Bridge dynamic weighing method, device, equipment and storage medium

Abstract

The present application provides a bridge dynamic weighing method, apparatus, device, and storage medium. The method includes collecting strain data generated by a bridge when a calibration vehicle and a target vehicle pass through the bridge, calculating the weight ratio of the calibration vehicle and the target vehicle based on the strain data, and ultimately determining the weight of the target vehicle based on the weight ratio and the weight of the calibration vehicle. Compared to the prior art method of identifying vehicle weight based on bridge physical model information, the method of the present application does not rely on bridge physical model information, thereby avoiding the difficulty in identifying vehicle weight caused by the difficulty in obtaining or changing the bridge influence line, and achieving more convenient vehicle weight identification and reducing calculation complexity.

Description

Technical Field

[0001] The present application relates to the technical field of transportation infrastructure safety monitoring, and specifically to a bridge dynamic weighing method, device, equipment and storage medium. Background Art

[0002] Highway bridges are key components of transportation infrastructure. However, the prevalence of overloaded vehicles is increasing, causing varying degrees of damage to bridges, degrading their performance, significantly shortening their service life, and even seriously threatening their safe operation. Therefore, accurately identifying vehicle loads and promptly controlling overloaded vehicles are crucial for the daily operation and maintenance of infrastructure such as highway bridges.

[0003] Existing technologies rely on bridge weigh-in-motion systems to identify and control overloaded vehicles. These systems are typically based on information from the bridge's physical model, such as static influence lines. They utilize the least squares method for calculations, using an optimization algorithm to determine vehicle load information using the error function between measured response data and theoretically calculated responses.

[0004] However, the bridge physical model information cannot be accurately obtained in actual operations, and the bridge physical model information will also change with the age of the bridge, which will lead to errors in the identification of the bridge dynamic weighing system. Summary of the Invention

[0005] The purpose of this application is to address the deficiencies in the above-mentioned prior art and provide a bridge dynamic weighing method, device, equipment and storage medium to solve the problem of the difficulty in accurately obtaining static influence line information in the existing bridge dynamic weighing technology and the bridge dynamic weighing identification error caused by changes in the bridge influence line.

[0006] To achieve the above objectives, the technical solutions adopted in this application are as follows:

[0007] In a first aspect, the present application provides a bridge dynamic weighing method, the method comprising:

[0008] Collecting calibration strain data of the calibration vehicle, wherein the calibration strain data is used to characterize the relationship between the strain of the bridge and time when the calibration vehicle passes through the bridge;

[0009] Determining calibration strain spatial domain data of the calibration vehicle based on the calibration strain data, wherein the calibration strain spatial domain data is used to characterize the relationship between the strain of the bridge when the calibration vehicle passes through the bridge and the distance traveled by the calibration vehicle on the bridge;

[0010] collecting target strain data of a target vehicle, wherein the target strain data is used to characterize the relationship between the strain of the bridge and time when the target vehicle passes through the bridge;

[0011] Determining target strain spatial domain data of the target vehicle based on the target strain data, wherein the target strain spatial domain data is used to characterize the relationship between the strain of the bridge when the target vehicle passes through the bridge and the distance traveled by the calibration vehicle on the bridge;

[0012] The weight ratio of the target vehicle to the calibration vehicle is determined based on the calibration strain space domain data and the target strain space domain data at the same measuring point of the bridge, and the weight of the target vehicle is determined based on the weight ratio.

[0013] Optionally, determining the weight ratio of the target vehicle to the calibration vehicle at the same measuring point of the bridge based on the calibration strain spatial domain data and the target strain spatial domain data at the same measuring point of the bridge includes:

[0014] Obtain calibration strain space domain data and target strain space domain data corresponding to the same measuring point;

[0015] Determining, based on the calibration strain spatial domain data and the target strain spatial domain data, a ratio of Fourier transform coefficients of strain spatial domain data at the same measuring point of the bridge caused by the target vehicle and the calibration vehicle respectively passing through the bridge at a uniform speed;

[0016] The ratio of the Fourier transform coefficients at zero frequency is taken as the weight ratio.

[0017] Optionally, determining, based on the calibration strain spatial domain data and the target strain spatial domain data, a ratio of Fourier transform coefficients of strain spatial domain data at the same measuring point of a bridge caused when the target vehicle and the calibration vehicle respectively pass through the bridge at a uniform speed includes:

[0018] performing data resampling and discrete Fourier transform on the calibration strain spatial domain data to obtain calibration Fourier transform coefficients of the calibration vehicle;

[0019] performing data resampling and discrete Fourier transform on the target strain spatial domain data to obtain target Fourier transform coefficients of the target vehicle;

[0020] A ratio of the calibration Fourier transform coefficients to the target Fourier transform coefficients is calculated.

[0021] Optionally, performing data resampling and discrete Fourier transform on the target strain spatial domain data to obtain target Fourier transform coefficients of the target vehicle includes:

[0022] resampling the target strain spatial domain data to obtain resampled target strain spatial domain data, wherein the spatial interval of each sample point in the resampled target strain spatial domain data is the same as the spatial interval of each sample point in the resampled calibration strain spatial domain data;

[0023] The resampled target strain spatial domain data is subjected to discrete Fourier transform to obtain the target Fourier transform coefficients.

[0024] Optionally, obtaining target strain spatial domain data of the target vehicle according to the target strain data includes:

[0025] determining a product of a vehicle speed of the target vehicle and a time in a target strain data item;

[0026] The product and the strain in the one item of target strain data are used as one item of target strain spatial domain data.

[0027] Optionally, determining the speed of the target vehicle includes:

[0028] Determine first strain data of a first measuring point and second strain data of a second measuring point of the target vehicle on the bridge;

[0029] determining a time difference between the target vehicle passing through a first measuring point and a second measuring point based on a cross-correlation function of the first strain data and the second strain data;

[0030] The ratio of the measuring point distance between the first measuring point and the second measuring point to the time difference is used as the speed of the target vehicle.

[0031] Optionally, determining the weight of the target vehicle according to the weight ratio includes:

[0032] Obtaining the vehicle weight of the calibration vehicle;

[0033] The weight of the target vehicle is determined according to the weight ratio and the vehicle weight of the calibration vehicle.

[0034] In a second aspect, the present application provides a bridge dynamic weighing device, the device comprising:

[0035] A first acquisition module is used to acquire calibration strain data of the calibration vehicle, wherein the calibration strain data is used to characterize the relationship between the strain of the bridge and time when the calibration vehicle passes through the bridge;

[0036] a first determining module, configured to determine calibration strain spatial domain data of the calibration vehicle based on the calibration strain data, wherein the calibration strain spatial domain data is used to characterize the relationship between the strain of the bridge when the calibration vehicle passes through the bridge and the distance traveled by the calibration vehicle on the bridge;

[0037] A second acquisition module is used to acquire target strain data of a target vehicle, wherein the target strain data is used to characterize the relationship between the strain of the bridge and time when the target vehicle passes through the bridge;

[0038] a second determination module, configured to determine target strain spatial domain data of the target vehicle based on the target strain data, wherein the target strain spatial domain data is used to characterize the relationship between the strain of the bridge when the target vehicle passes through the bridge and the distance traveled by the calibration vehicle on the bridge;

[0039] The weight identification module is used to determine the weight ratio of the target vehicle and the calibration vehicle at the same measuring point of the bridge based on the calibration strain space domain data and the target strain space domain data at the same measuring point of the bridge, and determine the weight of the target vehicle based on the weight ratio.

[0040] Optionally, the weight identification module is specifically used to:

[0041] Obtain calibration strain space domain data and target strain space domain data corresponding to the same measuring point;

[0042] Determining, based on the calibration strain spatial domain data and the target strain spatial domain data, a ratio of Fourier transform coefficients of strain spatial domain data at the same measuring point of the bridge caused by the target vehicle and the calibration vehicle respectively passing through the bridge at a uniform speed;

[0043] The ratio of the Fourier transform coefficients at zero frequency is taken as the weight ratio.

[0044] Optionally, the weight identification module is further specifically configured to:

[0045] performing data resampling and discrete Fourier transform on the calibration strain spatial domain data to obtain calibration Fourier transform coefficients of the calibration vehicle;

[0046] performing data resampling and discrete Fourier transform on the target strain spatial domain data to obtain target Fourier transform coefficients of the target vehicle;

[0047] A ratio of the calibration Fourier transform coefficients to the target Fourier transform coefficients is calculated.

[0048] Optionally, the weight identification module is further specifically configured to:

[0049] resampling the target strain spatial domain data to obtain resampled target strain spatial domain data, wherein the spatial interval of each sample point in the resampled target strain spatial domain data is the same as the spatial interval of each sample point in the resampled calibration strain spatial domain data;

[0050] The resampled target strain spatial domain data is subjected to discrete Fourier transform to obtain the target Fourier transform coefficients.

[0051] Optionally, the second determining module is specifically configured to:

[0052] determining a product of a vehicle speed of the target vehicle and a time in a target strain data item;

[0053] The product and the strain in the one item of target strain data are used as one item of target strain spatial domain data.

[0054] Optionally, the second determining module is further specifically configured to:

[0055] Determine first strain data of a first measuring point and second strain data of a second measuring point of the target vehicle on the bridge;

[0056] determining a time difference between the target vehicle passing through a first measuring point and a second measuring point based on a cross-correlation function of the first strain data and the second strain data;

[0057] The ratio of the measuring point distance between the first measuring point and the second measuring point to the time difference is used as the speed of the target vehicle.

[0058] Optionally, the weight identification module is further specifically configured to:

[0059] Obtaining the vehicle weight of the calibration vehicle;

[0060] The weight of the target vehicle is determined according to the weight ratio and the vehicle weight of the calibration vehicle.

[0061] In a third aspect, the present application provides an electronic device comprising: a processor, a storage medium and a bus, wherein the storage medium stores machine-readable instructions executable by the processor. When the electronic device is running, the processor and the storage medium communicate through the bus, and the processor executes the machine-readable instructions to perform the steps of the above-mentioned bridge weighing method.

[0062] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the bridge weighing method described above are executed.

[0063] The beneficial effect of the present application is that by processing the strain data, based on the equivalence characteristic of the ratio of the Fourier transform coefficients of the strain spatial domain data of the same measuring point of the bridge caused by the target vehicle and the calibration vehicle respectively passing the bridge at a uniform speed and the ratio of the weight of the target vehicle and the calibration vehicle at zero frequency, the weight ratio of the target vehicle and the calibration vehicle is finally determined, and the weight of the target vehicle is determined based on the weight ratio. Compared with the prior art of identifying the vehicle weight through the physical model information of the bridge, it gets rid of the dependence on the bridge influence line. The technician can calculate the weight of the target vehicle based on the strain data without obtaining the physical model information of the bridge, avoiding the situation where the bridge influence line is difficult to obtain or the bridge influence line is changed. The difficulty in identifying the vehicle weight is avoided, and more convenient vehicle weight identification is achieved, reducing the complexity of the calculation. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0065] Figure 1 A schematic diagram of a bridge dynamic weighing system provided by an embodiment of the present application is shown;

[0066] Figure 2 A flow chart of a bridge dynamic weighing method provided by an embodiment of the present application is shown;

[0067] Figure 3 A flow chart for determining a weight ratio provided in an embodiment of the present application is shown;

[0068] Figure 4 A flow chart of another method for determining a weight ratio provided in an embodiment of the present application is shown;

[0069] Figure 5 A flow chart for determining target Fourier transform coefficients provided by an embodiment of the present application is shown;

[0070] Figure 6 A flowchart of determining target spatial domain data provided by an embodiment of the present application is shown;

[0071] Figure 7 A flow chart for determining the speed of a target vehicle provided by an embodiment of the present application is shown;

[0072] Figure 8 A schematic diagram of a strain history curve provided in an embodiment of the present application is shown;

[0073] Figure 9A flow chart for determining a target vehicle weight according to an embodiment of the present application is shown;

[0074] Figure 10 A schematic structural diagram of a bridge weighing device provided in an embodiment of the present application is shown;

[0075] Figure 11 A schematic structural diagram of an electronic device provided in an embodiment of the present application is shown. DETAILED DESCRIPTION

[0076] In order to make the purpose, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. It should be understood that the drawings in the present application only serve the purpose of illustration and description and are not used to limit the scope of protection of the present application. In addition, it should be understood that the schematic drawings are not drawn to scale. The flowcharts used in this application illustrate the operations implemented according to some embodiments of the present application. It should be understood that the operations of the flowcharts can be implemented out of sequence, and steps without logical context can be reversed or implemented simultaneously. In addition, those skilled in the art, under the guidance of the contents of this application, can add one or more other operations to the flowchart, or remove one or more operations from the flowchart.

[0077] In addition, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application generally described and shown in the drawings here can be arranged and designed in various configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without making creative work are within the scope of protection of the present application.

[0078] It should be noted that the term "comprising" will be used in the embodiments of the present application to indicate the existence of the features declared thereafter, but does not exclude the addition of other features.

[0079] Existing technologies often rely on bridge weigh-in-motion systems to identify and control overloaded vehicles. When a vehicle passes over a bridge, hardware systems collect data and perform calculations based on that data, generating vehicle load information. Specifically, these systems are often based on information from the bridge's physical model, such as static influence lines. They use the least squares method for calculations, utilizing an optimization algorithm to determine vehicle load information using the error function between measured response data and theoretically calculated responses.

[0080] However, in practical applications, the bridge influence line is often difficult to obtain accurately. Moreover, during the service life of the bridge, the actual influence line of the bridge will also change due to the deterioration of the bridge performance, which will cause certain errors in the identification results of the bridge dynamic weighing system.

[0081] Based on the above problems, the present application proposes a bridge dynamic weighing method, which determines the ratio of the Fourier transform coefficients of the strain spatial domain data of the same measuring point of the bridge caused by the target vehicle and the calibration vehicle respectively passing the bridge at a uniform speed based on the strain data generated when the calibration vehicle and the target vehicle pass through the bridge, and determines the weight ratio of the calibration vehicle and the target vehicle based on the equivalence characteristics of the calculated Fourier transform coefficient ratio at zero frequency and the ratio of the weight of the calibration vehicle and the target vehicle, and determines the weight of the target vehicle based on the weight ratio and the weight of the calibration vehicle. The vehicle weighing method of the present application gets rid of the dependence on the bridge influence line, and at the same time has low complexity. It can directly use the existing bridge weighing system for vehicle weighing identification, which can effectively reduce the installation cost and greatly improve the accuracy and reliability of bridge weighing.

[0082] Next, the bridge dynamic weighing system of this application is described. The bridge dynamic weighing system can dynamically weigh vehicles passing through the bridge. Figure 1 The figure is a schematic diagram of a bridge dynamic weighing system given in this application, referring to Figure 1 The bridge dynamic weighing system includes: dynamic strain gauge, dynamic weighing hardware and dynamic weighing software system.

[0083] The dynamic strain gauges, comprising at least two installed at predetermined cross-sectional locations on the bridge bottom, measure the strain generated by a calibration vehicle (of known weight) and a target vehicle (of unknown weight) crossing the bridge. The dynamic weighing hardware system, fixed to a specific location on the bridge and connected to the dynamic strain gauges, collects bridge strain data in real time. The dynamic weighing software calculates the vehicle weight based on the collected data.

[0084] Dynamic strain gauges can be installed at any predetermined cross-sectional location on the bottom of the bridge. Depending on practical circumstances and application effectiveness, installations at mid-span and quarter-span locations are recommended. These locations have a more pronounced strain amplitude and a higher signal-to-noise ratio, making identification less susceptible to environmental and measurement noise. Furthermore, the present invention is not limited to bridge strain responses; other types of sensors can also be used to capture the deflection response of vehicles crossing bridges.

[0085] The dynamic weighing hardware system can be fixed on the top or pier of the bridge, or on the ground near the bottom of the bridge pier and the superstructure of the bridge, so as to facilitate connection with sensors and data collection. This application does not impose any restrictions on this.

[0086] The dynamic weighing software system can store and call the strain time history data and the travel speed of a calibrated vehicle with a known total weight when it passes over a bridge. At the same time, in actual applications, technicians can keep the sampling frequency unchanged to facilitate calculations.

[0087] Next, the bridge dynamic weighing method of this application is further explained. The execution subject of this method can be Figure 1 The dynamic weighing software system in the dynamic weighing software system, or the electronic equipment connected to the dynamic weighing software system, such as Figure 2 As shown, the method includes:

[0088] S201: Collecting calibration strain data of the calibration vehicle, where the calibration strain data is used to characterize the relationship between the strain of the bridge and time when the calibration vehicle passes through the bridge.

[0089] Optionally, the calibration strain data can be obtained when the calibration vehicle passes through the bridge. Figure 1 The dynamic strain gauge in the figure and the strain data of the bridge collected by the dynamic hardware system, where the strain represents the relative deformation of the local part of the bridge where the dynamic strain gauge is located when the calibration vehicle passes through the bridge.

[0090] Optionally, the calibration strain data may include multiple time points and the strains of the bridge at those time points.

[0091] In this application, when a calibrated vehicle passes through a bridge, the strain of the bridge can be collected according to a preset time period, for example, the strain of the bridge is collected every Δt time, and the collection time point and the strain of the bridge are used as one set of strain data.

[0092] For example, the strain data s0(t) = {ε0(0), ε0(Δt), ε0(2Δt), …, ε0[(N0-1)Δt]} is calibrated from the time the vehicle is on the bridge to the time it is completely off the bridge. Here, s0(t) is discretized into N0 sampling points according to the collection situation in actual engineering applications, where the time interval is Δt = 1 / f s , f s is the device sampling frequency, and (N0-1)Δt is the total sampling time T0.

[0093] It should be noted that the calibration vehicle can pass through the bridge at a constant speed according to a preset speed, and the speed and weight of the calibration vehicle are known.

[0094] S202: Determine calibration strain spatial domain data of the calibration vehicle based on the calibration strain data. The calibration strain spatial domain data is used to characterize the relationship between the strain of the bridge when the calibration vehicle passes through the bridge and the distance the calibration vehicle has traveled on the bridge.

[0095] Optionally, the calibration strain spatial domain data may represent the relationship between the strain of the bridge when the calibration vehicle passes through the bridge and the distance the calibration vehicle has traveled on the bridge.

[0096] Assuming that the vehicle speed of the calibration vehicle is v0, the strain of the bridge is collected every Δt time and converted into calibration strain spatial domain data. Assuming that the time when the calibration vehicle starts to go on the bridge is time 0, the distance traveled by the calibration vehicle at time 0 is 0, and the distance traveled by the calibration vehicle at time t is v0×t. The strain of the bridge at time t in the calibration strain data will be converted into the strain of the bridge when the distance is v0×t in the calibration strain spatial domain data.

[0097] For example, the above-mentioned time domain discrete sample points s0(t) can be expressed as spatial domain discrete sample points s0(x) = {ε0(0),ε0(Δx0),ε0(2Δx0),…,ε0[(N0-1)Δx0]} according to the one-to-one correspondence between the acquisition time and the distance traveled by the calibration vehicle, where x represents the distance traveled by the first axle of the calibration vehicle, and the spatial interval Δx0 = v0Δt = v0 / f s , (N0-1)Δx0 is the total distance X0 traveled by the calibrated vehicle.

[0098] S203: Target strain data of the target vehicle is collected. The target strain data is used to characterize the relationship between the strain of the bridge and time when the target vehicle passes through the bridge.

[0099] Optionally, the target vehicle may be a vehicle whose weight needs to be measured.

[0100] Optionally, the target strain data can be when the target vehicle passes through the bridge. Figure 1 The dynamic strain gauge in the figure and the strain data of the bridge collected by the dynamic hardware system, wherein the strain represents the relative deformation of the local part of the bridge where the dynamic strain gauge is located when the target vehicle passes through the bridge.

[0101] Optionally, the target strain data may include multiple time points and the strains of the bridge at those time points.

[0102] In this application, when the target vehicle passes through the bridge, the strain of the bridge can be collected according to a preset time period, for example, the strain of the bridge is collected every Δt time, and the collection time point and the strain of the bridge are used as one set of target strain data.

[0103] For example, a calibration vehicle with an unknown weight of m1 is selected, and it is assumed that the target vehicle passes the bridge at a constant speed of v1. The bridge dynamic strain data s1(t) = {ε1(0), ε1(Δt), ε1(2Δt), …, ε1[(N1-1)Δt]} from the time the target vehicle goes up the bridge to the time it completely goes down the bridge is recorded and stored. Here, s1(t) is discretized into N1 sampling points according to the collection situation in actual engineering applications, where the time interval is Δt = 1 / f s , f s is the device sampling frequency, and (N1-1)Δt is the total sampling time T1.

[0104] S204: Determine target strain spatial domain data of the target vehicle based on the target strain data. The target strain spatial domain data is used to characterize the relationship between the strain of the bridge when the target vehicle passes through the bridge and the distance traveled by the calibration vehicle on the bridge.

[0105] Assuming that the vehicle speed of the target vehicle is v1, the strain of the bridge is collected every Δt time and converted into target strain spatial domain data. Assuming that the time when the target vehicle starts to go on the bridge is time 0, the distance traveled by the target vehicle at time 0 is 0, and the distance traveled by the target vehicle at time t is v1×t. The strain of the bridge at time t in the target strain data will be converted into the strain of the bridge when the distance is v1×t in the target strain spatial domain data.

[0106] For example, the above-mentioned time domain discrete sample point ε1(t) can be represented as a spatial domain discrete sample point s1(x) = {ε1(0),ε1(Δx1),ε1(2Δx1),…,ε1[(N1-1)Δx1]} according to the one-to-one correspondence between the acquisition time and the distance traveled by the target vehicle, where x represents the distance traveled by the first axle of the target vehicle, and the spatial interval Δx1 = v1Δt = v1 / f s , (N1-1)Δx1 is the total distance X1 traveled by the target vehicle.

[0107] It should be noted that the vehicle speed of the target vehicle is an unknown quantity. In this application, the vehicle speed of the target vehicle can be obtained through sensors, or it can be calculated based on strain data. The specific calculation method is described later and will not be repeated here.

[0108] S205: Determine a weight ratio of the target vehicle to the calibration vehicle based on the calibration strain space domain data and the target strain space domain data at the same measuring point of the bridge, and determine the weight of the target vehicle based on the weight ratio.

[0109] Optionally, the calibration strain spatial domain data can represent the relationship between the strain at the location of the dynamic strain gauge collected by the dynamic strain gauge when the calibration vehicle passes through the bridge and the distance the calibration vehicle has traveled, and the target strain spatial domain data can represent the relationship between the strain at the location of the dynamic strain gauge collected by the dynamic strain gauge when the target vehicle passes through the bridge and the distance the target vehicle has traveled.

[0110] In this application, the weight ratio of the target vehicle to the calibration vehicle can be determined based on the calibration strain space domain data and the target strain space domain data at the same measuring point on the bridge, that is, the location of the dynamic strain gauge. The weight of the calibration vehicle has been stored in the dynamic weighing software system. Therefore, based on this weight ratio and the weight of the calibration vehicle, the weight of the target vehicle can be calculated.

[0111] For example, assuming that the weight of the calibration vehicle is m0, and the weight ratio of the target vehicle to the calibration vehicle at the location of the dynamic strain gauge on the bridge is r, the weight m1 of the target vehicle can be expressed as m1=m0×r.

[0112] It should be noted that in this application, multiple dynamic strain gauges can be set at multiple locations on the bridge, and multiple weights of the target vehicle can be calculated based on the strain data collected by each dynamic strain gauge, and the average value of these target vehicles can be used as the final vehicle weight of the target vehicle.

[0113] In an embodiment of the present application, calibration strain data of the calibration vehicle is collected, and calibration strain spatial domain data is determined based on the calibration strain data. Target strain data of the target vehicle is collected, and target strain spatial domain data is determined based on the target strain data. Finally, the weight ratio of the target vehicle to the calibration vehicle is determined based on the target strain spatial domain data and the calibration strain spatial domain data at the same measuring point on the bridge, and the weight of the target vehicle is determined based on the weight ratio. By processing the strain data to ultimately determine the weight ratio of the target vehicle to the calibration vehicle and determining the weight of the target vehicle based on the weight ratio, the dependence on the bridge influence line is eliminated. Technicians can calculate the weight of the target vehicle based on the strain data without obtaining the bridge physical model information, avoiding the difficulty in identifying the vehicle weight caused by the difficulty in obtaining the bridge influence line or the change of the bridge influence line, and achieving more convenient vehicle weight identification. Compared with the prior art of identifying vehicle weight through bridge physical model information, the complexity of the calculation is reduced.

[0114] Next, combine Figure 3 , the steps of determining the weight ratio of the target vehicle and the calibration vehicle at the same measuring point of the bridge based on the calibration strain space domain data and the target strain space domain data at the same measuring point of the bridge are described as follows: Figure 3 As shown, the above step S205 includes:

[0115] S301: Acquire calibration strain space domain data and target strain space domain data corresponding to the same measuring point.

[0116] Reference Figure 1 , the strain data of the calibration vehicle and the target vehicle can be collected by the dynamic strain gauge set at the bottom of the bridge, and the calibration strain data and the target strain data can be converted into calibration strain space domain data and target strain space domain data respectively.

[0117] It should be noted that when multiple dynamic strain gauges are installed at the bottom of the bridge, the calibration strain space domain data and target strain space domain data corresponding to the same measuring point can be the calibration strain space domain data and target strain space domain data corresponding to the strain data collected by the same dynamic strain gauge.

[0118] S302: Determine, based on the calibration strain spatial domain data and the target strain spatial domain data, a ratio of Fourier transform coefficients of strain spatial domain data at the same measuring point of the bridge caused by the target vehicle and the calibration vehicle respectively passing through the bridge at a uniform speed.

[0119] Optionally, the ratio of discrete Fourier transform coefficients of the strain space domain data at the same measuring point of the bridge when the target vehicle and the calibration vehicle respectively pass through the bridge, hereinafter referred to as the ratio of the Fourier transform coefficients of the target vehicle and the calibration vehicle, is equivalent to the ratio of the weights of the target vehicle and the calibration vehicle at the zero frequency position, and is independent of the static influence line of the bridge, thereby avoiding the use of bridge physical model information.

[0120] Optionally, the Fourier transform coefficient Y0(ω) of the calibration vehicle can be determined based on the calibration strain spatial domain data, and the Fourier transform coefficient Y1(ω) of the target vehicle can be determined based on the target strain spatial domain data. Then, the weight ratio r(ω) can be expressed by the following formula (1):

[0121]

[0122] To facilitate understanding, the relationship between the Fourier transform coefficients of the strain spatial domain data and the vehicle weight in this application, that is, the principle on which the method of this application is based, is explained below.

[0123] In this application, the mathematical expression of the ratio of the original Fourier transform coefficients of the strain spatial domain data of the same measuring point of the bridge caused by the target vehicle and the calibration vehicle respectively passing the bridge at a uniform speed can be shown as the above formula (1), where r(ω) represents the value of the ratio of the Fourier transform coefficients of the target vehicle and the calibration vehicle at the frequency point ω.

[0124] When a vehicle passes over a bridge, the vehicle load can be considered as multiple concentrated loads with axle weight as the magnitude, and expressed as:

[0125]

[0126] Where x is the distance traveled by the first axle, f i is the axle weight of the i-th axle of the vehicle, x i is the position of the i-th axis of the vehicle, N x is the number of vehicle axles, and δ is the Dirac delta function. In this case, based on the superposition principle of bridge influence lines, the theoretical strain prediction value of the bridge can be expressed in the form of convolution:

[0127]

[0128] Here l(x) is the bridge strain influence line, is the convolution operator symbol. According to convolution theory, when the Fourier transform of f(x) and l(x) exist, the Fourier transform of ε(x) can be expressed as the product of the Fourier transform of f(x) and l(x), and its mathematical expression is:

[0129] Y(ω)=L(ω)F(ω)(4)

[0130] where Y(ω), L(ω), and F(ω) are the Fourier transforms of the bridge strain ε(x), the bridge influence line l(x), and the vehicle load f(x), respectively. Meanwhile, the Fourier transform of f(x) in Equation (4) can be expressed as:

[0131]

[0132] Substituting equations (4) and (5) into equation (1), we obtain:

[0133]

[0134] Where F1(ω) and F0(ω) are the Fourier transforms of the vehicle weights of the target vehicle and the calibration vehicle, respectively, and f 1i and f 1j , x 1i and x 1j are the axle weight of the target vehicle and the location of the corresponding axle, f 0i and f 0j , x 0i and x 0j They are the axle weight of the calibrated vehicle and the position of the corresponding axle.

[0135] It can be seen that the ratio of the Fourier transform coefficients of the target vehicle and the calibration vehicle is only related to the weight of the calibration vehicle and the target vehicle, and has nothing to do with the static influence line of the bridge.

[0136] At the same time, it can be seen that when the target vehicle and the calibration vehicle respectively pass through the bridge at the zero frequency position, that is, ω = 0, the ratio of the discrete Fourier transform coefficients of the strain spatial domain data at the same measuring point of the bridge can be expressed as follows (7):

[0137]

[0138] Therefore, the ratio of the Fourier transform coefficients of the target vehicle and the calibration vehicle used in this application has the following property at the zero frequency position: the ratio of the discrete Fourier transform coefficients of the strain space domain data of the same measuring point of the bridge when the target vehicle and the calibration vehicle respectively pass through the bridge at zero frequency is equal to the ratio of the gross weight of the target vehicle and the calibration vehicle. The mathematical expression is as follows:

[0139]

[0140] Therefore, the ratio of the Fourier transform coefficients at the zero-frequency position can be used as the weight ratio of the calibration vehicle and the target vehicle. Since the weight of the calibration vehicle is known, the present application can calculate the vehicle weight of the target vehicle based on the strain data without measuring the bridge influence line.

[0141] S303: The ratio of the Fourier transform coefficients at zero frequency is used as the weight ratio.

[0142] Optionally, referring to the above description of the principle on which the method is based, the present application may use the ratio of the Fourier transform coefficients of the target vehicle and the calibration vehicle at the zero frequency position as the ratio of the total weight of the target vehicle and the calibration vehicle.

[0143] The following is a further explanation of the above-mentioned determination of the ratio of Fourier transform coefficients, such as Figure 4 As shown, the above step S302 includes:

[0144] S401: performing data resampling and discrete Fourier transform on the calibration strain spatial domain data to obtain calibration Fourier transform coefficients of the calibration vehicle.

[0145] It should be noted that when the strain data is converted into strain spatial domain data, there may be a problem that the spatial intervals of the converted calibration strain spatial domain data and the target strain spatial domain data are different. Therefore, the calibration strain spatial domain data and the target strain spatial domain data can be resampled respectively, and the calibration strain spatial domain data and the target strain spatial domain data can be converted into discrete sample points with the same spatial interval, and the spatial intervals of two adjacent data in the calibration strain spatial domain data and the target strain spatial domain data are also the same, so that the frequency points after discrete Fourier transform can correspond one to one.

[0146] After resampling the calibration strain spatial domain data, discrete Fourier transform may be performed on the resampled data to obtain calibration Fourier transform coefficients of the calibration vehicle.

[0147] S402: performing data resampling and discrete Fourier transform on the target strain spatial domain data to obtain target Fourier transform coefficients of the target vehicle.

[0148] Optionally, the discrete Fourier transform may be an original Fourier transform performed on the strain spatial domain data, wherein the Fourier transform coefficient may be a value of the original Fourier transform at the frequency point ω.

[0149] S403: Calculate the ratio of the calibration Fourier transform coefficient to the target Fourier transform coefficient.

[0150] As shown in the above formula (1), r(ω) represents the value of the ratio of the discrete Fourier transform coefficients of the strain space domain data of the same measuring point of the bridge when the target vehicle and the calibration vehicle respectively pass through the bridge at the frequency point ω. When ω is the zero frequency position, r can represent the weight ratio of the target vehicle and the calibration vehicle, where Y1(ω) is the value of the target Fourier transform coefficient at the frequency point ω, and Y0(ω) is the value of the calibration Fourier transform coefficient at the frequency point ω.

[0151] like Figure 5 As shown, the specific steps of performing data resampling and discrete Fourier transform on the target strain spatial domain data in S402 to obtain the target Fourier transform coefficients of the target vehicle include:

[0152] S501: resampling the target strain spatial domain data to obtain resampled target strain spatial domain data, wherein the spatial interval of each sample point in the resampled target strain spatial domain data is the same as the spatial interval of each sample point in the resampled calibration strain spatial domain data.

[0153] The target strain spatial domain data is s1(x)={ε1(0),ε1(Δx1),ε1(2Δx1),…,ε1[(N1-1Δx1). After data resampling, the obtained strain data can be expressed as follows (9):

[0154] S1(x)={E1(0),E1(Δx),E1(2Δx),…,E1[(N-1)Δx]}(9)

[0155] Where S1(x) represents the strain data sample point after resampling s1(x), Δx is the spatial interval after resampling, and N is the number of sample points after resampling. The spatial interval of each sample point is the same.

[0156] S502: Performing discrete Fourier transform on the resampled target strain spatial domain data to obtain target Fourier transform coefficients.

[0157] Optionally, the calculation of discrete Fourier transform of the resampled target strain spatial domain data can be shown as follows (10):

[0158]

[0159] It should be noted that the method of performing data resampling and discrete Fourier transform on the calibration strain spatial domain data may be the same as the above-mentioned S501-S502.

[0160] The strain data obtained after resampling the calibration strain space domain data s0(x)={ε0(0),ε0(Δx0),ε0(2Δx0),…,ε0[(N0-1Δx0)] can be expressed as follows (11).

[0161] S0(x)={E0(0),E0(Δx),E0(2Δx),…,E0[(N-1)Δx]}(11)

[0162] Where S0(x) represents the strain data sample point after resampling s0(x), Δx is the spatial interval after resampling, and N is the number of sample points after resampling. The spatial interval of each sample point is the same.

[0163] Next, the discrete Fourier transform can be performed on the above equation (11) according to the following equation (12).

[0164]

[0165] In equations (9)-(12), Y0(ω) and Y1(ω) are the values of the original Fourier transforms of S0(x) and S1(x) at frequency ω. Furthermore, the values of Y0(k) and Y1(k) at zero frequency, Y0(0) and Y1(0), can be expressed as equations (13) and (14), respectively.

[0166]

[0167] It can be seen that at the zero frequency position, the original Fourier transform of the response data can be expressed as the sum of all sample points.

[0168] Substituting equations (13) and (14) into equation (8), we can obtain:

[0169]

[0170] It can be seen that the bridge weighing method of the present application can directly calculate the total weight of the target vehicle based on the ratio of the sum of all discrete sampling points, without the need for bridge influence line information, which greatly improves the convenience of calculation.

[0171] The following is a further explanation of the target strain spatial domain data of the target vehicle obtained based on the target strain data. Figure 6 As shown, the above step S204 includes:

[0172] S601: Determine the product of the vehicle speed of the target vehicle and the time in a target strain data item.

[0173] Optionally, the target strain data includes the acquisition time and the strain of the bridge at the measuring point corresponding to the acquisition time. As long as the vehicle speed of the target vehicle is determined, the vehicle speed of the target vehicle and the time in the target strain data can be multiplied in sequence to convert each time point into a distance.

[0174] It should be noted that the vehicle speed of the target vehicle can be calculated based on the strain data, or it can be collected by sensors on the bridge or speed radar. The specific acquisition method is not limited in this application.

[0175] S602: The product and the strain in one item of target strain data are used as one item of target strain spatial domain data.

[0176] Optionally, after determining the product of the vehicle speed of the target vehicle and the acquisition time point, the product and the strain corresponding to the acquisition time point may be used as a target strain spatial domain data.

[0177] In the present application, the time of each set of target strain data in the target strain data may be multiplied by the vehicle speed of the target vehicle, thereby converting the relationship between time and strain into a relationship between distance and strain, and obtaining target strain spatial domain data.

[0178] This application also provides a solution for determining the vehicle speed of the target vehicle, such as Figure 7 As shown, the above-mentioned step of determining the speed of the target vehicle includes:

[0179] S701: Determine first strain data of a target vehicle at a first measuring point and second strain data at a second measuring point on a bridge.

[0180] For two measuring points A and B at different cross-section positions on the bottom of the bridge, the bridge strain time history curves corresponding to the strain data of the two measuring points when the target vehicle passes the bridge are recorded as f(t) and g(t). Figure 8 As shown in Figure 2, when the target vehicle passes right above the measuring point, the two strain curves will produce strain response peak points.

[0181] S702: Determine the time difference between the target vehicle passing the first measuring point and the second measuring point based on the cross-correlation function of the first strain data and the second strain data.

[0182] Optionally, the time difference ΔT can be determined by the maximum value point of the cross-correlation function C(τ) between f(t) and g(t), where the τ value corresponding to the maximum value point of C(τ) is the time difference ΔT. The calculation expression of the cross-correlation function C(τ) is as follows:

[0183]

[0184] S703: The ratio of the distance between the first measuring point and the second measuring point to the time difference is used as the speed of the target vehicle.

[0185] Assuming that the known distance between the two measuring points is ΔL and the time difference between the same axle passing through the two measuring points is ΔT, the target vehicle's speed v1 can be calculated using formula (17).

[0186]

[0187] The following is a description of the steps for determining the weight of the target vehicle based on the weight ratio. Figure 9 As shown, the above step S205 includes:

[0188] S901: Obtain the vehicle weight of the calibrated vehicle.

[0189] Optionally, the vehicle weight of the calibrated vehicle may be a known weight and pre-stored in Figure 1 The dynamic weighing software system shown.

[0190] S902: Determine the weight of the target vehicle according to the weight ratio and the vehicle weight of the calibration vehicle.

[0191] As shown in the above formula (18), m1=m0r, so the product of the weight ratio and the vehicle weight of the calibration vehicle can be used as the weight of the target vehicle.

[0192] As mentioned above, the weight ratio may be the ratio of the sum of discrete sampling points of the calibration vehicle and the target vehicle.

[0193] In the embodiment of the present application, the weight ratio is calculated by the sum of discrete sampling points, and the vehicle weight of the target vehicle can be obtained simply and quickly based on the weight ratio and the vehicle weight of the calibration vehicle, which greatly reduces the complexity of the calculation.

[0194] Based on the same inventive concept, the embodiment of the present application also provides a bridge weighing device corresponding to the dynamic weighing method of the bridge. Since the principle of solving the problem by the device in the embodiment of the present application is similar to the above-mentioned bridge weighing method in the embodiment of the present application, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be repeated.

[0195] Reference Figure 10 FIG. 1 is a schematic diagram of a bridge weighing device provided in an embodiment of the present application, wherein the device includes: a first acquisition module 1001, a first determination module 1002, a second acquisition module 1003, a second determination module 1004, and a weight identification module 1005, wherein:

[0196] The first acquisition module 1001 is used to acquire calibration strain data of the calibration vehicle, where the calibration strain data is used to characterize the relationship between the strain of the bridge and time when the calibration vehicle passes through the bridge;

[0197] A first determining module 1002 is configured to determine calibration strain spatial domain data of the calibration vehicle based on the calibration strain data, where the calibration strain spatial domain data is used to represent the relationship between the strain of the bridge when the calibration vehicle passes through the bridge and the distance traveled by the calibration vehicle on the bridge;

[0198] The second acquisition module 1003 is used to acquire target strain data of the target vehicle, where the target strain data is used to characterize the relationship between the strain of the bridge and time when the target vehicle passes through the bridge;

[0199] The second determining module 1004 is configured to determine target strain spatial domain data of the target vehicle based on the target strain data, where the target strain spatial domain data is used to represent the relationship between the strain of the bridge when the target vehicle passes through the bridge and the distance traveled by the calibration vehicle on the bridge;

[0200] The weight identification module 1005 is used to determine the weight ratio of the target vehicle and the calibration vehicle at the same measuring point of the bridge based on the calibration strain space domain data and the target strain space domain data at the same measuring point of the bridge, and determine the weight of the target vehicle based on the weight ratio.

[0201] Optionally, the weight identification module 1005 is specifically configured to:

[0202] Obtain calibration strain space domain data and target strain space domain data corresponding to the same measuring point;

[0203] According to the calibration strain space domain data and the target strain space domain data, the ratio of the Fourier transform coefficients of the strain space domain data at the same measuring point of the bridge caused by the target vehicle and the calibration vehicle respectively passing through the bridge at a uniform speed is determined;

[0204] The ratio of the Fourier transform coefficients at zero frequency is taken as the weight ratio.

[0205] Optionally, the weight identification module 1005 is further specifically configured to:

[0206] Performing data resampling and discrete Fourier transform on the calibration strain spatial domain data to obtain calibration Fourier transform coefficients of the calibration vehicle;

[0207] Perform data resampling and discrete Fourier transform on the target strain spatial domain data to obtain the target Fourier transform coefficients of the target vehicle;

[0208] Calculate the ratio of the calibration Fourier transform coefficients to the target Fourier transform coefficients.

[0209] Optionally, the weight identification module 1005 is further specifically configured to:

[0210] resampling the target strain spatial domain data to obtain resampled target strain spatial domain data, wherein the spatial interval of each sample point in the resampled target strain spatial domain data is the same as the spatial interval of each sample point in the resampled calibration strain spatial domain data;

[0211] The resampled target strain spatial domain data is subjected to discrete Fourier transform to obtain the target Fourier transform coefficients.

[0212] Optionally, the second determining module 1004 is specifically configured to:

[0213] determining a product of a vehicle speed of a target vehicle and a time in an item of target strain data;

[0214] The product and the strain in the target strain data are used as target strain spatial domain data.

[0215] Optionally, the second determining module 1004 is further specifically configured to:

[0216] Determine first strain data of a first measuring point and second strain data of a second measuring point of a target vehicle on a bridge;

[0217] determining a time difference between a target vehicle passing through a first measuring point and a second measuring point based on a cross-correlation function of the first strain data and the second strain data;

[0218] The ratio of the measuring point distance to the time difference between the first measuring point and the second measuring point is used as the speed of the target vehicle.

[0219] Optionally, the weight identification module 1005 is further specifically configured to:

[0220] Get the vehicle weight of the calibrated vehicle;

[0221] The weight of the target vehicle is determined based on the weight ratio and the vehicle weight of the calibration vehicle.

[0222] For descriptions of the processing flow of each module in the device and the interaction flow between each module, reference can be made to the relevant descriptions in the above method embodiment, which will not be described in detail here.

[0223] The embodiment of the present application processes the strain data to ultimately determine the weight ratio of the target vehicle and the calibration vehicle and determines the weight of the target vehicle based on the weight ratio, thereby getting rid of the dependence on the bridge influence line. The technician can calculate the weight of the target vehicle based on the strain data without obtaining the bridge physical model information, avoiding the difficulty in identifying the vehicle weight caused by the difficulty in obtaining the bridge influence line or the change of the bridge influence line, and realizing more convenient vehicle weight identification. Compared with the existing technology of identifying the vehicle weight through the bridge physical model information, the complexity of the calculation is reduced.

[0224] The present application also provides an electronic device, such as Figure 11 As shown in FIG, a schematic diagram of the electronic device structure provided by an embodiment of the present application includes: a processor 1101, a memory 1102 and a bus. The memory 1102 stores machine-readable instructions executable by the processor 1101 (for example, Figure 10 The device includes the first acquisition module 1001, the first determination module 1002, the second acquisition module 1003, the second determination module 1004 and the execution instructions corresponding to the weight identification module 1005, etc.), when the computer device is running, the processor 1101 communicates with the memory 1102 through a bus, and when the machine-readable instructions are executed by the processor 1101, the above-mentioned bridge weighing method is performed.

[0225] An embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the above-mentioned bridge weighing method are executed.

[0226] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the system and device described above can refer to the corresponding process in the method embodiment, and will not be repeated in this application. In the several embodiments provided in this application, it should be understood that the disclosed system, device and method can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation. For example, multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0227] In addition, the functional units in the various embodiments of the present application can be integrated into a processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. If the function is implemented in the form of 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 the present invention is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk.

[0228] The above is only a specific implementation method of the present application, but the protection scope of the present application is not limited thereto. Any technician familiar with this technical field can easily think of changes or replacements within the technical scope disclosed in this application, which should be covered by the protection scope of the present application.

Claims

1. A bridge dynamic weighing method, characterized in that: The method comprises: The calibration strain data of the calibration vehicle is collected. The calibration strain data is used to characterize the relationship between the strain and time of the bridge when the calibration vehicle passes through the bridge. The calibration strain data is time domain data, expressed as s0(t) = {ε0(0),ε0(Δt),ε0(2Δt),…,ε0[(N0-1)Δt]}, including N0 sampling points, where the time interval is Δt = 1 / f s , f s is the device sampling frequency, (N0-1)Δt is the total sampling time T0; The calibration strain spatial domain data of the calibration vehicle is determined based on the calibration strain data. The calibration strain spatial domain data is used to characterize the relationship between the strain of the bridge when the calibration vehicle passes through the bridge and the distance the calibration vehicle has traveled on the bridge. The calibration strain spatial domain data is expressed as s0(x)={ε0(0),ε0(Δx0),ε0(2Δx0),…,ε0[(N0-1)Δx0]}, where x represents the distance traveled by the first axle of the calibration vehicle, and the spatial interval Δx0=v0Δt=v0 / f s , v0 is the calibrated vehicle speed, (N0-1)Δx0 is the total distance X0 traveled by the calibrated vehicle; collecting target strain data of a target vehicle, wherein the target strain data is used to characterize the relationship between the strain of the bridge and time when the target vehicle passes through the bridge; The target strain spatial domain data of the target vehicle is determined according to the target strain data. The target strain spatial domain data is used to characterize the relationship between the strain of the bridge when the target vehicle passes through the bridge and the distance the calibration vehicle has traveled on the bridge. The target strain data is time domain data, expressed as s1(t) = {ε1(0), ε1(Δt), ε1(2Δt), …, ε1[(N1-1)Δt]}, including N1 sampling points, where the time interval is Δt = 1 / f s , f s is the sampling frequency of the device, and (N1-1)Δt is the total sampling time T1; According to the calibration strain spatial domain data and the target strain spatial domain data at the same measuring point of the bridge, the weight ratio of the target vehicle to the calibration vehicle is determined, and the weight of the target vehicle is determined according to the weight ratio. The target strain spatial domain data is expressed as s1(x)={ε1(0),ε1(Δx1),ε1(2Δx1),…,ε1[(N1-1)Δx1]}, where x represents the distance traveled by the first axle of the calibration vehicle, and the spatial interval Δx1=v1Δt=v1 / f s , v1 is the target vehicle speed, (N1-1)Δx1 is the total distance X1 traveled by the calibration vehicle; Determining a weight ratio between the target vehicle and the calibration vehicle based on the calibration strain spatial domain data and the target strain spatial domain data at the same measuring point of the bridge includes: Obtain calibration strain space domain data and target strain space domain data corresponding to the same measuring point; Determining, based on the calibration strain spatial domain data and the target strain spatial domain data, a ratio of Fourier transform coefficients of strain spatial domain data at the same measuring point of the bridge caused by the target vehicle and the calibration vehicle respectively passing through the bridge at a uniform speed; Taking the ratio of the Fourier transform coefficients at zero frequency as the weight ratio; The vehicle weight is calculated by the following formula: Wherein, m1 is the target vehicle, m0 is the calibration vehicle, r is the ratio of the Fourier transform coefficients, N is the number of sample points after resampling, E1(nΔx) is the resampled target strain spatial domain data, E0(nΔx) is the resampled calibration strain spatial domain data, Δx is the resampled spatial interval, and the spatial interval of the sample points in the resampled target strain spatial domain data is the same as the spatial interval of the sample points in the resampled calibration strain spatial domain data.

2. The method according to claim 1, characterized in that Determining, based on the calibration strain spatial domain data and the target strain spatial domain data, a ratio of Fourier transform coefficients of strain spatial domain data at the same measuring point of the bridge caused by the target vehicle and the calibration vehicle respectively passing the bridge at a uniform speed comprises: performing data resampling and discrete Fourier transform on the calibration strain spatial domain data to obtain calibration Fourier transform coefficients of the calibration vehicle; performing data resampling and discrete Fourier transform on the target strain spatial domain data to obtain target Fourier transform coefficients of the target vehicle; A ratio of the calibration Fourier transform coefficients to the target Fourier transform coefficients is calculated.

3. The method according to claim 2, characterized in that The step of resampling and discrete Fourier transforming the target strain spatial domain data to obtain target Fourier transform coefficients of the target vehicle includes: resampling the target strain spatial domain data to obtain resampled target strain spatial domain data; The resampled target strain spatial domain data is subjected to discrete Fourier transform to obtain the target Fourier transform coefficients.

4. The method according to claim 1, wherein The step of obtaining target strain spatial domain data of the target vehicle according to the target strain data includes: determining a product of a vehicle speed of the target vehicle and a time in a target strain data item; The product and the strain in the one item of target strain data are used as one item of target strain spatial domain data.

5. The method according to claim 4, characterized in that Determining the vehicle speed of the target vehicle includes: Determine first strain data of a first measuring point and second strain data of a second measuring point of the target vehicle on the bridge; determining a time difference between the target vehicle passing through a first measuring point and a second measuring point based on a cross-correlation function of the first strain data and the second strain data; The ratio of the measuring point distance between the first measuring point and the second measuring point to the time difference is used as the speed of the target vehicle.

6. The method according to claim 1, characterized in that Determining the weight of the target vehicle according to the weight ratio includes: Obtaining the vehicle weight of the calibration vehicle; The weight of the target vehicle is determined according to the weight ratio and the vehicle weight of the calibration vehicle.

7. A bridge dynamic weighing device, characterized in that: The device comprises: The first acquisition module is used to collect calibration strain data of the calibration vehicle, and the calibration strain data is used to characterize the relationship between the strain of the bridge and time when the calibration vehicle passes through the bridge. The calibration strain data is time domain data, expressed as s0(t)={ε0(0),ε0(Δt),ε0(2Δt),…,ε0[(N0-1Δt, including N0 sampling points, where the time interval is Δt=1 / fs, fs is the device sampling frequency, and (N0-1)Δt is the total sampling time T0; A first determination module is configured to determine calibration strain spatial domain data of the calibration vehicle based on the calibration strain data, wherein the calibration strain spatial domain data is used to characterize the relationship between the strain of the bridge when the calibration vehicle passes through the bridge and the distance the calibration vehicle has traveled on the bridge. The calibration strain spatial domain data is represented by s0(x)={ε0(0),ε0(Δx0),ε0(2Δx0),…,ε0[(N0-1)Δx0]}, where x represents the distance traveled by the first axle of the calibration vehicle, and the spatial interval Δx0=v0Δt=v0 / f s , v0 is the calibrated vehicle speed, (N0-1)Δx0 is the total distance X0 traveled by the calibrated vehicle; The second acquisition module is used to collect target strain data of the target vehicle. The target strain data is used to characterize the relationship between the strain of the bridge and time when the target vehicle passes through the bridge. The target strain data is time domain data, expressed as s1(t)={ε1(0),ε1(Δt),ε1(2Δt),…,ε1[(N1-1Δt, including N1 sampling points, where the time interval is Δt=1 / fs, fs is the device sampling frequency, and (N1-1)Δt is the total sampling time T1; The second determination module is used to determine the target strain spatial domain data of the target vehicle based on the target strain data. The target strain spatial domain data is used to characterize the relationship between the strain of the bridge when the target vehicle passes through the bridge and the distance the calibration vehicle has traveled on the bridge. The target strain spatial domain data is expressed as s1(x)={ε1(0),ε1(Δx1),ε1(2Δx1),…,ε1[(N1-1)Δx1]}, where x represents the distance traveled by the first axle of the calibration vehicle, and the spatial interval Δx1=v1Δt=v1 / f s , v1 is the target vehicle speed, (N1-1)Δx1 is the total distance X1 traveled by the calibration vehicle; a weight identification module, configured to determine a weight ratio between the target vehicle and the calibration vehicle based on the calibration strain spatial domain data and the target strain spatial domain data at the same measuring point of the bridge, and determine the weight of the target vehicle based on the weight ratio; The weight recognition module is specifically used for: Obtain calibration strain space domain data and target strain space domain data corresponding to the same measuring point; Determining, based on the calibration strain spatial domain data and the target strain spatial domain data, a ratio of Fourier transform coefficients of strain spatial domain data at the same measuring point of the bridge caused by the target vehicle and the calibration vehicle respectively passing through the bridge at a uniform speed; Taking the ratio of the Fourier transform coefficients at zero frequency as the weight ratio; The vehicle weight is calculated by the following formula: Wherein, m1 is the target vehicle, m0 is the calibration vehicle, r is the ratio of the Fourier transform coefficients, N is the number of sample points after resampling, E1(nΔx) is the resampled target strain spatial domain data, E0(nΔx) is the resampled calibration strain spatial domain data, Δx is the resampled spatial interval, and the spatial interval of the sample points in the resampled target strain spatial domain data is the same as the spatial interval of the sample points in the resampled calibration strain spatial domain data.

8. An electronic device, characterized in that: include: A processor, a storage medium and a bus, wherein the storage medium stores program instructions executable by the processor. When the electronic device is running, the processor and the storage medium communicate through the bus, and the processor executes the program instructions to perform the steps of the bridge dynamic weighing method as described in any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the bridge dynamic weighing method according to any one of claims 1 to 6 are executed.

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