Bridge foundation scouring detection method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention provides a bridge foundation scouring detection method and device, electronic equipment and a storage medium, and belongs to the field of bridge health detection. The method comprises the following steps: acquiring the vehicle acceleration of a target vehicle running on a target bridge at a constant speed; calculating a contact acceleration between the target vehicle and the target bridge according to the vehicle acceleration; calculating bridge frequency distribution of the target bridge according to the contact acceleration; performing modal separation on the bridge frequency distribution to obtain a bridge modal component; constructing a bridge modal shape according to the bridge modal component; and performing foundation scouring detection according to the bridge modal shape to obtain the damage area and the scouring degree of the target bridge. According to the embodiment of the invention, the adaptability of bridge foundation scouring detection in a complex environment can be improved.

Description

Technical Field

[0001] This application relates to the field of bridge health monitoring, and more particularly to a method, apparatus, electronic device, and storage medium for detecting bridge foundation scour. Background Technology

[0002] Scouring significantly weakens the foundation bearing capacity and structural stiffness of bridges, and is one of the main causes of bridge damage. Scouring detection can identify whether scouring occurs in bridge foundations, ensuring the stability and safety of bridges. Existing scouring detection technologies are mainly divided into two categories: direct detection and indirect inference. Direct detection methods typically rely on fixed sensors installed around the piers to measure changes in water or soil to obtain scouring depth information. Indirect inference methods rely on statically deployed sensors to detect changes in the vibration characteristics of the bridge structure and infer the impact of scouring on foundation stiffness and boundary conditions. However, both of these methods involve complex equipment deployment and high maintenance costs, limiting their application and widespread use in complex environments. Summary of the Invention

[0003] The main objective of this application is to provide a method, apparatus, electronic device, and storage medium for detecting bridge foundation scour, aiming to improve the adaptability of bridge foundation scour detection in complex environments.

[0004] To achieve the above objectives, a first aspect of this application proposes a method for detecting bridge foundation scour, the method comprising: Obtain the vehicle acceleration of the target vehicle traveling at a constant speed on the target bridge; Calculate the contact acceleration between the target vehicle and the target bridge based on the vehicle acceleration. The bridge frequency distribution of the target bridge is calculated based on the contact acceleration. Modal separation is performed on the bridge frequency distribution to obtain the bridge modal components; The bridge mode shape is constructed based on the bridge modal components; Based on the bridge's modal vibration patterns, foundation scour detection is performed to obtain the damaged area and scour degree of the target bridge.

[0005] In some embodiments, calculating the contact acceleration between the target vehicle and the target bridge based on the vehicle acceleration includes: Calculate the vertical acceleration and pitch acceleration of the target vehicle based on the vehicle acceleration. The equivalent axle load of the target vehicle is calculated based on the vertical acceleration and the pitch acceleration. Calculate the axle acceleration of the target vehicle based on the equivalent axle load; Calculate the equivalent wheel load of the target vehicle based on the vehicle acceleration and the axle acceleration; The contact acceleration is calculated based on the equivalent wheel load.

[0006] In some embodiments, the contact acceleration includes front wheel contact acceleration and rear wheel contact acceleration, and calculating the bridge frequency distribution of the target bridge based on the contact acceleration includes: Calculate the residual contact acceleration between the front wheel contact acceleration and the rear wheel contact acceleration; The residual contact acceleration is converted from the time domain to the frequency domain to obtain the bridge frequency distribution.

[0007] In some embodiments, the modal separation of the bridge frequency distribution to obtain bridge modal components includes: The bandpass filter bank is determined based on the bridge frequency distribution; The bridge frequency distribution is filtered by the bandpass filter bank to obtain the amplitude spectrum. The amplitude spectrum is converted from the frequency domain to the time domain to obtain the bridge modal components.

[0008] In some embodiments, determining the bandpass filter bank based on the bridge frequency distribution includes: Obtain the center frequency of the twin peaks in the bridge frequency distribution and the frequency interval between adjacent twin peaks; The passband frequency range is determined based on the center frequency and the frequency interval; The bandpass filter bank is determined based on the passband frequency range.

[0009] In some embodiments, constructing the bridge mode shape based on the bridge modal components includes: Obtain the orthogonal components of the bridge modal components; A complex analytical signal is constructed based on the bridge modal components and the orthogonal components; The complex analytic signal is transformed from the Cartesian coordinate system to the polar coordinate system to obtain the instantaneous amplitude of the target. The bridge mode shape is constructed based on the target instantaneous amplitude.

[0010] In some embodiments, the step of performing foundation scour detection based on the bridge's modal vibration modes to obtain the damage area and scour degree of the target bridge includes: Calculate the target mode curvature of the bridge's modal vibration modes; Obtain the reference mode shape of the healthy bridge and calculate the reference mode shape curvature of the reference mode shape; The difference between the target mode curvature and the reference mode curvature is calculated to obtain the mode curvature difference, and the damage area is determined based on the mode curvature difference. The root mean square difference of modal curvature between the bridge mode shape and the reference mode shape is calculated to obtain the degree of scouring.

[0011] To achieve the above objectives, a second aspect of this application provides a bridge foundation scour detection device, the device comprising: The acquisition module is used to acquire the vehicle acceleration of the target vehicle traveling at a constant speed on the target bridge; An acceleration calculation module is used to calculate the contact acceleration between the target vehicle and the target bridge based on the vehicle's acceleration. The bridge frequency calculation module is used to calculate the bridge frequency distribution of the target bridge based on the contact acceleration. The mode separation module is used to perform mode separation on the bridge frequency distribution to obtain the bridge mode components; A construction module is used to construct bridge mode shapes based on the bridge modal components; The detection module is used to perform foundation scour detection based on the bridge's modal vibration modes to obtain the damage area and scour degree of the target bridge.

[0012] To achieve the above objectives, a third aspect of the present application provides an electronic device, the electronic device including a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method described in the first aspect.

[0013] To achieve the above objectives, a fourth aspect of the present application provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method described in the first aspect.

[0014] The bridge foundation scour detection method, device, electronic equipment, and computer-readable storage medium proposed in this application acquire the vehicle acceleration of a target vehicle traveling at a constant speed on a target bridge, thus using vehicle acceleration as the basic data for bridge foundation scour detection. The contact acceleration between the target vehicle and the target bridge is calculated based on the vehicle acceleration, reflecting the impact of bridge surface roughness on the vehicle tires. By considering the interference of bridge surface roughness, a non-structural factor, the accuracy of scour detection is improved. The bridge frequency distribution of the target bridge is calculated based on the contact acceleration, determining the bridge's vibration characteristics at different frequencies, thereby identifying changes in bridge structural characteristics. Modal separation is performed on the bridge frequency distribution to obtain the components of interest, resulting in bridge modal components. Bridge modal shapes are constructed based on these components, reflecting the dynamic characteristics of the bridge structure, thus enabling bridge foundation scour detection. Based on the bridge modal shapes, the damaged areas and scour levels of the target bridge are determined, enabling the identification of the location and severity of scour damage, and improving the adaptability of bridge foundation scour detection in complex environments. Attached Figure Description

[0015] Figure 1 This is a flowchart of the bridge foundation scour detection method provided in the embodiments of this application; Figure 2 yes Figure 1 The flowchart of step S120 in the middle; Figure 3 yes Figure 1 The flowchart of step S130 in the process; Figure 4 yes Figure 1 The flowchart of step S140 in the middle; Figure 5 yes Figure 4 The flowchart of step S410 in the middle; Figure 6 yes Figure 1 The flowchart of step S150 in the middle; Figure 7 yes Figure 1 The flowchart of step S160 in the process; Figure 8 This is a schematic diagram of the bridge and vehicle model provided in the embodiments of this application; Figure 9 This application provides finite element simulation and calculation of the front wheel acceleration response in its embodiments. Figure 10 This is the rear wheel acceleration response simulated and calculated using finite element methods as described in the embodiments of this application; Figure 11 This is the residual contact point response provided in the embodiments of this application; Figure 12 These are the first-order modal components and first-order mode shapes provided in the embodiments of this application; Figure 13 These are the first-order mode shapes under different scouring levels provided in the embodiments of this application; Figure 14 These are the DMSC values ​​calculated under different scouring levels provided in the embodiments of this application; Figure 15 These are the RMS values ​​of the mode shapes under healthy conditions and different scour levels provided in the embodiments of this application; Figure 16 These are the first-order modes of the bridge under different scour levels provided in the embodiments of this application; Figure 17 These are the DMSC values ​​under different scouring levels provided in the embodiments of this application; Figure 18 These are the RMS values ​​of the modal shapes under different scouring levels provided in the embodiments of this application; Figure 19 This is a schematic diagram of the structure of the bridge foundation scour detection device provided in the embodiments of this application; Figure 20 This is a schematic diagram of the hardware structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0016] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0017] It should be noted that although functional modules are divided in the device schematic diagram and a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device or the order in the flowchart. The terms "first," "second," etc., in the specification, claims, and the aforementioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence.

[0018] Unless otherwise defined, 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 application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0019] As crucial transportation infrastructure, bridges typically face the risk of safety performance degradation during long-term service, especially in areas with piers located in water, where foundation scour is frequent and can lead to structural instability or even collapse in severe cases. Scour significantly weakens the foundation bearing capacity and structural stiffness of bridges, and a large number of bridge collapses are closely related to scour, making it one of the main causes of bridge damage. Scour is characterized by its suddenness and difficulty in early warning. Therefore, early detection of scour loss is of great importance to ensuring the safe operation of bridges.

[0020] Existing scour detection technologies are mainly divided into two categories: direct detection and indirect inference. Direct detection methods typically rely on fixed sensors installed around bridge piers, such as time-domain reflectometers, fiber optic sensors, or imaging sonar, to measure changes in water or soil to obtain scour depth information. Although this type of method offers high measurement accuracy, its equipment deployment is complex, maintenance costs are high, and it is susceptible to floods or sediment, limiting its application and widespread adoption in complex environments.

[0021] Scouring can cause a decrease in the natural frequencies of pile foundations and changes in the mode shapes of bridges. Therefore, numerous indirect scouring identification methods based on structural response have emerged. These methods infer the impact of scouring on foundation stiffness and boundary conditions by detecting changes in the vibration characteristics of the bridge structure, such as natural frequencies, damping ratios, and mode shapes. However, these methods rely on a large number of statically deployed sensors, which are not only costly and inefficient but also limited in application in dynamic traffic environments.

[0022] Based on this, embodiments of this application provide a method, device, electronic equipment, and computer-readable storage medium for detecting bridge foundation scour, aiming to improve the adaptability of bridge foundation scour detection in complex environments.

[0023] The bridge foundation scour detection method, bridge foundation scour detection device, electronic device, and computer-readable storage medium provided in this application are specifically described through the following embodiments. First, the bridge foundation scour detection method in this application embodiment is described.

[0024] The bridge foundation scour detection method provided in this application relates to the field of bridge health monitoring. This method can be applied to a terminal, a server, or software running on either a terminal or a server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, etc.; the server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms; the software can be an application implementing the bridge foundation scour detection method, but is not limited to the above forms.

[0025] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0026] Figure 1 This is an optional flowchart of the bridge foundation scour detection method provided in the embodiments of this application. Figure 1 The method may include, but is not limited to, steps S110 to S160.

[0027] Step S110: Obtain the vehicle acceleration of the target vehicle traveling at a constant speed on the target bridge; Step S120: Calculate the contact acceleration between the target vehicle and the target bridge based on the vehicle acceleration; Step S130: Calculate the bridge frequency distribution of the target bridge based on the contact acceleration; Step S140: Perform mode separation on the bridge frequency distribution to obtain the bridge mode components; Step S150: Construct bridge mode shapes based on bridge modal components; Step S160: Conduct foundation scour detection based on bridge modal vibration to obtain the damage area and scour degree of the target bridge.

[0028] In step S110 of some embodiments, bridge scour detection is performed based on the response of a moving vehicle. The target vehicle is a dual-axle test vehicle, and the target bridge is the bridge to be tested for foundation scour. Accelerometers are deployed directly above the front and rear axles of the target vehicle. The acceleration data in the vertical direction of the target vehicle as it passes the target bridge at a constant speed is collected in real time by these accelerometers to obtain the vehicle acceleration. The vehicle acceleration includes the front axle acceleration collected by the accelerometer on the front axle and the rear axle acceleration collected by the accelerometer on the rear axle. The acceleration data collection period should cover the entire process from the front (rear) axle entering the target bridge to the front (rear) axle completely leaving the bridge, and the collection period includes multiple sampling time steps. Unlike traditional detection methods that rely on underwater sensors or statically deployed devices, this embodiment uses the vehicle itself as a mobile measurement platform, deploying accelerometers on the front and rear axles. This allows for flexible equipment deployment, rather than fixed sensors on the bridge, reducing the complexity of equipment deployment and maintenance costs. Furthermore, the equipment deployment does not require underwater operations, avoiding complex under-bridge installation and environmental interference, and improving the efficiency and accessibility of scour detection.

[0029] Please see Figure 2 In some embodiments, step S120 may include, but is not limited to, steps S210 to S250: Step S210: Calculate the vertical acceleration and pitch acceleration of the target vehicle based on the vehicle acceleration. Step S220: Calculate the equivalent axle load of the target vehicle based on the vertical acceleration and pitch acceleration; Step S230: Calculate the axle acceleration of the target vehicle based on the equivalent axle load; Step S240: Calculate the equivalent wheel load of the target vehicle based on the vehicle acceleration and axle acceleration; Step S250: Calculate the contact acceleration based on the equivalent wheel load.

[0030] In step S210 of some embodiments, the distance between the center of gravity of the target vehicle and the front axle is obtained to obtain a first distance. The distance between the center of gravity of the target vehicle and the rear axle is obtained to obtain a second distance. The sum of the first and second distances is calculated to obtain a distance sum, which is the distance between the front and rear axles. Based on the collected front axle vehicle acceleration, rear axle vehicle acceleration, first distance, second distance, and distance sum, the vertical acceleration of the target vehicle is calculated. Vertical acceleration is the acceleration of the vehicle body in the vertical direction, reflecting the rate of change of the target vehicle's velocity in the vertical direction. When the target vehicle travels on the target bridge, it will experience vertical motion due to the undulations of the bridge surface; the velocity change of this motion is the vertical acceleration. The formula for calculating vertical acceleration is expressed as: , , in, Indicates the sampling time step; Indicates vertical acceleration; Indicates the acceleration of the vehicle on the front axle; Indicates the distance between the vehicle's center of gravity and the front axle; Indicates the acceleration of the vehicle on the rear axle; This indicates the distance between the vehicle's center of gravity and the rear axle; Indicates the distance between the front and rear axles; Indicates displacement; The superscript is a dot symbol, indicating the sampling time step. The second derivative of .

[0031] Based on the collected front axle vehicle acceleration, rear axle vehicle acceleration, and distance values, the pitch acceleration of the target vehicle is calculated. Pitch acceleration is the angular acceleration of the target vehicle rotating about its left and right lateral axes. The formula for calculating pitch acceleration is: , in, It represents pitch acceleration.

[0032] In step S220 of some embodiments, the equivalent axle load refers to the number of repetitions of converting vehicle axle loads with different configurations into standard axle loads using a certain equivalence factor. The equivalent axle load includes the equivalent front axle load and the equivalent rear axle load. The vehicle body mass and moment of inertia of the target vehicle are obtained. The vehicle body mass is the weight of the target vehicle, and the moment of inertia reflects the magnitude of the inertia when the vehicle body rotates around a certain axis (such as the lateral axis or the vertical axis). The target vehicle has front tires and rear tires, both equipped with suspension units. The linear stiffness and viscous damping coefficient of the suspension units of the front and rear tires are obtained. The linear stiffness is the force required for the target vehicle to deform per unit area within its elastic range, and the viscous damping coefficient is the damping force required for the target vehicle to move per unit speed. The equivalent front axle load of the target vehicle is calculated based on the distances between the vehicle's center of gravity and the front axle, the distances between the vehicle's center of gravity and the rear axle, the distances between the front and rear axles, the vehicle's mass, moment of inertia, vertical acceleration, pitch acceleration, and the linear stiffness and viscous damping coefficient of the front tire suspension unit. The formula for calculating the equivalent front axle load is as follows: , in, This is the equivalent front axle load; Indicates the vehicle's mass; Indicates the moment of inertia of the vehicle body; This indicates the linear stiffness of the front tire suspension unit; This represents the viscous damping coefficient of the front tire suspension unit; Indicates time The first derivative; Indicates time The second derivative of .

[0033] The equivalent rear axle load of the target vehicle is calculated based on the distances between the vehicle's center of gravity and the front axle, the distances between the vehicle's center of gravity and the rear axle, the distance between the front and rear axles, the vehicle's mass, moment of inertia, vertical acceleration, pitch acceleration, and the linear stiffness and viscous damping coefficient of the rear tire suspension unit. The formula for calculating the equivalent rear axle load is as follows: , in, This is the equivalent rear axle load.

[0034] In step S230 of some embodiments, the axle acceleration includes front axle acceleration and rear axle acceleration. The front axle acceleration for the current sampling time step is obtained by integrating the linear stiffness and viscous damping coefficient of the front tire suspension unit with the equivalent front axle load for each sampling time step from the first sampling time step to the current sampling time step. The rear axle acceleration for the current sampling time step is obtained by integrating the linear stiffness and viscous damping coefficient of the rear tire suspension unit with the equivalent rear axle load for each sampling time step from the first sampling time step to the current sampling time step. The front and rear axle accelerations are responses to the acceleration data collected by the sensors, and the calculation formulas for the front and rear axle accelerations are expressed as follows: , in, It is the axial acceleration; It can be or , and They represent before and after, respectively. This represents the linear stiffness of the suspension unit; This represents the viscous damping coefficient of the suspension unit; For integration variables; This is the current sampling time step; , These represent the equivalent front axle load and the equivalent rear axle load, respectively. , These represent the vertical displacements of the front and rear axles, respectively. Displacement versus time The second derivative of .

[0035] In step S240 of some embodiments, the equivalent wheel load refers to the uniformly distributed pressure calculated based on the tire-to-ground contact area, where the total axle weight of the vehicle is distributed to each wheel. It reflects the actual force exerted by the wheels on the road surface. The equivalent wheel load includes the equivalent front wheel load and the equivalent rear wheel load. The linear stiffness and viscous damping coefficients of the front and rear tires, as well as the axle masses of the front and rear axles, are obtained. The equivalent front wheel load is calculated based on the linear stiffness and viscous damping coefficients of the front wheels, the linear stiffness and viscous damping coefficients of the front suspension units, the axle mass of the front axle, the front axle acceleration, and the front axle vehicle acceleration. The equivalent rear wheel load is calculated based on the linear stiffness and viscous damping coefficients of the rear wheels, the linear stiffness and viscous damping coefficients of the rear suspension units, the axle mass of the rear axle, the rear axle acceleration, and the rear axle vehicle acceleration. The formula for calculating the equivalent wheel load is expressed as: , in, Indicates the equivalent wheel load; It can be or , and They represent before and after, respectively. , These represent the axle masses of the front and rear axles, respectively. Indicates axial acceleration; and These represent the linear stiffness and viscous damping coefficient of the tire, respectively. and These represent the linear stiffness and viscous damping coefficient of the suspension unit, respectively. This indicates the vehicle's acceleration.

[0036] In step S250 of some embodiments, an integral calculation is performed based on the tire's linear stiffness and viscous damping coefficient, and the equivalent wheel load at each sampling time step from the first sampling time step to the current sampling time step, to obtain the contact point response between the tire and the ground, thus obtaining the contact acceleration between the target vehicle and the target bridge. The contact acceleration includes the front wheel contact acceleration and the rear wheel contact acceleration. The calculation formulas for the front and rear wheel contact accelerations are expressed as follows: , in, Indicates contact acceleration. Indicates the front wheel contact acceleration. Indicates the contact acceleration of the rear wheel; and These represent the linear stiffness and viscous damping coefficient of the tire, respectively. Indicates the equivalent wheel load; It is the integral variable.

[0037] There is a certain distance between the front and rear axles of the target vehicle. When the rear wheels reach the same position as the front wheels did previously, there will be a time delay. If the time it takes for the front wheels to reach a certain position is... Then the time it takes for the rear wheels to reach that position is , For the duration of the delay, , This is the distance between the front and rear axles. Let be the speed of the target vehicle. The rear wheel acceleration can be re-expressed as: , in, This indicates the contact acceleration of the rear wheel.

[0038] It should be noted that the equivalent wheel load only involves the vehicle body response, the inversely calculated axle response, and mechanical characteristics, and does not involve the bridge response. Therefore, the method for calculating the contact response is applicable to all types of bridges.

[0039] Steps S210 to S250 above involve calculating the contact point responses between the front and rear wheels and the ground based on the measured vehicle response, in order to determine the vibration response generated by the vehicle during the passage of the bridge based on the contact point responses, and then conducting foundation scour detection.

[0040] Please see Figure 3 In some embodiments, step S130 may include, but is not limited to, steps S310 to S320: Step S310: Calculate the residual contact acceleration between the front wheel contact acceleration and the rear wheel contact acceleration; Step S320: Convert the residual contact acceleration from the time domain to the frequency domain to obtain the bridge frequency distribution.

[0041] In step S310 of some embodiments, once the contact accelerations of the front and rear wheels are obtained, the contact acceleration of the front wheel is subtracted from the contact acceleration of the rear wheel to obtain the residual contact acceleration. The formula for calculating the residual contact acceleration is expressed as: , in, This refers to residual contact acceleration; It is an impulse response. .

[0042] The impulse response is expressed as: , in, It is a unit step function.

[0043] In step S320 of some embodiments, a Fast Fourier Transform is performed on the residual contact acceleration to transform it from the time domain to the frequency domain, obtaining the bridge frequency distribution. The bridge frequency distribution is expressed as: , in, Indicates bridge frequency distribution; Represents the imaginary unit; Indicates angular frequency; This represents the integral variable.

[0044] Through the above steps S310 to S320, the bridge frequency distribution can be obtained, so as to reflect the frequency characteristics of bridge vibration based on the bridge frequency distribution.

[0045] Please see Figure 4 In some embodiments, step S140 may include, but is not limited to, steps S410 to S430: Step S410: Determine the bandpass filter bank based on the bridge frequency distribution; Step S420: The bridge frequency distribution is filtered by a bandpass filter bank to obtain the amplitude spectrum; Step S430: Convert the amplitude spectrum from the frequency domain to the time domain to obtain the bridge modal components.

[0046] In step S410 of some embodiments, a bandpass filter bank is designed based on the bridge frequency distribution in order to automatically separate the bridge component of interest from the bridge frequency distribution.

[0047] In step S420 of some embodiments, a bandpass filter bank is applied to the bridge frequency distribution for filtering to obtain the amplitude spectrum. The amplitude spectrum is represented as: , in, Indicates the amplitude spectrum; Indicates bridge frequency distribution; This indicates a bandpass filter bank.

[0048] In step S430 of some embodiments, an inverse Fourier transform is performed on the amplitude spectrum to convert it from the frequency domain to the time domain, obtaining the bridge modal components. The formula for the inverse Fourier transform is defined as follows: , in, Represents the bridge modal components; Indicates the amplitude spectrum; Indicates angular frequency; Represents a time variable.

[0049] Through the above steps S410 to S430, the bridge component of interest can be automatically separated from the bridge frequency distribution, thereby avoiding the influence of irrelevant interference on the detection results and improving the accuracy of foundation scour detection.

[0050] Please see Figure 5 In some embodiments, step S410 may include, but is not limited to, steps S510 to S530: Step S510: Obtain the center frequency of the double peaks in the bridge frequency distribution and the frequency interval between adjacent double peaks; Step S520: Determine the passband frequency range based on the center frequency and frequency interval; Step S530: Determine the bandpass filter bank based on the passband frequency range.

[0051] In step S510 of some embodiments, both the contact acceleration and the residual contact acceleration include the bridge vibration frequency. Each bridge frequency appears in pairs with left-biased and right-biased frequencies, meaning each bridge frequency component exhibits a double peak in the spectrum. Since the bridge vibration frequency is unknown beforehand, a fast Fourier transform reveals multiple double peaks in the residual contact point response spectrum, i.e., the bridge frequency distribution. The center frequency of these double peaks is... The frequency interval between adjacent double peaks is , This is the index value of the bimodal peak. The target vehicle's speed. The length of a single span of the target bridge.

[0052] In step S520 of some embodiments, in order to separate the modal components corresponding to the bimodals, the frequency interval can be repeatedly selected as... The bimodal frequency range is used as the passband frequency range to examine all response spectra, thereby determining the bridge vibration frequency. The passband frequency range is the range of frequencies that the signal is allowed to pass through, expressed as: , in, Indicates the center frequency of the double peaks; Indicates frequency interval.

[0053] In step S530 of some embodiments, in order to maintain the original phase characteristics of the signal, a zero-phase filtering technique is used. The amplitude corresponding to the double-peak frequency within the passband frequency range is set to 1, and the amplitude corresponding to the frequency outside the passband frequency range is set to 0, thus obtaining the ideal frequency response function. The bandpass filter bank is then determined based on the ideal frequency response function. The ideal frequency response function is expressed as: , in, Represents the ideal frequency response function; Indicates frequency.

[0054] Through the above steps S510 to S530, a bandpass filter can be obtained to separate the bridge mode components of interest.

[0055] Please see Figure 6 In some embodiments, step 150 may include, but is not limited to, steps S610 to S640: Step S610: Obtain the orthogonal components of the bridge modal components; Step S620: Construct a complex analytic signal based on the bridge modal components and orthogonal components; Step S630: Transform the complex analytical signal from the Cartesian coordinate system to the polar coordinate system to obtain the instantaneous amplitude of the target; Step S640: Construct the bridge mode shape based on the target instantaneous amplitude.

[0056] In step S610 of some embodiments, the bridge modal components are subjected to a Hilbert transform using the Hilbert transform operator to obtain the orthogonal components of the bridge modal components. The Hilbert transform is expressed as: , in, H represents the bridge modal components; H is the Hilbert transform operator. PV represents the orthogonal component of the bridge modal components; PV is the Cauchy principal value.

[0057] In step S620 of some embodiments, the bridge modal components and their orthogonal components constitute a transform pair, and a complex analytic signal is constructed based on this transform pair. The complex analytic signal is represented as: , in, It is a complex analytic signal; Represents the imaginary unit; and These represent the bridge's modal components and their orthogonal components, respectively.

[0058] In step S630 of some embodiments, the complex analytic signal is transformed from Cartesian coordinates to polar coordinates, thereby representing the complex analytic signal in the form of amplitude and phase angle, obtaining the instantaneous amplitude and instantaneous phase, and using the instantaneous amplitude as the target instantaneous amplitude. The complex analytic signal in polar coordinates is represented as: , in, Indicates instantaneous amplitude; Represents the imaginary unit; Indicates the instantaneous phase.

[0059] The instantaneous amplitude and instantaneous phase are expressed as follows: , , Here, arctan represents the arctangent function.

[0060] In step S640 of some embodiments, the spectrum of the bridge modal components is concentrated in a narrow frequency range, which is a narrowband signal. Based on the characteristics of narrowband signals, the instantaneous amplitude can be regarded as the envelope function of the bridge modal components. The change of this amplitude with the bridge length can be used as the mode shape of the bridge, and the instantaneous amplitude has physical meaning. The mode shape is extracted from the target instantaneous amplitude, and the sign of the mode shape is determined to obtain the bridge mode shape, which can reflect the dynamic characteristics of the bridge structure.

[0061] A reference point can be set on the target bridge to calculate the displacement of a certain position reached by the target vehicle relative to the reference point. If the displacement at a certain position is in the same direction as the reference point, the sign of the mode shape is determined to be positive; if it is in the opposite direction, the sign is negative.

[0062] Existing technologies typically fragment the vehicle response into short-time responses when constructing mode shapes, making it difficult to accurately obtain the high spatial resolution features of the mode shapes. This application's embodiments construct mode shapes using high-resolution data collected in real-time by motion sensors. Utilizing the dynamic coupling relationship between the vehicle and the bridge, and combining signal processing techniques such as frequency domain analysis, bandpass filtering, and Hilbert transform, the bridge mode shapes are extracted. This preserves the response throughout the entire process of vehicle passage across the bridge and accurately obtains the high spatial resolution features of the mode shapes, thereby identifying changes in bridge structural characteristics and ultimately determining the severity and location of bridge foundation scour.

[0063] Steps S610 to S640 described above indirectly extract bridge modal information by measuring the vibration response generated by vehicles during bridge passage, thereby reflecting the structural change characteristics of the bridge. This method has advantages such as no need for underwater operations, no need to interrupt traffic, suitability for rapid detection, and wide coverage.

[0064] Please see Figure 7 In some embodiments, step S160 may include, but is not limited to, steps S710 to S740: Step S710: Calculate the target mode curvature of the bridge's modal vibration modes; Step S720: Obtain the reference mode shape of the healthy bridge and calculate the reference mode curvature; Step S730: Calculate the difference between the target mode curvature and the reference mode curvature to obtain the mode curvature difference value, and determine the damage area based on the mode curvature difference value; Step S740: Calculate the root mean square difference of modal curvature between the bridge mode shape and the reference mode shape to obtain the degree of scour.

[0065] In step S710 of some embodiments, the first mode in the modal vibration pattern is sensitive to changes in the central pier of a two-span continuous bridge. In a two-span bridge with flexible supports, the central pier is the main vertical support, so changes in its foundation conditions (such as scour) will lead to changes in the modal vibration patterns of the entire bridge. The modal vibration pattern curvature difference is highly sensitive to local structural damage, much more sensitive to damage than the modal vibration pattern itself. In the presence of foundation scour, the modal vibration pattern curvature difference usually shows a significant peak at the damage location, thus serving as an effective indicator for identifying the damage location. By calculating the curvature difference, the location and approximate distribution of damage can be analyzed, thereby locating the damage area. To calculate the modal vibration pattern curvature difference, it is necessary to calculate the modal vibration pattern curvature of the bridge modal vibration pattern to obtain the target mode curvature. The modal vibration pattern curvature is the second derivative of the modal vibration pattern with respect to spatial coordinates, estimated using the central difference formula as follows: , in, Indicates the sampling time, i.e., the sampling time step; Indicates the sampling interval; For normalized mode shapes, i.e. Instantaneous amplitude at time 10:00 .

[0066] In step S720 of some embodiments, a healthy bridge refers to a bridge without any damage. Referring to steps S110 to S150, the modal shapes of the healthy bridge are constructed to obtain reference modal shapes. The modal curvature of the reference modal shapes is then calculated using the formula described above to obtain the reference mode curvature.

[0067] In step S730 of some embodiments, the absolute value of the difference between the target mode shape curvature and the reference mode shape curvature is calculated to obtain the mode shape curvature difference. The formula for calculating the mode shape curvature difference is expressed as: , in, Indicates the sampling time The corresponding difference in mode shape curvature; Reference mode curvature representing the reference mode shape of a healthy bridge; The target mode curvature represents the bridge mode shape of the target bridge.

[0068] A curvature difference threshold can be set. If the modal curvature difference is greater than or equal to the threshold, it indicates that the modal curvature difference between the target bridge and the healthy bridge is too large, and the target bridge has scour damage. In this case, the current sampling time step is multiplied by the target vehicle's speed to obtain the target vehicle's current distance traveled on the target bridge. Based on this distance, the current location of the target vehicle is determined, thus identifying the damaged area. If the modal curvature difference is less than the threshold, it indicates that the target vehicle's current location is not within the damaged area.

[0069] Alternatively, the sampling time step with the largest difference in modal curvature can be obtained to get the target time step. The target time step is then multiplied by the speed of the target vehicle to determine the damage area.

[0070] In step S740 of some embodiments, to quantify the degree of scour, a root mean square difference (RMSD) of modal curvature is introduced. The RMSD represents the difference between the modal modes of a healthy bridge and those of a damaged bridge. The RMSD between the bridge's modal modes and a reference modal mode is calculated to determine the degree of scour on the target bridge. The formula for calculating the RMSD is as follows: , Wherein, RMS is the root mean square difference of modal curvature; This represents the total number of mode points, i.e., the number of sampling time steps; The reference mode shape representing a healthy bridge; This represents the bridge mode shape of the target bridge.

[0071] The relationship between RMS and the percentage reduction in foundation stiffness is clearly non-linear, directly reflecting the structural damage trend caused by scour. It is a more useful indicator than the actual size of the scour pit. The larger the RMS value, the more severe the scour damage.

[0072] Steps S710 to S740, through modal vibration and curvature changes, can accurately locate scour-damaged elements and achieve sensitive detection of foundation stiffness changes, possessing high spatial resolution modal recognition capabilities. By introducing modal curvature difference and root mean square difference of modal curvature to quantify foundation stiffness changes, the degree of structural damage can be judged, achieving a quantifiable assessment of the severity of scour.

[0073] This application provides a low-cost, high-efficiency, high-precision, and highly anti-interference method for detecting bridge foundation scour, overcoming the problems of complex sensor deployment, poor real-time performance, weak anti-interference capabilities, and limited recognition accuracy in existing scour detection technologies. It balances accuracy, robustness, and practicality, achieving efficient and rapid identification and early warning of bridge scour conditions. This method is applicable to different bridge surface roughness, scour conditions, and vehicle parameters, possessing good anti-interference capabilities and promising engineering applications. It is robust and widely applicable. Employing frequency domain filtering and time domain envelope techniques, it achieves rapid modal reconstruction and state recognition, making it suitable for online inspections and post-disaster emergency detection. It is particularly suitable for intelligent detection and early warning of bridges in remote areas, after floods, and in operation.

[0074] The bridge foundation scour detection method according to an embodiment of this application will be demonstrated below. Consider a two-span bridge (modeled as a beam) and a test vehicle (modeled as a four-degree-of-freedom sprung mass), such as... Figure 8 As shown in Table 1, the property parameters of the bridge and vehicle are as follows. The vehicle's sway frequency and vertical vibration frequency are 0.58 Hz and 10.33 Hz, respectively, and the vibration frequencies of the front and rear wheels are 0.58 Hz and 10.33 Hz, respectively. The first natural frequency of the bridge is 3.86 Hz. The vehicle crosses the bridge at a typical highway speed, v = 5 m / s, and the acceleration data of the front and rear sensors are recorded during the crossing. and The embodiments in this application consider three types of scour failure, corresponding to a reduction in pier foundation stiffness of 10%, 20%, and 45%, respectively.

[0075] Table 1

[0076] The front wheel acceleration response was obtained through finite element method (FEM) simulation and calculation formula based on front wheel contact acceleration. The front wheel acceleration response is as follows: Figure 9 As shown. The front wheel acceleration response includes the time history response (time domain result) and the frequency response (frequency domain result). The time history response describes the variation of the front wheel contact acceleration over time. The time history curve of the time history response is shown in the figure. Figure 9 As shown in (a), the frequency response is the response obtained by transforming the time history response from the time domain to the frequency domain. The spectrum of the frequency response is shown in [image missing]. Figure 9 As shown in (b). Figure 9 In (a), the dashed line represents the front wheel contact acceleration calculated using the vehicle response, based on the formula. The solid line represents the result calculated directly through finite element simulation. Similarly, the corresponding spectrum is shown in... Figure 9 (b) shows a high degree of agreement between the estimation results from the two methods, indicating the accuracy of the wheel response calculation. Similarly, the rear wheel acceleration response was obtained through finite element simulation and calculation based on the rear wheel contact acceleration formula, as follows: Figure 10 As shown. The time history response and frequency response of the rear wheel acceleration response are respectively as follows. Figure 10 As shown in (a) and 10(b).

[0077] The residual contact response (residual contact acceleration) is represented by the difference between the front wheel contact point response (front wheel contact acceleration) and the rear wheel contact point response (rear wheel contact acceleration). The residual contact response is as follows: Figure 11 As shown in (a), the spectrum of the residual response at the contact point is as follows: Figure 11 As shown in (b). From Figure 11 In (b), three sharp peaks can be easily observed, corresponding to the first three natural frequencies of the bridge. Once the frequency distribution of the bridge is determined, bandpass filtering can be used to separate the vibration components of interest from the residual contact point response. Taking the first vibration mode of the bridge as an example, the first modal components of the bridge are obtained through a bandpass filter, such as... Figure 12 As shown in (a), the Hilbert transform technique is applied to the filtered signal to reconstruct the bridge's mode shape, generating the instantaneous amplitude of the first-order vibration mode, thus obtaining the first-order mode shape, as shown in (a). Figure 12 As shown in (b), the normalized mode shape is very close to the FME estimation result, and the Modal Assurance Criterion (MAC) value between the two is 0.998. This indicates that the mode shape identification method of the present application embodiment is feasible and provides a basis for pier scour detection based on mode shape.

[0078] To demonstrate the repeatability of the bridge foundation scour testing process, vehicle mass and speed were varied, and nine representative sets of vehicle operating data were used to reconstruct the mode shapes of healthy and damaged states. Specifically, three different vehicle masses were used: =1000 kg, 900 kg and 800 kg, and three different speeds: =5 m / s, 4 m / s, and 2 m / s. The mode identification method of this application is used to identify the mode modes of the bridge under healthy conditions and under three scour conditions: 10%, 20%, and 45%.

[0079] Figure 13 The first-order mode shapes are shown for both health and scour conditions. The shaded area for each mode shape represents the region within the mean ± one standard deviation of the mode shape at each location. Based on nine vehicle passes under each scour condition, it can be observed that the loss of pier foundation stiffness reduces the mode shape amplitude at these points, altering the overall shape of the first-order mode shape. In each condition, the largest change in peak value occurs at the location of the scourted pier, and the change in peak value is greater with increasing scour-related foundation stiffness loss. This indicates that the rapid bridge scour detection method of this application performs well and is unaffected by vehicle characteristics and speed variations.

[0080] Figure 14 The distribution of DMSC values ​​at three scour levels (10%, 20%, and 45%) is shown. In the scour area, the DMSC curves all show significant peaks, especially near the central pier, accurately locating the scour site and verifying the effectiveness of this embodiment in locating bridge scour damage.

[0081] Figure 15 The root mean square (RMS) differences between the healthy mode shapes extracted based on eigenvalue analysis and the nine estimated mode shapes at each scour level are presented. Specifically, the RMS differences are presented as the mean, and the standard deviation is used to show the variation in the analysis. The results show a significant nonlinear relationship between the RMS and the percentage stiffness reduction. Based on these observations, an exponential function was used to fit the nonlinear relationship between the RMS and the stiffness reduction level, and the fitting results are shown below. Figure 15 As shown.

[0082] The scour identification capability of this application embodiment was verified under bridge surface roughness levels B and C. The bridge surface roughness at level C is higher than that at level B. The identification results are as follows: Figure 16 As shown. The identification results for grade B roughness are as follows. Figure 16 As shown in (a), the identification results of C-level roughness are as follows: Figure 16As shown in (b). Overall, under different roughness conditions, the modal shapes identified by the proposed method are highly consistent with the FEM simulation values. The MAC values ​​for healthy and three erosion states under roughness level B are 0.9822, 0.9954, 0.9945, and 0.9851, respectively, while those under roughness level C are 0.9812, 0.9770, 0.9930, and 0.9682, respectively. The identification accuracy decreases slightly with increasing roughness level, but the overall performance remains stable and reliable. Figure 17 The distribution of mode shape curvature difference (DMSC) under different roughnesses is further illustrated. The DMSC value for grade B roughness is shown below. Figure 17 As shown in (a), the DMSC value for roughness grade C is as follows: Figure 17 As shown in (b), the DMSC curves all show obvious peaks in the scour area, especially near the central pier, which can accurately locate the scour position. Figure 18 The root mean square difference (RMS) of modal curvature under healthy and various scour conditions was quantitatively analyzed. The results show that the RMS value increases significantly with increasing scour intensity, exhibiting a nonlinear relationship and reflecting a trend of structural stiffness loss. Although there are some fluctuations under Grade C roughness, the overall identification trend remains clear and is within a certain range. Figure 15 The fitted curves are within the 95% confidence range, indicating that the proposed method has good robustness and adaptability under different working conditions.

[0083] Please see Figure 19 This application also provides a bridge foundation scour detection device, which can implement the above-mentioned bridge foundation scour detection method. The bridge foundation scour detection device includes: The acquisition module 1910 is used to acquire the vehicle acceleration of the target vehicle traveling at a constant speed on the target bridge; Acceleration calculation module 1920 is used to calculate the contact acceleration between the target vehicle and the target bridge based on the vehicle's acceleration. Bridge frequency calculation module 1930 is used to calculate the bridge frequency distribution of the target bridge based on contact acceleration; The mode separation module 1940 is used to perform mode separation on the bridge frequency distribution to obtain the bridge mode components; Module 1950 is used to construct bridge mode shapes based on bridge modal components; The detection module 1960 is used to detect foundation scour based on the bridge's modal vibration patterns, thereby obtaining the damaged area and degree of scour of the target bridge.

[0084] The specific implementation method of the bridge foundation scour detection device is basically the same as the specific implementation method of the bridge foundation scour detection method described above, and will not be repeated here.

[0085] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described bridge foundation scour detection method. This electronic device can be any smart terminal, including tablet computers, in-vehicle computers, etc.

[0086] Please see Figure 20 , Figure 20 The hardware structure of an electronic device according to another embodiment is illustrated. The electronic device includes: The processor 2010 can be implemented using a general-purpose central processing unit (CPU), microprocessor, application specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application. The memory 2020 can be implemented in the form of read-only memory (ROM), static storage device, dynamic storage device, or random access memory (RAM). The memory 2020 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 2020 and is called and executed by the processor 2010 to execute the bridge foundation scour detection method of the embodiments of this application. Input / output interface 2030 is used to implement information input and output; The communication interface 2040 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.). Bus 2050 transmits information between various components of the device (e.g., processor 2010, memory 2020, input / output interface 2030, and communication interface 2040); The processor 2010, memory 2020, input / output interface 2030 and communication interface 2040 are connected to each other within the device via bus 2050.

[0087] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described bridge foundation scour detection method.

[0088] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0089] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0090] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0091] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0092] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0093] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0094] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0095] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0096] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0097] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0098] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0099] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A method of scour detection for a bridge foundation, the method comprising: The method comprises: obtaining vehicle acceleration of a target vehicle uniformly driving on a target bridge; calculating contact acceleration between the target vehicle and the target bridge according to the vehicle acceleration; calculating bridge frequency distribution of the target bridge according to the contact acceleration; modal separation is performed on the bridge frequency distribution to obtain bridge modal components; bridge modal shapes are constructed according to the bridge modal components; basic scour detection is performed according to the bridge modal shapes to obtain damage area and scour degree of the target bridge.

2. The method of claim 1, wherein, The calculation of the contact acceleration between the target vehicle and the target bridge according to the vehicle acceleration comprises: calculating vertical acceleration and pitching acceleration of the target vehicle according to the vehicle acceleration; calculating equivalent axle load of the target vehicle according to the vertical acceleration and the pitching acceleration; calculating axle acceleration of the target vehicle according to the equivalent axle load; calculating equivalent wheel load of the target vehicle according to the vehicle acceleration and the axle acceleration; calculating the contact acceleration according to the equivalent wheel load.

3. The method of claim 1, wherein, The contact acceleration comprises front wheel contact acceleration and rear wheel contact acceleration, and the calculation of the bridge frequency distribution of the target bridge according to the contact acceleration comprises: calculating residual contact acceleration between the front wheel contact acceleration and the rear wheel contact acceleration; converting the residual contact acceleration from time domain to frequency domain to obtain the bridge frequency distribution.

4. The method of claim 1, wherein, The modal separation of the bridge frequency distribution to obtain the bridge modal components comprises: determining a band-pass filter set according to the bridge frequency distribution; filtering the bridge frequency distribution through the band-pass filter set to obtain an amplitude spectrum; converting the amplitude spectrum from frequency domain to time domain to obtain the bridge modal components.

5. The method of claim 4, wherein, The determination of the band-pass filter set according to the bridge frequency distribution comprises: obtaining center frequencies of double peaks in the bridge frequency distribution and frequency intervals between adjacent double peaks; determining passband frequency ranges according to the center frequencies and the frequency intervals; determining the band-pass filter set according to the passband frequency ranges.

6. The method according to any one of claims 1 to 5, characterized in that, The construction of the bridge modal shapes according to the bridge modal components comprises: obtaining orthogonal components of the bridge modal components; constructing a complex analytic signal according to the bridge modal components and the orthogonal components; converting the complex analytic signal from a Cartesian coordinate system to a polar coordinate system to obtain a target instantaneous amplitude; constructing the bridge modal shapes according to the target instantaneous amplitude.

7. The method according to any one of claims 1 to 5, characterized in that, The basic scour detection according to the bridge modal shapes to obtain the damage area and the scour degree of the target bridge comprises: calculating a target modal shape curvature of the bridge modal shapes; obtaining a reference modal shape of a healthy bridge and calculating a reference modal shape curvature of the reference modal shape; calculating a difference value between the target modal shape curvature and the reference modal shape curvature to obtain a modal shape curvature difference value, and determining the damage area according to the modal shape curvature difference value; calculating a modal curvature root mean square difference value between the bridge modal shapes and the reference modal shape to obtain the scour degree.

8. A bridge foundation scour detection apparatus, characterised in that, The device comprises: an obtaining module configured to obtain vehicle acceleration of a target vehicle uniformly driving on a target bridge; An acceleration calculation module is configured to calculate a contact acceleration between the target vehicle and the target bridge according to the vehicle acceleration; A bridge frequency calculation module is configured to calculate a bridge frequency distribution of the target bridge according to the contact acceleration; A modal separation module is configured to perform modal separation on the bridge frequency distribution to obtain a bridge modal component; A construction module is configured to construct a bridge modal shape according to the bridge modal component; A detection module is configured to perform basic scour detection according to the bridge modal shape to obtain a damage area and a scour degree of the target bridge.

9. An electronic device, comprising: The electronic device comprises a memory and a processor, the memory stores a computer program, and the processor implements the method in any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium storing a computer program, the computer program comprising instructions that, when executed by a computer, cause the computer to perform the method of any one of claims 1 to 9. The computer program is executed by the processor to implement the method in any one of claims 1 to 7.

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