Mobile measurement trolley based on bridge frequency measurement and damping tuning

Abstract

The invention discloses a mobile measurement trolley based on bridge frequency measurement and damping tuning, which comprises a system pre-starting and parameter initialization stage: a first pass pre-scanning and parameter coarse identification stage: in the stage, the trolley passes through a bridge at a constant speed, collects a vibration signal, position information and a suspension state, and extracts a bridge fundamental frequency estimated value through FFT analysis; in the damping parameter dynamic tuning stage, tuning is carried out based on the fixed point principle, the optimal frequency ratio and the optimal damping ratio are calculated, and the damping parameters are adjusted; a secondary passing fine measurement and verification stage: performing high-precision data acquisition on the trolley through the bridge again in the stage, calculating a difference value, and judging the frequency stability; in the cycle tuning and convergence judgment stage, when the frequency change rate is larger than a threshold value, the mobile measurement trolley starts a new round of tuning-measurement cycle until the requirement is met, and the technical obstacles that a traditional passive mass damper is limited by space and weight, insufficient in controllability and the like in mobile vehicle scene application are overcome.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of bridge detection equipment, in particular to a bridge frequency measurement and damping tuning mobile measurement trolley. BACKGROUND

[0002] With the development of bridge structure health monitoring technology, the traditional fixed monitoring system gradually develops towards mobile monitoring due to its limited coverage, high installation and maintenance costs, etc. The bridge health monitoring method based on vehicle-bridge coupling system has become a research hotspot in recent years due to its strong mobility and wide coverage.

[0003] At present, the bridge health monitoring method based on vehicle-bridge coupling system mainly obtains the dynamic characteristic parameters of the bridge by detecting the vibration response of the vehicle when passing through the bridge. For example, CN106802222A discloses a bridge damage diagnosis method based on vehicle-bridge coupling system, which starts from different positions on the bridge by two detection vehicles, synchronously collects the vertical acceleration response of the vehicle during each passing through the bridge, and obtains the approximate vertical displacement response of the vehicle through secondary integral processing, thereby diagnosing the bridge damage [1]. CN107727338B also proposes a similar method, which realizes the detection of bridge damage by two detection vehicles passing through the bridge by being towed by a tractor, collecting the vertical acceleration response of the vehicle, and obtaining the vertical displacement response of the vehicle.

[0004] In terms of bridge dynamic characteristic parameter identification, CN119178572A proposes a non-stationary vibration signal acquisition and analysis system for linear time-varying structures simulated by a small vehicle passing through the bridge. The system simulates bridge structures with different time-varying characteristics by changing the mass and motion mode of the mass block, and realizes dynamic monitoring and analysis of the bridge structure through multi-modal sensors, dynamic parameter control modules and signal processing modules [3]. CN118468539A discloses a method for obtaining the impact coefficient of a highway continuous beam bridge, which considers the influence of road roughness on vehicle vibration response, and obtains the random force spectrum of the continuous beam bridge by calculating the power spectral density of the vibration response of the moving vehicle system under the action of road roughness [4].

[0005] In terms of bridge vibration control, CN110528381A discloses a four-wire pendulum tuned mass damper for long boom vibration reduction of large-span bridges and a design method. The damper provides a control force opposite to the vibration direction of the boom through pendulum feedback, dissipates energy through universal rotating ball hinges at the connection between the pendulum and the support or / and air dampers between the boom and the counterweight, and has a significant control effect on the displacement and velocity response of the boom [5].

[0006] However, the existing bridge health monitoring method based on vehicle-bridge coupling system still has the following problems: 1. Vehicle self-vibration noise interference is serious, which affects the accuracy of bridge frequency identification. When the existing mobile detection vehicle passes through the bridge, the vibration of the vehicle itself will interfere with the measurement signal, reducing the accuracy of bridge frequency identification[1][2].

[0007] 2. In the vehicle-bridge coupling system, the passage of the vehicle causes the bridge frequency to change over time, i.e. the frequency time-varying effect, which is difficult to effectively control and affects the stability of bridge frequency identification[3].

[0008] 3. The suspension parameters of the existing mobile detection vehicle are not optimized, resulting in poor robustness of parameter identification and difficulty in adapting to the detection needs of different types of bridges[4].

[0009] 4. The traditional passive mass damper (TMD) has technical obstacles such as space and weight constraints, insufficient control, etc. in the application of mobile vehicle scenarios[5].

[0010] 5. There is a lack of an intelligent tuning system that can adjust the damping parameters in real time according to the bridge frequency. The existing dampers are designed with fixed parameters and cannot adapt to changes in bridge dynamic characteristics[5].

[0011] Therefore, it is urgent to develop a mobile measurement device that can real-time tune damping parameters and improve the accuracy of bridge frequency identification to solve the above technical problems. SUMMARY

[0012] In order to solve the technical challenges faced by the existing mobile detection vehicle and the limited coverage and high operation and maintenance cost of traditional bridge monitoring methods, achieve high-precision bridge frequency identification and dynamic decoupling, the present application provides a mobile measurement trolley based on bridge frequency measurement and damping tuning.

[0013] The technical solution adopted by the present application to solve its technical problems is: The mobile measurement trolley comprises a multi-modal sensor array, a driving and feedback device, and a damping adjustment control device. The multi-modal sensor array comprises an accelerometer and a displacement sensor. The driving and feedback device comprises a wireless communication module, a vehicle-mounted processor, a driver, and a driving rod. The damping adjustment control device comprises a driving module, an integrated mass block, a wireless signal transceiver device, a stiffness unit, and a damping adjustment unit. The mobile measurement trolley realizes the measurement process according to the adjustment of bridge frequency measurement and damping tuning, comprising the following steps: System pre-start and parameter initialization stage: activate the vehicle-mounted processor and communication module, damping adjustment control device, multi-modal sensor array, and input bridge foundation parameters; First-pass pre-scanning and parameter rough identification stage: the trolley passes through the bridge at a constant speed, collects vibration signals, position information and suspension state, and extracts the bridge base frequency estimate through FFT analysis; Damping parameter dynamic tuning stage: this stage is based on the fixed point principle tuning, calculating the optimal frequency ratio and optimal damping ratio, adjusting the damping parameter; Second-pass fine measurement and verification stage: the trolley passes through the bridge again for high-precision data collection, calculates the frequency difference, and determines the frequency stability; Cyclic tuning and convergence determination stage: when the frequency change rate is greater than the threshold, the mobile measurement trolley starts a new round of tuning-measurement cycle until the requirements are met.

[0014] Further, the mobile measurement trolley starts a new round of tuning-measurement cycle process, including: Before measurement, the basic parameters of the bridge are input into the vehicle-mounted processor to construct the bridge base frequency estimation model according to the following formula, that is:

[0015] Where w(x, t) is the lateral displacement of the bridge, δ(x) is the Dirac delta function, m is the total mass of the vehicle, x2(t) is the position of the contact point; for constant speed, x c (t) = v t ; F d (t) is the dynamic load force on the bridge; After the trolley measures for the first time, the multi-modal sensor array sends the signal to the vehicle-mounted processor to obtain the bridge base frequency estimate; The vehicle-mounted processor calculates the vehicle damping ratio according to the frequency estimate according to the following formula, and outputs the signal to the drive module;

[0016]

[0017] Where , is the non-coupled natural frequency of the sprung mass, where ω is the first-order frequency of the bridge, is the non-coupled natural frequency of the unsprung mass, defined as the mass ratio of the sprung mass to its unsprung mass. Where, solving formula three obtains the damping ratio .

[0018] The damping adjustment unit adjusts the damping ratio signal based on the received bridge frequency to obtain the optimal damping ratio, which is then fed back to the on-board processor. Each time a new bridge frequency is obtained in the on-board damper, damping tuning is performed until the frequency change rate is less than a specified value. The onboard processor 8 determines the final bridge frequency based on whether the bridge frequency change rate is less than a specified value. Damping ratio ζ b。 The process report includes tuning parameters for each cycle, frequency change rate curves, and spectrum comparison charts.

[0019] Beneficial effects The beneficial effects of this invention are as follows: By employing semi-active suspension tuning technology, the time-varying frequency effect is effectively suppressed, significantly reducing the bridge frequency identification error from ±2% to ±0.5%; an instantaneous frequency model of the vehicle-bridge system is established based on time-freezing technology, achieving dynamic decoupling and making the bridge frequency approach constant during vehicle traffic; an adaptive closed-loop tuning method using a "pre-scan-tuning-verification" cycle is adopted, eliminating the need for complex signal separation algorithms and greatly improving measurement efficiency; the tuned suspension system can reduce bridge vibration energy by 90%, effectively avoiding excitation interference during measurement; and through hardware-algorithm co-design, high-precision identification of the bridge's natural frequency is achieved, overcoming the technical obstacles of traditional passive mass dampers in mobile vehicle scenarios, such as space and weight constraints and insufficient controllability. Attached Figure Description

[0020] Figure 1 This is a schematic diagram of a mobile measuring trolley structure based on bridge frequency measurement and damping tuning according to the present invention. Figure 2 This is a flowchart of the operation of a mobile measuring trolley based on bridge frequency measurement and damping tuning according to the present invention. Detailed Implementation

[0021] The technical solution of the present invention will now be clearly and completely described with reference to the accompanying drawings and embodiments. Obviously, the described embodiments are merely some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0022] like Figure 1 As shown, the present invention provides a mobile measuring vehicle, comprising a multimodal sensor array, a drive and feedback device, and a damping adjustment and control device; wherein, the multimodal sensor array includes an accelerometer and a displacement sensor; the drive and feedback device includes a wireless communication module, an on-board processor, a driver, and a drive rod; the damping adjustment and control device includes a drive module, an integrated mass block, a wireless signal transceiver, a stiffness unit, and a damping adjustment unit. The working process of the mobile measuring vehicle includes the following steps, such as... Figure 2 As shown: During the system pre-start and parameter initialization phase, the on-board processor and communication module, damping adjustment control device, and multimodal sensor array are activated, and bridge foundation parameters are input. In the initial pre-scanning and parameter coarse identification stage, the vehicle passes through the bridge at a constant speed, collecting vibration signals, location information and suspension status. The on-board processor extracts the bridge's fundamental frequency estimate through FFT analysis. The dynamic tuning stage of the damping parameters is based on the fixed-point principle. The optimal frequency ratio and optimal damping ratio are calculated, and the damping parameters are adjusted.

[0023] In the second phase of precise measurement and verification, the vehicle passes over the bridge again to collect high-precision data, calculate the frequency difference, and determine the frequency stability. Cyclic tuning and convergence determination: When the rate of change of frequency is greater than the threshold, the system starts a new round of tuning-measurement cycle until the requirements are met.

[0024] Example 1 This embodiment provides a damping tuning method, which is applied to a mobile measuring trolley for measuring and tuning the damping of bridges.

[0025] Before measurement, the bridge's basic parameters are input into the onboard processor 8. These parameters include the bridge's length, width, height, material type, and estimated natural frequency range. These parameters form the basis for subsequent damping tuning calculations.

[0026] After receiving the basic parameters of the bridge, the on-board processor 8 establishes relevant mathematical models. These models include the bridge's dynamic model, damping characteristic model, and frequency response model. Using these mathematical models, the on-board processor 8 can predict the bridge's vibration response under different excitation conditions and provide a theoretical basis for subsequent damping tuning.

[0027] The mobile measuring trolley conducted its first measurement on the bridge. During the measurement, accelerometer 5 in the multimodal sensor array 1 detected the bridge's vibration acceleration, and displacement sensor 6 detected the bridge's displacement changes. These sensors worked simultaneously to collect vibration data from the bridge.

[0028] After the first measurement is completed, the multimodal sensor array 1 sends the collected signals to the on-board processor 8. The on-board processor 8 processes and analyzes these signals, using signal processing methods such as Fast Fourier Transform to obtain the bridge's frequency prediction. This frequency prediction reflects the bridge's current vibration characteristics.

[0029] The on-board processor 8 calculates the optimal damping based on the obtained frequency prediction and other relevant data. The process of calculating the optimal damping includes the following steps: First, the on-board processor 8 determines the dynamic characteristics of the bridge based on the frequency prediction of the bridge; second, the on-board processor 8 calculates the damping coefficient that can minimize the bridge vibration by combining the mass distribution, stiffness characteristics and current vibration state of the bridge; finally, the on-board processor 8 converts the calculated damping coefficient into the control parameters of the damping adjustment unit 15.

[0030] The on-board processor 8 outputs the calculated optimal damping control parameters to the drive module 11. After receiving the control parameters, the drive module 11 generates corresponding control signals to adjust the working state of the damping adjustment unit 15.

[0031] The damping adjustment unit 15 adjusts the damping according to the control signal from the drive module 11. The damping adjustment unit 15 can precisely adjust the damping coefficient by changing the internal structure of the damper, adjusting the flow channel area of ​​the damping oil, or changing the magnetic field strength of the electromagnetic damper. Through this adjustment, the device achieves the optimal damping ratio.

[0032] After the damping adjustment is completed, the mobile measuring trolley continues to measure on the bridge. Each time a new bridge frequency is obtained in the on-board damper, the damping is tuned. Specifically, the multimodal sensor array 1 collects the bridge's vibration data again, the on-board processor 8 analyzes this data to obtain the new bridge frequency, then recalculates the optimal damping, and adjusts the damping through the drive module 11 and the damping adjustment unit 15.

[0033] This invention obtains the optimal damping ratio by establishing a mathematical model: Before measurement, the basic parameters of the bridge are input into the on-board processor 8, and a relevant mathematical model is established in the on-board processor 8. Ignoring the equilibrium deflection of the bridge under its own weight, the control equation for the lateral vibration of the bridge caused by the moving vehicle is:

[0034] Where w(x, t) is the lateral displacement of the bridge, δ(x) is the Dirac delta function, and m = m s +m u x is the total mass of the vehicle, and x2(t) is the position of the contact point. For a constant speed, x c (t) = v t F d (t) represents the dynamic load on the bridge. A coarse frequency of the bridge is calculated based on its foundation parameters.

[0035] transfer function Therefore, the dynamic coupling between the transfer functions of these lumped masses can be expressed as:

[0036] Among them, H s and H u It is a complex amplitude response function that describes the transfer characteristics of a system. It is the uncoupled natural frequency of the sprung mass. This is the damping ratio of the sprung mass. The tilde notation will be used to represent the frequency of the uncoupled system.

[0037] The solution is:

[0038] 3.3 Application of the Extended Fixed-Point Principle Fixed point identification: Substitute formula (2) into formula (3) and simplify the algebraic operations to obtain the result.

[0039] in Simplify In order to make |H q |Irrelevant to ζ, it can be simplified, and the frequency values ​​of these fixed points can be solved from it.

[0040]

[0041] Substituting the bridge frequency estimate into the above formula, we can obtain three solutions ω. * 1. ω * 2, ω * 3, but ω * The value of 3 is usually beyond the range of practical concern. Since the most important natural frequencies of highway bridges are typically below 10 Hz, it is unnecessary to consider ω. * 3. This point. We will only consider ω near the frequency of the uncoupled system. * 1 and ω * 2.

[0042] The optimal tuning system first achieves this by making the dynamic amplification factor at ω * 1 and ω * The magnitudes at points 2 are equal, i.e., |H q | ω*1 = |H q | ω*2 Since the response amplitude at these two points is independent of ζ, equation (5) can be simplified by setting ζ = 0 or ζ→∞. By setting ζ = 0 in equation (5) and applying the optimal tuning condition, we obtain:

[0043] The solution to the above equation gives the natural frequency of the uncoupled sprung mass. Optimal tuning value Optimal parameter tuning steps: Damping tuning: We can obtain the optimal damping ratio by solving the following equation. Determine the optimal damping ratio (ζ). opt Determine the optimal damping.

[0044] This damping tuning process is repeated until the rate of frequency change is less than a specified value. The rate of frequency change refers to the relative change in the bridge frequency between two consecutive measurements. When the rate of frequency change is less than a preset threshold (e.g., 0.5%), it indicates that the bridge's vibration characteristics have stabilized, and the damping tuning process can be terminated.

[0045] Example 2 This embodiment provides a mobile measuring trolley, which is designed and manufactured using the damping tuning method described in Embodiment 1.

[0046] The mobile measurement vehicle consists of three core modules: a multimodal sensor array 1, a drive and feedback device 2, and a damping adjustment and control device 3.

[0047] The multimodal sensor array 1 includes an accelerometer 5 and a displacement sensor 6. The accelerometer 5 is mounted in the middle of the mobile measuring vehicle and is used to detect the vibration acceleration of the bridge. The accelerometer 5 is a triaxial MEMS accelerometer with a measurement range of ±10g and a sensitivity of 0.01g. The displacement sensor 6 is mounted at the bottom of the mobile measuring vehicle and is used to detect changes in bridge displacement. The displacement sensor 6 uses laser ranging, with a measurement range of 0-100 mm and an accuracy of 0.01 mm.

[0048] The drive and feedback device 2 includes a wireless communication module 7, an on-board processor 8, a driver 9, and a drive rod 10. The wireless communication module 7 uses 5G communication technology, enabling high-speed data transmission and ensuring the real-time nature of measurement data. The on-board processor 8 uses a high-performance embedded processor with a main frequency of 2.5GHz, 16GB of RAM, and 512GB of storage, capable of quickly processing large amounts of measurement data and performing complex computational tasks. The driver 9 uses a high-precision stepper motor with a step angle of 0.9 degrees and a maximum torque of 5 N·m, enabling precise control of the movement of the drive rod 10. The drive rod 10 is made of carbon fiber, featuring high strength and low weight, and effectively transmits driving force.

[0049] The damping adjustment control device 3 includes a drive module 11, an integrated mass block 12, a wireless signal transceiver 13, a stiffness unit 14, and a damping adjustment unit 15. The drive module 11 employs a power amplifier circuit controlled by a digital signal processor (DSP), capable of converting the control signal output from the vehicle processor 8 into a current signal driving the damping adjustment unit 15. The integrated mass block 12, made of high-density alloy material, weighs 10 kg and is installed at one end of the damping adjustment unit 15 to provide inertial force. The wireless signal transceiver 13 uses Bluetooth Low Energy technology for data exchange with the vehicle processor 8. The stiffness unit 14 employs a variable stiffness spring structure with a stiffness range of 1000-5000 N / m, adjustable as needed. The damping adjustment unit 15 uses a magnetorheological damper, with a damping coefficient continuously adjustable within the range of 50-500 N·s / m.

[0050] The working process of the mobile measurement vehicle is as follows: First, the basic parameters of the bridge are input into the on-board processor 8, which establishes a relevant mathematical model. Then, the mobile measurement vehicle performs its first measurement on the bridge. The multimodal sensor array 1 collects the bridge's vibration data and transmits it to the on-board processor 8 via the wireless communication module 7. The on-board processor 8 analyzes this data, obtains the bridge's frequency prediction, and calculates the optimal damping. The on-board processor 8 sends the calculation results to the drive module 11 via the wireless communication module 7. The drive module 11 controls the damping adjustment unit 15 to adjust the damping. The mobile measurement vehicle continues to measure on the bridge, and each time a new bridge frequency is obtained, the damping is tuned until the frequency change rate is less than a specified value.

[0051] Example 3 This embodiment provides a detailed structure of the core module of a mobile measuring vehicle, which is designed and manufactured using the damping tuning method described in Embodiment 1.

[0052] The multimodal sensor array 1 includes an accelerometer 5 and a displacement sensor 6. The accelerometer 5 is a piezoelectric triaxial accelerometer, consisting of a piezoelectric crystal, a mass block, and a signal conditioning circuit. When the bridge vibrates, the mass block exerts pressure on the piezoelectric crystal, causing the crystal to generate a charge proportional to the acceleration. The signal conditioning circuit converts these charges into a voltage signal. The accelerometer 5 has a sampling frequency of 1000Hz, enabling it to capture the high-frequency vibration characteristics of the bridge. The displacement sensor 6 uses the laser triangulation principle and consists of a laser diode, a position-sensitive detector, and a signal processing circuit. The laser beam emitted by the laser diode illuminates the bridge surface, and the reflected laser beam is received by the position-sensitive detector. The bridge displacement is calculated based on the change in the laser beam's position on the detector. The displacement sensor 6 has a sampling frequency of 500Hz, enabling it to accurately measure minute displacement changes in the bridge.

[0053] The drive and feedback device 2 includes a wireless communication module 7, an on-board processor 8, a driver 9, and a drive lever 10. The wireless communication module 7 uses 5G communication technology and consists of a radio frequency transceiver, a baseband processor, and an antenna. The radio frequency transceiver is responsible for signal transmission and reception, the baseband processor for signal encoding and decoding, and the antenna for electromagnetic wave transmission and reception. The wireless communication module 7 has a transmission rate of up to 1Gbps and a latency of less than 10 milliseconds, ensuring real-time transmission of measurement data. The on-board processor 8 uses a multi-core ARM architecture processor, equipped with a dedicated floating-point arithmetic unit and a digital signal processing unit, enabling efficient execution of complex mathematical calculations and signal processing tasks. The on-board processor 8 runs a real-time operating system, has multi-tasking capabilities, and can simultaneously process multiple sensor data streams and execute damping tuning algorithms. The driver 9 uses a closed-loop controlled stepper motor drive system, consisting of a stepper motor, an encoder, and a drive circuit. The stepper motor provides rotational power, the encoder detects the actual rotation angle of the motor, and the drive circuit adjusts the motor's drive current based on the encoder's feedback signal to achieve precise position control. The drive rod 10 is made of carbon fiber composite material with an internal honeycomb structure design, which provides high strength, low weight, and good bending resistance. One end of the drive rod 10 is connected to the driver 9, and the other end is connected to the damping adjustment unit 15 to transmit driving force.

[0054] The damping adjustment control device 3 includes a drive module 11, an integrated mass block 12, a wireless signal transceiver 13, a stiffness unit 14, and a damping adjustment unit 15. The drive module 11 employs an H-bridge power amplifier circuit controlled by a digital signal processor (DSP), consisting of a DSP controller, an H-bridge drive circuit, and a current detection circuit. The DSP controller receives control signals from the on-board processor 8 and generates a PWM waveform. The H-bridge drive circuit converts the PWM waveform into a drive current, and the current detection circuit monitors the actual output current and feeds it back to the DSP controller, forming a closed-loop control. The output current range of the drive module 11 is 0-5A, with a current accuracy of 0.01A, enabling precise control of the operating state of the damping adjustment unit 15. The integrated mass block 12, made of tungsten alloy, weighs 10 kg and has a volume of 500 cubic centimeters. It is installed at one end of the damping adjustment unit 15 to provide inertial force. The wireless signal transceiver 13 uses Bluetooth Low Energy 5.0 technology and consists of a Bluetooth chip, an antenna, and a power management circuit. The Bluetooth chip is responsible for signal encoding, decoding, and transmission; the antenna is responsible for electromagnetic wave transmission and reception; and the power management circuit is responsible for controlling power consumption. The wireless transceiver 13 has a transmission distance of up to 100 meters and power consumption of less than 10mW, enabling stable communication with the vehicle-mounted processor 8. The stiffness unit 14 adopts a variable stiffness spring structure, consisting of a main spring, an auxiliary spring, and an adjustment mechanism. The main spring provides basic stiffness, while the auxiliary spring can partially or fully participate in the work through the control of the adjustment mechanism, thereby changing the overall stiffness. The stiffness range of the stiffness unit 14 is 1000-5000 N / m, with an adjustment accuracy of 100 N / m, capable of adapting to different vibration conditions. The damping adjustment unit 15 uses a magnetorheological damper, consisting of a magnetorheological fluid, a piston, an electromagnetic coil, and a housing. The magnetorheological fluid changes viscosity under the influence of a magnetic field; the resistance experienced by the piston when moving in the magnetorheological fluid is related to the magnetic field strength; the electromagnetic coil generates a controllable magnetic field; and the housing provides sealing and support. The damping coefficient of the damping adjustment unit 15 can be continuously adjusted within the range of 50-500 N·s / m, with a response time of less than 10 milliseconds, enabling fast and precise damping adjustment.

[0055] The working process of the mobile measuring vehicle is as follows: Before measurement, the operator inputs the basic parameters of the bridge into the on-board processor 8 via the wireless communication module 7. The on-board processor 8 establishes a dynamic model and a damping characteristic model of the bridge based on these parameters. When the mobile measuring vehicle travels on the bridge, the accelerometer 5 detects the vibration acceleration of the bridge, and the displacement sensor 6 detects the displacement change of the bridge. These sensor data are input into the processor through the data acquisition interface of the on-board processor 8. The on-board processor 8 performs filtering, Fourier transform, and other processing on these data to obtain the frequency prediction value of the bridge. The on-board processor 8 calculates the optimal damping coefficient based on the frequency prediction value and the dynamic model, and sends the control signal to the drive module 11 via the wireless communication module 7. The drive module 11 generates a corresponding drive current based on the received control signal, controls the magnetic field strength of the electromagnetic coil in the damping adjustment unit 15, thereby adjusting the viscosity of the magnetorheological fluid and achieving precise control of the damping coefficient. The mobile measuring vehicle continues to travel on the bridge, and the multimodal sensor array 1 continuously collects new vibration data. The onboard processor 8 updates the bridge's frequency estimate based on this data and recalculates the optimal damping. The drive module 11 and damping adjustment unit 15 adjust the damping coefficient according to the new control signal. This process is repeated until the relative change between two adjacent measurements of the bridge frequency is less than a preset threshold (e.g., 0.5%), indicating that the bridge's vibration characteristics have stabilized and the damping tuning process is complete.

[0056] It should be noted that Embodiment 1, Embodiment 2, and Embodiment 3 are all types of damping tuning methods.

[0057] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A mobile measuring trolley based on bridge frequency measurement and damping tuning, characterized in that: The mobile measuring vehicle includes a multimodal sensor array, a drive and feedback device, and a damping adjustment and control device; wherein, the multimodal sensor array includes an accelerometer and a displacement sensor; the drive and feedback device includes a wireless communication module, an on-board processor, a driver, and a drive rod; the damping adjustment and control device includes a drive module, an integrated mass block, a wireless signal transceiver, a stiffness unit, and a damping adjustment unit; wherein, the mobile measuring vehicle realizes the measurement process based on bridge frequency measurement and damping tuning adjustment, including the following steps: System pre-start and parameter initialization phase: This phase activates the on-board processor and communication module, damping adjustment control device, and multimodal sensor array, and inputs bridge foundation parameters; Pre-scanning and coarse parameter identification stage: In this stage, the vehicle passes through the bridge at a constant speed, collecting vibration signals, location information and suspension status, and extracting the bridge fundamental frequency prediction value through FFT analysis; Dynamic tuning stage of damping parameters: This stage is based on the fixed-point principle of tuning, calculating the optimal frequency ratio and the optimal damping ratio, and adjusting the damping parameters; Secondary Passage Precision Measurement and Verification Stage: In this stage, the vehicle passes through the bridge again to collect high-precision data, calculate the frequency difference, and determine the frequency stability. Cyclic tuning and convergence determination stage: When the frequency change rate is greater than the threshold, the mobile measuring trolley starts a new round of tuning-measurement cycle until the requirements are met.

2. The mobile measuring trolley based on bridge frequency measurement and damping tuning according to claim 1, characterized in that: The mobile measuring trolley initiates a new round of tuning-measuring cycle, including: Before measurement, the basic parameters of the bridge are input into the on-board processor, and a bridge fundamental frequency prediction model is constructed according to the following formula: ； Where w(x, t) is the lateral displacement of the bridge, δ(x) is the Dirac delta function, and m=m s +m u It is the total mass of the vehicle, m u and m s Let x represent the lumped unsprung mass and the lumped sprung mass, respectively, and let x2(t) be the position of the contact point; for constant velocity, x c (t) = v t ;F d (t) represents the dynamic load on the bridge; EI represents the bending stiffness; After the vehicle's first measurement, the multimodal sensor array sends the signal to the onboard processor to obtain the bridge fundamental frequency prediction model and thus the bridge fundamental frequency prediction value. The on-board processor calculates the vehicle damping ratio based on the frequency estimate using the following formula and outputs the signal to the drive module. ； ； in: , It is the uncoupled natural frequency of the sprung mass. Where ω is the first-order frequency of the bridge, It is the uncoupled natural frequency of the unsprung mass. ,definition The ratio of the sprung mass to its unsprung mass is given by equation (3); the damping ratio is obtained by solving equation (3). ; The on-board processor receives the bridge frequency signal, and then calculates the optimal damping ratio and sends it to the damping adjustment unit. Before each measurement, the damping is tuned according to the bridge frequency signal obtained from the previous measurement. After each measurement, a more accurate bridge frequency and frequency change rate are obtained until the frequency change rate is less than the specified value. The onboard processor determines the bridge frequency change rate is less than a specified value and outputs the final bridge frequency. Damping ratio ζ b 。

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