bridge multi-order frequency identification method, and provides a bridge multi-order frequency indirect identification method based on vehicle-road-bridge information decoupling, which comprises the following steps: step S1: based on vehicle-bridge coupling dynamics equation, the coupling relationship among vehicle, road and bridge is established; step S2: by using dimensionless parameters, the road roughness information in the coupling system is completely eliminated from the difference between the front and rear wheel responses of the double-axle vehicle, and the vehicle and bridge information are separated; step S3: finally, according to the size of the driving speed, different subspace identification algorithms are selected to indirectly obtain the multi-order frequency of the bridge from the vehicle response. The technical problems of the adverse effect of road roughness in the process of indirectly identifying the bridge frequency through the vehicle response and the limitation of the vehicle driving speed are solved.

Description

Technical Field

[0001] This invention belongs to the field of bridge multi-frequency identification methods, and particularly relates to an indirect bridge multi-frequency identification method based on vehicle-road-bridge information decoupling. Background Technology

[0002] my country has the largest number of bridges currently in service in the world. As these bridges age and their service environment deteriorates, the load-bearing capacity of some bridges with low design standards and long service lives is facing severe challenges. Furthermore, early bridge construction in my country generally emphasized construction over maintenance, resulting in insufficient routine upkeep and delayed detection of damage, which can easily lead to safety hazards. Traditional bridge health monitoring methods require a large number and variety of sensors, are expensive, and have short lifespans, necessitating frequent maintenance and replacement.

[0003] Vehicle-response-based bridge modal scanning is a novel bridge system identification method that has emerged in recent years. This technology uses moving vehicles to sense, receive, and analyze relevant data from the bridge system to achieve rapid identification of urban bridge systems. The core idea of ​​this method is based on a vehicle-bridge coupled dynamics model, which considers that vehicles simultaneously act as both a "load excitation system" and a "signal receiving system" when crossing a bridge. On the one hand, the force exerted by the vehicle load on the bridge causes vibrations; on the other hand, the vehicle-bridge coupling relationship is used to indirectly collect modal information about the bridge from the vehicle response. Since the vehicle response contains information about both the vehicle and the bridge within the coupled system, by suppressing or eliminating the influence of vehicle-specific and environmental factors in the vehicle response, relevant bridge information can be obtained from the vehicle response.

[0004] The commonly used method is to indirectly identify bridge frequencies based on the frequency domain response of vehicles. There are also a few bridge frequency indirect identification techniques based on random subspace identification. However, these methods (1) are difficult to completely eliminate the adverse effects of road surface unevenness and vehicle information on bridge frequency identification, and (2) have a large limitation on vehicle speed, usually only 1 to 2 m / s. Summary of the Invention

[0005] This invention decouples the vehicle-road-bridge information contained in the vibration response of a two-axle vehicle traveling on a target bridge, and completely eliminates the road surface unevenness information in the vehicle response by using a dimensionless parameter method. It also separates the vehicle and bridge information, thereby enabling the indirect identification of the bridge's multi-order frequencies solely based on the vehicle response. This solves the technical problems of the adverse effects of road surface unevenness and the limitation of vehicle speed in the process of indirectly identifying bridge frequencies through vehicle response.

[0006] This invention is implemented as follows: a bridge multi-frequency indirect identification method based on vehicle-road-bridge information decoupling, the bridge multi-frequency indirect identification method comprising the following steps:

[0007] Step S1: Based on the vehicle-bridge coupled dynamic equations, establish the coupling relationship between the vehicle, road, and bridge;

[0008] Step S2: Using dimensionless parameters, road surface roughness information in the coupled system is completely eliminated from the difference in the front and rear wheel responses of a two-axle vehicle, while vehicle and bridge information are separated.

[0009] Step S3: Finally, based on the vehicle speed, different subspace identification algorithms are selected to indirectly obtain the multi-order frequencies of the bridge from the vehicle response.

[0010] A further technical solution of the present invention is that step S1 includes the following specific steps:

[0011] Step S11: Assemble the dual-axle vehicle model so that the stiffness coefficients of the front and rear axle suspension systems are k. c The damping coefficient is c c The first-order modal mass of the vehicle was obtained through testing. The first-order frequency is Speed ​​sensors and displacement sensors are placed at the center of the two axles, and tire pressure sensors are installed on the wheels.

[0012] A further technical solution of the present invention is that step S1 further includes the following specific steps:

[0013] Step S12: The vehicle crosses the bridge at a normal speed v, and the vertical displacement of the front and rear axles of the vehicle is monitored during the journey. and speed Simultaneously monitor the tire pressure of the front and rear wheels.

[0014] A further technical solution of the present invention is that step S1 further includes the following specific steps:

[0015] Step S13: For any target bridge, the measured bridge length is L. B Assume the bridge's mass, stiffness, and damping matrix are M, respectively. B K B C B The bridge response is Establish the kinematic equations of a two-axis, four-DOF vehicle-bridge system.

[0016]

[0017]

[0018] in, For the response of the vehicle in four degrees of freedom, M V K V C V These represent the mass, stiffness, and damping matrix of a two-axle vehicle. The contact force between the front and rear wheels and the road surface, i.e., the tire pressure, is modeled as follows:

[0019]

[0020]

[0021] in, This indicates the position of the wheels on the bridge. This indicates the elevation of the bridge surface unevenness at that location.

[0022] A further technical solution of the present invention is that step S2 includes the following specific steps:

[0023] Step S21: By using the vehicle-road contact force model and combining it with the vehicle-bridge kinematic equations, the relationship between the vehicle and the bridge can be established, and the vehicle and bridge responses can be dimensionless, resulting in the following equations.

[0024]

[0025] And it achieves decoupling of vehicle, road, and bridge information, where, The dimensionless vehicle and bridge responses are respectively used. The dimensionless stiffness parameters K of the front and rear wheels can be obtained by calculation. V =k c / m1 V (ω1 V ) 2 and damping parameter C V =c c / m1 V ω1 V and dimensionless tire pressure in addition, R(x) represents the relative position of the vehicle on the bridge. j ) = r c (x j ) / L B Indicates the relative position x j The dimensionless elevation of bridge surface unevenness.

[0026] A further technical solution of the present invention is that step S2 further includes the following specific steps:

[0027] Step S22: Formula (5) for the front and rear wheels of a two-axle vehicle corresponds to the same relative position x. jThe formula for the difference that takes into account the time difference and eliminates the influence of road surface unevenness is as follows:

[0028]

[0029] In the formula, It can be calculated based on measurement data.

[0030] A further technical solution of the present invention is that step S3 includes the following specific steps:

[0031] Step S31: Dimensionlessly transform the kinematic equations (1) of the bridge, and together with equation (6), convert them into state-space matrix equations as follows:

[0032]

[0033]

[0034] Treating the bridge as an unknown system, formula (7-8) is formally applicable to the subspace identification method; the tire pressure difference between the front and rear wheels can be calculated based on the measurement data. and the output signal ΔP k

[0035]

[0036] A further technical solution of the present invention is that step S3 includes the following specific steps:

[0037] Step S32: When the vehicle speed is relatively low, the dimensionless speed parameter is satisfied. The last term in formula (7) and the time-varying matrix can be ignored. The impact on subspace identification method recognition, and on the output signal ΔP k The multiple frequencies of the bridge can be calculated by applying the stochastic subspace identification method (ST-SSI).

[0038] A further technical solution of the present invention is that step S3 further includes the following specific steps:

[0039] Step S33: If the vehicle speed is high, apply the pseudo-inverse matrix to formula (8) to calculate as follows.

[0040]

[0041] Tire pressure difference between the two wheels and output signals containing vehicle location information The MOESP algorithm can be used to calculate the multiple frequencies of a bridge.

[0042] The beneficial effects of this invention are as follows: This method for indirect identification of bridge multi-frequency components decouples the vehicle-road-bridge information contained in the vibration response generated by a two-axle vehicle traveling on the target bridge. It completely eliminates the road surface unevenness information in the vehicle response by using a dimensionless parameter method and separates the vehicle and bridge information. This enables the indirect identification of bridge multi-frequency components solely based on the vehicle response. Furthermore, it allows for large-scale screening of urban bridge systems using public transportation vehicles at low cost, quickly, and efficiently without affecting normal traffic operations. Attached Figure Description

[0043] Figure 1 This is a flowchart illustrating the steps of a bridge multi-frequency indirect identification method based on vehicle-road-bridge information decoupling provided in this embodiment of the invention.

[0044] Figure 2 This is a schematic diagram of a dual-axle vehicle model for a bridge multi-frequency indirect identification method based on vehicle-road-bridge information decoupling provided in an embodiment of the present invention. Detailed Implementation

[0045] Figure 1-2 This invention illustrates a bridge multi-frequency indirect identification method based on vehicle-road-bridge information decoupling, comprising the following steps:

[0046] Step S1: Based on the vehicle-bridge coupled dynamic equation, establish the coupling relationship between vehicle, road, and bridge.

[0047] Step S11: Assemble the two-axle vehicle model, such as Figure 2 As shown, the stiffness coefficients of the front and rear axle suspension systems of the vehicle are k. c The damping coefficient is c c The first-order modal mass of the vehicle was obtained through testing. The first-order frequency is Speed ​​sensors and displacement sensors are placed at the center of the two axles, and tire pressure sensors are installed on the wheels.

[0048] Step S12: The vehicle crosses the bridge at a normal speed v, and the vertical displacement of the front and rear axles of the vehicle is monitored during the journey. and speed Simultaneously monitor the tire pressure of the front and rear wheels.

[0049] Step S13: For any target bridge, the measured bridge length is L. B Assume the bridge's mass, stiffness, and damping matrix are M, respectively. B K B C B The bridge response is Establish the kinematic equations of a two-axis, four-DOF vehicle-bridge system.

[0050]

[0051]

[0052] in, For the response of the vehicle in four degrees of freedom, M V K V C V These represent the mass, stiffness, and damping matrix of a two-axle vehicle. The contact force between the front and rear wheels and the road surface, i.e., the tire pressure, is modeled as follows:

[0053]

[0054]

[0055] in, This indicates the position of the wheels on the bridge. This indicates the elevation of the bridge surface unevenness at that location.

[0056] Step S2: Using dimensionless parameters, road surface roughness information in the coupled system is completely eliminated from the difference in the front and rear wheel responses of the two-axle vehicle, while vehicle and bridge information are separated.

[0057] Step S21: By using the vehicle-road contact force model and combining it with the vehicle-bridge kinematic equations, the relationship between the vehicle and the bridge can be established, and the vehicle and bridge responses can be dimensionless, resulting in the following equations.

[0058]

[0059] And it achieves decoupling of vehicle, road, and bridge information, where, The dimensionless vehicle and bridge responses are respectively used. The dimensionless stiffness parameters K of the front and rear wheels can be obtained by calculation. V =k c / m1 V (ω1 V ) 2 and damping parameter C V =c c / m1 V ω1 V and dimensionless tire pressure in addition, R(x) represents the relative position of the vehicle on the bridge. j ) = r c (x j ) / L B Indicates the relative position x jThe dimensionless elevation of bridge surface unevenness.

[0060] Step S22: Formula (5) for the front and rear wheels of a two-axle vehicle corresponds to the same relative position x. j The formula for the difference that takes into account the time difference and eliminates the influence of road surface unevenness is as follows:

[0061]

[0062] In the formula, It can be calculated based on measurement data.

[0063] Steps S21-S22 combine the dimensionless vehicle-bridge coupled dynamic equations, which not only establishes the connection between the vehicle and the bridge, but also achieves effective decoupling of vehicle, road, and bridge information, completely eliminating road surface information in the coupled system and eliminating the disadvantages of indirectly identifying the bridge's multi-order frequencies based on vehicle response.

[0064] Step S3: Finally, based on the vehicle speed, different subspace identification algorithms are selected to indirectly obtain the multi-order frequencies of the bridge from the vehicle response.

[0065] Step S31: Dimensionlessly transform the kinematic equations (1) of the bridge, and together with equation (6), convert them into state-space matrix equations as follows:

[0066]

[0067]

[0068] Treating the bridge as an unknown system, formula (7-8) is formally applicable to the subspace identification method; the tire pressure difference between the front and rear wheels can be calculated based on the measurement data. and the output signal ΔP k

[0069]

[0070] Step S32: When the vehicle speed is relatively low, the dimensionless speed parameter is satisfied. The last term in formula (7) and the time-varying matrix can be ignored. The impact on subspace identification method recognition, and on the output signal ΔP k The multiple frequencies of the bridge can be calculated by applying the stochastic subspace identification method (ST-SSI).

[0071] Step S33: If the vehicle speed is high, apply the pseudo-inverse matrix to formula (8) to calculate as follows.

[0072]

[0073] Tire pressure difference between the two wheels and output signals containing vehicle location information The MOESP algorithm can be used to calculate the multiple frequencies of a bridge.

[0074] Step S33 introduces pseudo-inverse matrix calculation, making the method applicable to two-axle vehicles at any speed, even if the vehicle is traveling at normal or high speed.

[0075] This indirect method for identifying bridge multi-frequency components decouples the vehicle-road-bridge information contained in the vibration response of a two-axle vehicle traveling on the target bridge. It uses a dimensionless parameter method to completely eliminate road surface unevenness information in the vehicle response and separates vehicle and bridge information. This allows for the indirect identification of bridge multi-frequency components solely based on vehicle response. Furthermore, it enables large-scale screening of urban bridge systems using public transportation vehicles at low cost, quickly, and efficiently without affecting normal traffic operations.

[0076] 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, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A bridge multi-frequency indirect identification method based on vehicle-road-bridge information decoupling, characterized in that, The bridge multi-order frequency indirect identification method includes the following steps: Step S1: Based on the vehicle-bridge coupled dynamic equations, establish the coupling relationship between the vehicle, road, and bridge; Step S2: Using dimensionless parameters, road surface roughness information in the coupled system is completely eliminated from the difference in the front and rear wheel responses of a two-axle vehicle, while vehicle and bridge information are separated. Step S3: Finally, based on the vehicle speed, different subspace identification algorithms are selected to indirectly obtain the multi-order frequencies of the bridge from the vehicle response; Step S1 includes the following specific steps: Step S11: Assemble the dual-axle vehicle model so that the stiffness coefficients of the front and rear axle suspension systems are k. c The damping coefficient is c c The first-order modal mass of the vehicle was obtained through testing. The first-order frequency is Speed ​​sensors and displacement sensors are placed at the center of the two axles, and tire pressure sensors are installed on the wheels. Step S1 further includes the following specific steps: Step S12: The vehicle crosses the bridge at a normal speed v, and the vertical displacement of the front and rear axles of the vehicle is monitored during the journey. and speed Simultaneously monitor the tire pressure of the front and rear wheels. Step S1 further includes the following specific steps: Step S13: For any target bridge, the measured bridge length is L. B Assume the bridge's mass, stiffness, and damping matrix are M, respectively. B K B C B The bridge response is Establish the kinematic equations of a two-axis, four-DOF vehicle-bridge system. in, For the response of the vehicle in four degrees of freedom, M V K V C V These represent the mass, stiffness, and damping matrix of a two-axle vehicle. The contact force between the front and rear wheels and the road surface, i.e., the tire pressure, is modeled as follows: in, This indicates the position of the wheels on the bridge. This indicates the elevation of the bridge surface unevenness at that location; Step S2 includes the following specific steps: Step S21: By using the vehicle-road contact force model and combining it with the vehicle-bridge kinematic equations, the relationship between the vehicle and the bridge can be established, and the vehicle and bridge responses can be dimensionless, resulting in the following equations. To achieve decoupling of vehicle, road, and bridge information, in the formula, The dimensionless vehicle and bridge responses are respectively used. The dimensionless stiffness parameters of the front and rear wheels can be obtained by calculation. and damping parameters and dimensionless tire pressure in addition, R(x) represents the relative position of the vehicle on the bridge. j ) = r c (x j ) / L B Indicates the relative position x j Dimensionless elevation of bridge surface unevenness; Step S2 further includes the following specific steps: Step S22: Formula (5) for the front and rear wheels of a two-axle vehicle corresponds to the same relative position x. j The formula for the difference that takes into account the time difference and eliminates the influence of road surface unevenness is as follows: In the formula, and It can be calculated based on measurement data; Step S3 includes the following specific steps: Step S31: Dimensionlessly transform the kinematic equations (1) of the bridge, and together with equation (6), convert them into state-space matrix equations as follows: Treating the bridge as an unknown system, formula (7-8) is formally applicable to the subspace identification method, and the tire pressure difference between the front and rear wheels can be calculated based on the measurement data. and the output signal ΔP k Step S3 includes the following specific steps: Step S32: When the vehicle speed is relatively low, the dimensionless speed parameter is satisfied. The last term in formula (7) and the time-varying matrix can be ignored. The impact on subspace identification method recognition, and on the output signal ΔP k The multiple frequencies of the bridge can be calculated by applying the stochastic subspace identification method (ST-SSI). Step S3 further includes the following specific steps: Step S33: If the vehicle speed is high, apply the pseudo-inverse matrix to formula (8) to calculate as follows. Tire pressure difference between the two wheels and output signals containing vehicle location information The MOESP algorithm can be used to calculate the multiple frequencies of a bridge.

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