Vehicle spatiotemporal distribution information recognition method based on bending strain and shear strain

Abstract

The present invention discloses a method for identifying spatiotemporal distribution information of vehicles based on bending strain and shear strain. The method firstly decouples the measured coupled strain into a single strain on a one-dimensional bridge model, then establishes a complex mapping relationship between the bending strain and the shear strain and basic vehicle parameters according to different strain types, and can effectively identify vehicle information such as the number of axles, the number of vehicles and the distance between vehicles. Finally, the estimated basic vehicle information and the decoupled bending strain on the one-dimensional bridge are combined to finally estimate the spatially distributed vehicle load in real time, thereby realizing the real-time acquisition of the spatiotemporal information of vehicles on the two-dimensional bridge model, and providing the possibility for the prediction of overloaded vehicles.

Description

Technical Field

[0001] The present invention belongs to the technical field of bridge monitoring, and more specifically, relates to a method for identifying vehicle spatiotemporal distribution information based on bending strain and shear strain. Background Art

[0002] Vehicle overloading is one of the main human factors that threaten the safety of in-service bridges. Vehicle overloading not only causes serious damage to roads and bridges, shortens their service life, but may also lead to traffic accidents. Therefore, how to timely and effectively detect vehicle weight and reasonably control overloaded vehicles has become an issue that cannot be ignored in bridge health monitoring.

[0003] Commonly used vehicle weighing methods include static weighing and dynamic weighing. Among them, static weighing requires stopping for detection, which seriously affects the normal passage of road traffic. Therefore, dynamic weighing without stopping has been developed. Dynamic weighing mainly includes pavement dynamic weighing and bridge dynamic weighing. In pavement dynamic weighing, since the weighing sensor is in direct contact with the wheel, the sensor is easily damaged. In contrast, bridge dynamic weighing, which obtains vehicle information by measuring the structural response of the bridge under the action of vehicle load, avoids the key problems in pavement dynamic weighing technology in practical application. After a lot of research and development, the existing bridge dynamic weighing technology has made significant breakthroughs and progress on single-lane bridges, but it is still limited on multi-lane bridges, and most of them only consider identifying the axle information of the vehicle. There is relatively little research on restoring the dynamic spatial distribution of vehicles on the bridge, making it difficult to realize the recognition of vehicle spatiotemporal information in complex and changeable traffic conditions. Summary of the invention

[0004] The present invention is provided to solve the above problems existing in the prior art. Therefore, a method for identifying the spatiotemporal distribution information of vehicles based on bending strain and shear strain is needed to solve the problems of low vehicle information identification accuracy and difficulty in identifying spatiotemporal information of vehicles caused by coupled strain in bridge dynamic weighing technology under complex traffic conditions, and provide a basis for monitoring and early warning of bridge structure health.

[0005] The present invention provides a method for identifying vehicle spatiotemporal distribution information based on bending strain and shear strain, the method comprising:

[0006] Decoupling the strains measured on the 2D bridge model to the independent strains of the 1D bridge model under the same vehicle load;

[0007] Establishing a mapping relationship between bending strain and shear strain and basic vehicle parameters, and using bending strain and shear strain to collaboratively estimate basic vehicle information of each lane, wherein the basic vehicle information includes the number of axles, axle spacing, and vehicle spacing;

[0008] Based on the estimated vehicle basic information and decoupled bending strain on each lane, the vehicle load distributed on all lanes is estimated in real time.

[0009] Furthermore, the step of decoupling the strain measured on the two-dimensional bridge model into an independent strain of the one-dimensional bridge model under the same vehicle load comprises:

[0010] Under the load of each lane, the strain response is expressed as:

[0011]

[0012] Where ε i is the coupled entanglement strain of the i-th lane; is the separation strain of the i-th lane, and the separation strain is the strain on the one-dimensional bridge model with coupled strain decoupled from multi-lane measurements; N is the total number of lanes on the bridge; η ij is the lateral distribution coefficient of the wheel load on the jth lane on the ith lane determined during the calibration process.

[0013] Furthermore, according to formula (1), the expression for determining the separation strain is:

[0014]

[0015] Furthermore, the mapping relationship between the bending strain and the shear strain and the basic parameters of the vehicle is established, and the basic information of the vehicle in each lane is estimated collaboratively using the bending strain and the shear strain, including:

[0016] When a vehicle with n axles passes over the bridge, when the i-th axle acts on the peak value of the bending strain influence line, the bending strain at the monitoring point is determined as:

[0017]

[0018] Where P j is the axle weight of the jth axis; x j is the position of each axis of the jth axis, and x1...x i-1 , x i They are (m+d i-1 +……d1)……(m+d i-1 ), m, where d1…d i-1 is the axis spacing of each axis, m is the center distance between the monitoring point and the support at the bridge end; E is the elastic modulus of the structural material; y is the distance from any point on the node surface to the neutral axis; I is the section moment of inertia; L is the center distance between the supports at both ends of the simply supported beam bridge.

[0019] When the i-th axis acts on the peak value of the shear strain influence line, the peak value of the shear strain at the monitoring point is:

[0020]

[0021] Where G and S are the shear modulus and cross-sectional area of ​​the material, respectively.

[0022] Furthermore, the bending strain of the monitoring point is determined by the following method:

[0023] Take monitoring point A as the monitoring point for bending strain and shear strain. The distance between monitoring point A and the center of the bridge end support is m. When the load acts on a simply supported beam bridge, the load position is x, and the distance between the loads is d. i are both greater than x, then the strain influence line formula of monitoring point A is:

[0024]

[0025] Where L is the center distance between the two ends of the simply supported beam bridge, IL M is the bending strain influence line, IL V is the shear strain influence line;

[0026] When the i-th axis acts on the peak value of the bending strain influence line, the bending strain at the monitoring point A is:

[0027]

[0028] Where P i is the axle weight of the i-th axle;

[0029] The bending strain of the monitoring point can be obtained by simplifying equation (5) as equation (6).

[0030] Furthermore, the shear strain peak value of the monitoring point is determined by the following method:

[0031] When the i-th axis acts on the peak value of the shear strain influence line, the peak value of the shear strain at the monitoring point A is:

[0032]

[0033] The shear strain peak value of the monitoring point is obtained by simplifying equation (9) as shown in equation (10).

[0034] Furthermore, the real-time estimation of vehicle loads distributed on all lanes based on the estimated basic vehicle information and the decoupled bending strain on each lane includes:

[0035] Calculate the vehicle speed at the bridge approach end based on the time of the shear strain peak point;

[0036] The first-order difference operation is performed on the bending strain time history response at the set monitoring point in the support area of ​​the bridge end to identify the number of vehicles and axles passing the bridge. The first-order difference operation is t k+1The moment-strain response at time t minus k The moment-strain response value at time;

[0037] The vehicle wheelbase is determined according to the vehicle speed at the approaching end and the shear strain peak point time corresponding to the front and rear axles of the vehicle;

[0038] According to the peak data corresponding to each axle at the monitoring point, the relationship between the strain data and the axle weight is analyzed, and the dynamic response correction coefficient λ at the monitoring point is established;

[0039] The balance equation of the vehicle's front and rear axles acting on the monitoring point at the bridge entrance is established, and the balance equation is solved based on the dynamic response correction coefficient λ to determine the axle weight.

[0040] Furthermore, the calculation formula of the vehicle speed at the bridge approach end is:

[0041]

[0042] Where t A,max and t B,max are the shear strain peak time of monitoring point A and monitoring point B, respectively, and l is the distance between monitoring point A and monitoring point B;

[0043] The calculation formula of the vehicle wheelbase is:

[0044] d=v*(t h,max -t q,max ) (14)

[0045] Where t q,max and t h,max are the shear strain peak points corresponding to the front and rear axles of the vehicle, and v is the vehicle speed at the approaching bridge end.

[0046] Furthermore, the dynamic response correction coefficient λ at the monitoring point is expressed as:

[0047]

[0048] Where P b1 , P b2 are the front and rear axle weights of the calibrated vehicle, d b is the wheelbase of the vehicle, ε b2 To calibrate the strain peak value corresponding to the rear axle of the vehicle, E is the elastic modulus of the structural material, I is the section moment of inertia, L is the center distance between the supports at both ends of the simply supported beam bridge, and m is the center distance between the monitoring point and the support at the bridge entrance end.

[0049] Furthermore, the establishment of a balance equation when the front axle and the rear axle of the vehicle act on the monitoring point at the approaching bridge end, and solving the balance equation based on the dynamic response correction coefficient λ to determine the axle weight includes:

[0050] When the front and rear axles of the vehicle act on the monitoring point A at the approaching bridge, the equilibrium equation is established as follows:

[0051]

[0052] In the formula and is the peak value of bending strain generated when the front axle and rear axle act on the monitoring point respectively; R1 and R2 are the support reaction forces of the left end support when the front axle and rear axle act on the monitoring point respectively; P1 and P2 are the axle weights of the front axle and rear axle of the two-axle vehicle to be tested; x 1,1 is the position of the front axle of the vehicle when it acts on the monitoring point, x 1,1 =m,x 2,1 and x 2,2 are the positions of the front and rear axles of the vehicle when the front axle of the vehicle acts on the monitoring point, respectively, 2,1 =m+d、x 2,2 =m; λ is the dynamic response correction coefficient of the rear axle at the vehicle measuring point;

[0053] Solving the equilibrium equation by combining equations (15) and (16) yields:

[0054]

[0055] According to formula (18), the calculation expression of the axle weight of the i-th axle when n axle loads act is derived:

[0056]

[0057] In the formula is the peak bending strain corresponding to the i-th axis; P j is the axle weight of the first i-1 axles; x i,j is the position of the first i-1 axes when the i-th axis acts on the monitoring point near the bridge end support, x i,1 =(m+d i-1 +…+d1), x i,2 =(m+d i-1 +…+d2),…,x i,i-1 =(m+d i-1 ); i-1 is the dynamic response correction coefficient of the i-1th axis to the i-th axis.

[0058] The present invention has at least the following beneficial effects:

[0059] (1) The present invention proposes a new identification method, which establishes a dynamic mapping relationship between strain response and vehicle load loading mode based on the bending strain and shear strain of the bridge structure itself, and builds a vehicle detection network that can identify the spatiotemporal information of vehicles. Compared with the existing methods, the vehicle information identification method proposed in the present invention can not only effectively identify the axle information of vehicles traveling on the bridge, but also restore the spatiotemporal distribution model of the vehicles on the bridge, and the effectiveness of the method is verified using finite element models and experimental scale models.

[0060] (2) The present invention decouples the measured coupled strain into a single strain on a one-dimensional bridge model, and then establishes a complex mapping relationship between bending strain and shear strain and basic vehicle parameters according to different strain types, and can effectively identify vehicle information such as the number of axles, the number of vehicles, and the distance between vehicles. The estimated basic vehicle information and the decoupled bending strain on the one-dimensional bridge are then combined to finally estimate the spatially distributed vehicle load in real time. In this way, the real-time acquisition of vehicle spatiotemporal information on a two-dimensional bridge model is achieved, which makes it possible to predict overloaded vehicles.

[0061] (3) The present invention can effectively solve the problem of large vehicle load identification error caused by inaccurate identification of vehicle basic parameters by extracting shear strain and bending strain. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 A flow chart of a method for identifying vehicle spatiotemporal distribution information based on bending strain and shear strain according to an embodiment of the present invention is shown;

[0063] Figure 2 A simplified 2D diagram of multi-lane coupled strain according to an embodiment of the present invention is shown;

[0064] Figure 3 A simplified diagram of the calculation of bending strain and shear strain influence lines according to an embodiment of the present invention is shown;

[0065] Figure 4 A simplified diagram of the calculation of bending strain and shear strain of a monitoring point according to an embodiment of the present invention is shown;

[0066] Figure 5 shows a bending strain peak response diagram of the front axle at the monitoring point according to an embodiment of the present invention;

[0067] Figure 6 A finite element model of a 25m three-lane concrete simply supported T-beam bridge according to an embodiment of the present invention is shown, and the unit of the dimension marking in the figure is cm;

[0068] Figure 7 shows a coupled strain separation image at a monitoring point according to an embodiment of the present invention;

[0069] Figure 8 shows a shear strain time history curve image at a monitoring point according to an embodiment of the present invention;

[0070] Fig. 9 shows a first-order difference value curve image of bending strain at a monitoring point according to an embodiment of the present invention;

[0071] Fig.10 shows a bending strain time history curve diagram at a monitoring point according to an embodiment of the present invention;

[0072] Fig.11 A vehicle spatial distribution diagram according to an embodiment of the present invention is shown. DETAILED DESCRIPTION

[0073] In order to enable those skilled in the art to better understand the technical solution of the present invention, the present invention is described in detail below in conjunction with the accompanying drawings and specific embodiments. The embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings and specific embodiments, but are not intended to limit the present invention. For the various steps described herein, if there is no necessity for a causal relationship between each other, the order in which they are described as examples herein should not be regarded as a limitation, and those skilled in the art should know that they can be adjusted in order, as long as the logic between them is not destroyed, resulting in the inability to implement the entire process.

[0074] Figure 1 FIG. 4 is a flow chart showing a method for identifying vehicle spatiotemporal distribution information based on bending strain and shear strain according to an embodiment of the present invention. Figure 1 As shown, an embodiment of the present invention provides a method for identifying the spatiotemporal distribution information of vehicles based on bending strain and shear strain. The method first decouples the strain measured on the two-dimensional bridge model into the independent strain of the one-dimensional bridge model under the action of its vehicle load. By establishing a mapping relationship between the bending strain and the shear strain and the basic parameters of the vehicle, the two decoupled strains are used to collaboratively estimate the basic information of the vehicle on each lane, including the number of axles, axle spacing, and vehicle spacing. Finally, the basic vehicle information estimated on each lane and the decoupled bending strain are combined to estimate the vehicle load distributed on all lanes in real time. When the method is implemented specifically, it includes the following steps 1 and 2, which are described in detail as follows:

[0075] Step 1: Multi-vehicle coupling strain separation.

[0076] When multiple vehicles are running on multiple lanes, due to the spatial distribution effect of the bridge, the strain measured on each beam is the coupling effect caused by all vehicles in the lateral direction. The distribution ratio of the load on different lanes is determined by the lateral relative stiffness ratio of the bridge and the position of the vehicle. In order to simplify this calculation model of the two-dimensional bridge, the lateral distribution coefficient η is used to characterize the size of the lateral distribution ratio of the bridge. In this way, the measured coupled strain is decoupled into the strain on the one-dimensional bridge model, such as Figure 2 shown.

[0077] Under the load of each lane, the strain response of the structure can be expressed as follows according to the influence line theory:

[0078]

[0079] Where ε i is the coupled entanglement strain of the i-th lane; is the separation strain of the i-th lane, which is the strain on the one-dimensional bridge model decoupled from the coupled strain measured by multiple lanes; N is the total number of lanes on the bridge; η ij is the lateral distribution coefficient of the wheel load on the jth lane determined during the calibration process on the ith lane, which can be obtained by taking a calibration vehicle with known parameters to calibrate each lane of the bridge. Solving equation (1), the separation strain expression can be obtained as follows:

[0080]

[0081] Step 2: Identify basic vehicle information. Step 2 specifically includes Step 2.1 and Step 2.2, which are described in detail as follows:

[0082] Step 2.1, establish the mapping relationship between different types of strains and basic vehicle parameters.

[0083] In order to solve the uncertainty problem of loading mode of mobile vehicle load, the strain value generated by the vehicle load when different axes of the vehicle act on the peak value of the strain influence line is calculated, the loading mode of the vehicle load at the strain peak moment of different types of strain is determined, and the mapping relationship model between different types of strain and basic vehicle parameters is established.

[0084] For a simply supported beam bridge, the position of unit A near the bridge end support is taken as the monitoring point of bending strain and shear strain, and the distance between A and the center of the bridge end support is m. When the load acts on the simply supported beam bridge, the load action position is x, and the distance between the loads is d i are both greater than x, then the strain influence line formula at point A is:

[0085]

[0086] Where L is the center distance between the supports at both ends of the simply supported beam bridge, m is the center distance between the unit monitoring point near the support at the bridge end and the support at the bridge end, and x is the center distance between the load action point and the support at the bridge end.

[0087] When a vehicle with n axles passes over a bridge, the i-th axle acts at the peak of the bending strain influence line due to d i are both greater than m, so x ≥ m, then the bending strain at the measuring point is:

[0088]

[0089] Where P j is the axle weight of the jth axis; x j is the position of each axis of the jth axis, and x1...x i -1,x i They are (m+d i-1 +……d1)……(m+d i-1 ), m, where d1…d i-1 is the interaxial distance between the axes; E is the elastic modulus of the structural material; y is the distance from any point on the node surface to the neutral axis; I is the section moment of inertia.

[0090] According to formula (6), the bending strain value generated by the i-th axis is subtracted from the bending strain value generated by the i-1-th axis:

[0091]

[0092] make We can get: Since E, I, L, y, and m are structural correlation coefficients and monitoring point locations, all greater than 0, the above formula can be simplified to:

[0093]

[0094] In the formula, m is the unit near the bridge end support, m is much smaller than L, and d i-1 is the distance between the i-th and i-1-th axles of the vehicle, which is also much smaller than L, so Right now Pi is the axle weight of the i-th axle of the vehicle, P i >0, that is, formula (8) holds true, It can be proved that: the bending strain value generated by the i-th axis is always greater than the bending strain value generated by the i-1-th axis, that is, the bending strain value generated by the last axis of the n axes acting on the monitoring point near the bridge end support is the largest.

[0095] When the i-th axis acts on the peak value of the shear strain influence line, the peak value of the shear strain at the monitoring point is:

[0096]

[0097] Where G and S are the shear modulus and cross-sectional area of ​​the material, respectively.

[0098] According to formula (10), the shear strain value generated by the i-th axis is subtracted from the shear strain value generated by the i-1-th axis:

[0099]

[0100] make We can get: Where G and S are structural correlation coefficients, both greater than 0, the above formula can be simplified to:

[0101]

[0102] Given m and d i-1 are much smaller than L, then Right now And P i-1 is the axle weight of the i-1th axle of the vehicle, P i-1 >0, that is, formula (12) holds true, It can be proved that: the shear strain value generated when the rear axle of the vehicle acts on the monitoring point is greater than the shear strain value generated when the front axle acts on the monitoring point, that is, the shear strain peak value of the monitoring point near the bridge end support of each vehicle when driving on the bridge is generated when the rear axle of the vehicle acts on the monitoring point, and the vehicle load loading mode of each monitoring point is the same.

[0103] Step 2.2, identification of basic vehicle parameters.

[0104] According to the above shear strain mapping relationship, it can be known that the shear strain peaks at the monitoring points near the bridge end support on the bridge are all generated when the rear axle of the vehicle load acts on the monitoring points. Therefore, the two points A and B near the bridge end of the simply supported bridge are taken as shear strain monitoring points, with a center distance of l. By extracting the time of the shear strain peak point, the vehicle speed at the bridge end can be calculated as follows (since the distance between the two monitoring points is relatively close, the speed change can be ignored):

[0105]

[0106] Where t A,max and t B,max are the shear strain peak time of point A and point B respectively.

[0107] By extracting the bending strain time history response at the monitoring point near the bridge end support and performing a first-order difference operation (i.e., t k+1 The moment-strain response at time t minus k The moment-strain response value at the moment can clearly identify the number of vehicles and axles passing through the bridge. Therefore, according to formula (16), the wheelbase calculation expression can be obtained as:

[0108] d=v*(t h,max -t q,max ) (14)

[0109] Where t q,max and t h,max They are the shear strain peak point times corresponding to the front and rear axles of the vehicle.

[0110] According to the above bending strain mapping relationship, it can be known that the bending strain peak value at the monitoring point near the bridge end support is generated when the last axle acts on the monitoring point. Therefore, a simply supported beam bridge is taken as the research object. When a two-axle vehicle moves on the simply supported beam bridge, the position of the vehicle axle load is set as x. The bending strain response peak values ​​generated by the front and rear axles are as follows: Figure 5 As shown (d>x):

[0111] During the movement of the vehicle, the front axle of the vehicle will have a dynamic impact on the rear axle, resulting in inaccurate strain response data of the rear axle. Therefore, this paper proposes a dynamic response correction coefficient λ that can correct the strain response of the rear axle to correct the dynamic impact of the front axle on the rear axle. The λ coefficient can be obtained by calibrating a known vehicle, and the calibrated vehicle axle weight is P b1 , P b2 , wheelbase is d b During the calibration process, by recording the peak data corresponding to each axle at the monitoring point, analyzing the relationship between strain data and axle weight, the dynamic response correction coefficient λ at the monitoring point is established as:

[0112]

[0113] Where P b1 , P b2 are the front and rear axle weights of the calibrated vehicle, d b is the wheelbase of the vehicle, ε b2 To calibrate the strain peak value corresponding to the rear axle of the vehicle.

[0114] Depend on Figure 5 It can be obtained that when the front axle and rear axle of the vehicle act on the monitoring point A at the bridge entrance, the equilibrium equation is established as:

[0115]

[0116] In the formula and is the peak value of bending strain generated when the front axle and rear axle act on the monitoring point respectively; R1 and R2 are the support reaction forces of the left end support when the front axle and rear axle act on the monitoring point respectively; P1 and P2 are the axle weights of the front axle and rear axle of the two-axle vehicle to be tested; x 1,1 is the position of the front axle of the vehicle when it acts on the monitoring point, x 1,1 =m.x 2,1 and x 2,2 are the positions of the front and rear axles of the vehicle when the front axle of the vehicle acts on the monitoring point, respectively, 2,1 =m+d、x 2,2 =m; λ is the dynamic response correction coefficient of the rear axle at the vehicle measuring point.

[0117] Solving the equilibrium equation by combining equations (15) and (16) yields:

[0118]

[0119] According to formula (18), the calculation expression of the axle weight of the i-th axle when n axle loads act can be derived:

[0120]

[0121] In the formula is the peak bending strain corresponding to the i-th axis; P j is the axle weight of the first i-1 axles; x i,j is the position of the first i-1 axes when the i-th axis acts on the monitoring point near the bridge end support, x i,1 =(m+d i-1 +…+d1), x i,2 =(m+d i-1 +…+d2),…,x i,i-1 =(m+d i-1 ); i-1 is the dynamic response correction coefficient of the i-1th axis to the i-th axis.

[0122] Through the above vehicle information identification method, it can be seen that by extracting the dynamic strain response time-history data at the monitoring point at the bridge entrance end at the time t1-t2 in each time period, the driving conditions of each vehicle on the bridge can be accurately identified and judged, and the vehicle spatial distribution information such as the number of vehicles traveling on each lane, the axle spacing and the vehicle spacing can be identified, and the spatiotemporal distribution model of vehicles on the entire bridge in each time period can be accurately restored.

[0123] The following embodiment of the present invention will verify the effectiveness of the proposed vehicle spatiotemporal information recognition method by simulating a 25-meter-long uniform-section T-shaped simply supported beam bridge.

[0124] The main beam of the bridge is made of C55 concrete. The single T beam is divided into 25 units, each 1 meter long. Starting from the support, the bridge is equipped with a diaphragm every 5 meters. The height of the diaphragm is 1.05 meters from the top plate of the T beam flange, and the thickness is 0.15 meters. Its finite element model and main beam cross-section structure diagram are shown below. Figure 8 As shown in Figure 2, bending strain monitoring points are arranged at the first unit span of the bottom of the bridge No. 2, No. 3 and No. 4 main beams. At the same time, shear strain monitoring points are arranged at the first and fourth unit spans along the length of the bridge. Figure 6 As shown in the figure, the straight line and circle represent the position A of the bending strain monitoring point and the shear strain monitoring point respectively. i , B i The center spacing of shear strain monitoring points is 3m.

[0125] In the vehicle model design, for some three-axle vehicles with a small rear axle wheelbase, this embodiment adopts the method of combining the two rear axle weights into a total axle weight to simplify the axle group, and takes the center point of the rear axle spacing as the total weight action position of the rear axle group, so as to reduce the impact of the small rear axle wheelbase of the three-axle vehicle on the recognition algorithm. According to the influencing factors such as vehicle wheelbase and axle weight, three different types of vehicles are designed here, as shown in Table 1:

[0126] Table 1 Vehicle model parameters

[0127]

[0128] Vehicle 3 is simplified from a three-axle vehicle with axle spacing of 4m and 2m. In order to determine the reliability of the proposed method, the influence of speed, number and spacing on the recognition accuracy is fully considered. Four working conditions are designed this time, as shown in Table 2:

[0129] Table 2 Working condition design

[0130]

[0131] Since multi-lane bridges have strain entanglement problems when multiple vehicles are driving, strain dissociation processing is first performed on the strain data collected at the monitoring points. The lateral distribution coefficient η of each lane can be determined by a calibration vehicle ij At the same time, according to the above four different driving conditions, the coupled strain response time history data of the beam bottom monitoring point from time t1 to time t2 are extracted and brought into the lateral distribution coefficient η of each lane. ij Dissociation calculation is performed, and the strain curve after separation is as follows Figure 7 as shown, and it is applicable to the single lane bridge theory.

[0132] According to the distribution of the above four different driving conditions, the shear strain and bending strain data of the monitoring point at the bridge entrance end from t1 to t2 obtained by decoupling separation are further processed, and the corresponding shear strain time history curve, bending strain time history curve and bending strain first-order difference value image are plotted as shown in Figure 2. Fig. 9 shown.

[0133] according to Figures 8 to 10 The shear strain peak point and bending strain peak point at the monitoring point in each working condition can be identified. By calibrating a vehicle with known axle information (P1 = 5KN, P2 = 9KN, d = 6m) passing through the model bridge, its structural stiffness coefficient ζ and rear axle dynamic response correction coefficient λ are calibrated as follows: 1, 3 lanes: ζ = 1.136x1010, λ = 1.17563; 2 lanes: ζ = 1.19564x1010, λ = 1.2293. According to theoretical derivation, the axle information of the vehicle under each working condition can be calculated as follows:

[0134] Table 3 Vehicle speed and wheelbase recognition results

[0135]

[0136] Table 4 Vehicle axle weight and total weight recognition results

[0137]

[0138]

[0139] According to the recognition results in Tables 3 and 4, the recognition errors of vehicle speed, wheelbase and axle weight under various working conditions are all less than 8.5%, which shows that the vehicle information recognition method proposed in this paper can effectively recognize vehicle information such as vehicle speed, wheelbase and axle weight under working conditions of different complexity. At the same time, it can be seen from the error results in the table that when the speed is 5m / s, most of the vehicle speed recognition results are within 5%, while the recognition error increases significantly when the speed is 10m / s and 20m / s, which shows that the accuracy of the present invention is related to the speed, and the lower the speed, the more accurate the recognition. In addition, the maximum total weight recognition error in the table is 5.27%, which shows that the present invention has high accuracy and robustness in vehicle gross weight recognition.

[0140] Based on the above vehicle axle load information identification content, it can be known that: by extracting the dynamic strain response time history data at the bridge end monitoring point at time t1-t2 under various working conditions, the spatiotemporal information of each vehicle can be accurately identified, and the vehicle spatial distribution model of the entire bridge at time t1-t2 in each time period can be accurately restored based on the spatiotemporal distribution information of the vehicle, such as Fig.11 shown.

[0141] Based on the above identified vehicle spatial distribution information, the following can be drawn: Fig.11 The vehicle spatial distribution model diagram shown in the figure can clearly show the driving conditions of vehicles on the bridge in different time periods, and at the same time show the spatial position distribution of vehicles on the bridge during the monitoring period. It can effectively monitor the dynamic distribution of mobile vehicles on the bridge and generate a large amount of relevant traffic data, which can help the supervision of traffic flow and the analysis and prediction of vehicle overload.

[0142] The above description is intended to be illustrative rather than restrictive. For example, the above examples (or one or more of them) can be used in combination with each other. For example, those of ordinary skill in the art can use other embodiments when reading the above description. In addition, in the above-mentioned specific embodiments, various features can be grouped together to simplify the present invention. This should not be interpreted as a feature of an invention that is not claimed for protection being necessary for any claim. On the contrary, the subject matter of the present invention may be less than all the features of the embodiments of a specific invention. Thus, the following claims are incorporated into the specific embodiments as examples or embodiments, wherein each claim is independently used as a separate embodiment, and it is considered that these embodiments can be combined with each other in various combinations or arrangements. The scope of the present invention should be determined with reference to the full scope of the equivalent forms of the appended claims and these claims.

Claims

1. A method for identifying vehicle spatiotemporal distribution information based on bending strain and shear strain, characterized in that: Decoupling the strain measured on the 2D bridge model to the bending and shear strains of the 1D bridge model under the same vehicle load; Establishing a mapping relationship between bending strain and shear strain and basic vehicle parameters, and using bending strain and shear strain to collaboratively estimate basic vehicle information of each lane, wherein the basic vehicle information includes the number of axles, vehicle wheelbase, and vehicle spacing; Based on the estimated basic vehicle information and decoupled bending strain on each lane, the vehicle load distributed on all lanes is estimated in real time; The method of estimating the vehicle loads distributed on all lanes in real time based on the estimated basic vehicle information and the decoupled bending strain on each lane includes: Calculate the vehicle speed at the bridge approach end based on the time of the shear strain peak point; The bending strain response value at the set monitoring point in the support area at the approaching end is subjected to a first-order difference operation to identify the number of vehicles and axles passing through the bridge. The first-order difference operation is t k+1 The moment-strain response at time t minus k The moment-strain response value at time; The vehicle wheelbase is determined according to the vehicle speed at the approaching end and the shear strain peak point time corresponding to the front and rear axles of the vehicle; According to the peak data corresponding to each axle at the monitoring point, the relationship between the strain data and the axle weight is analyzed, and the dynamic response correction coefficient λ at the monitoring point is established; Establish the balance equation when the front and rear axles of the vehicle act on the monitoring point at the bridge entrance, and solve the balance equation based on the dynamic response correction coefficient λ to determine the axle weight; The dynamic response correction coefficient λ at the monitoring point is expressed as: Where P b1 , P b2 are the front and rear axle weights of the calibrated vehicle, d b is the wheelbase of the vehicle, ε b2 To calibrate the strain peak value corresponding to the rear axle of the vehicle, E is the elastic modulus of the structural material; y is the distance from any point on the node surface to the neutral axis; I is the section moment of inertia; L is the center distance between the supports at both ends of the simply supported beam bridge, and m is the center distance between the monitoring point and the support at the bridge entrance end.

2. The method according to claim 1, characterized in that The mapping relationship between the bending strain and the shear strain and the basic parameters of the vehicle is established, and the basic information of the vehicle in each lane is estimated by using the bending strain and the shear strain in a coordinated manner, including: When a vehicle with n axles passes over the bridge, when the i-th axle acts on the peak value of the bending strain influence line, the bending strain at the monitoring point is determined as: Where P j is the axle weight of the jth axle; x j is the action position of the jth axis, and x1…x i-1 , x i They are (m+d i-1 +……d1)……(m+d i-1 ), m, where d1…d i-1 is the wheelbase of each axle; When the i-th axis acts on the peak value of the shear strain influence line, the peak value of the shear strain at the monitoring point is: In the formula, G and S are the shear modulus and cross-sectional area of ​​the material, respectively, and P i is the axle weight of the i-th axle.

3. The method according to claim 2, characterized in that The bending strain at the monitoring point is determined by the following method: Take monitoring point A as the monitoring point for bending strain and shear strain. When the load acts on a simply supported beam bridge, assume that the load position is x, and the distance between loads is greater than x. Then the strain influence line formula of monitoring point A is: Where IL M is the bending strain influence line, IL V is the shear strain influence line; When the i-th axis acts on the peak value of the bending strain influence line, the bending strain at the monitoring point A is: The bending strain of the monitoring point can be obtained by simplifying equation (5) as equation (6).

4. The method according to claim 3, characterized in that The shear strain peak value at the monitoring point is determined by the following method: When the i-th axis acts on the peak value of the shear strain influence line, the peak value of the shear strain at the monitoring point A is: The shear strain peak value of the monitoring point is obtained by simplifying equation (9) as shown in equation (10).

5. The method according to claim 1, characterized in that The calculation formula for the vehicle speed at the bridge approach end is: Where t A,max and t B,max are the shear strain peak time of monitoring point A and monitoring point B, respectively, and l is the distance between monitoring point A and monitoring point B; The calculation formula of the vehicle wheelbase is: d=v*(t h,max -t q,max ) (14) Where t q,max and t h,max are the shear strain peak points corresponding to the front and rear axles of the vehicle respectively, and v is the vehicle speed at the approaching bridge end.

6. The method according to claim 1, characterized in that The method of establishing a balance equation when the front axle and the rear axle of the vehicle act on the monitoring point at the bridge entrance end, and solving the balance equation based on the dynamic response correction coefficient λ to determine the axle weight includes: When the front and rear axles of the vehicle act on the monitoring point A at the approaching bridge, the equilibrium equation is established as follows: In the formula and is the peak value of bending strain generated when the front axle and rear axle act on the monitoring point respectively; R1 and R2 are the support reaction forces of the left end support when the front axle and rear axle act on the monitoring point respectively; P1 and P2 are the axle weights of the front axle and rear axle of the two-axle vehicle to be tested; x 1,1 is the position of the front axle of the vehicle when it acts on the monitoring point, x 1,1 =m,x 2,1 and x 2,2 are the positions of the front and rear axles of the vehicle when the front axle of the vehicle acts on the monitoring point, respectively, 2,1 =m+d、x 2,2 =m; Solving the equilibrium equation by combining equations (15) and (16) yields: According to formula (18), the calculation expression of the axle weight of the i-th axle when n axle loads act is derived: In the formula is the peak bending strain corresponding to the i-th axis; x i,j is the position of the jth axis when the i-th axis acts on the monitoring point near the bridge end support, x i,1 =(m+d i-1 +…+d1), x i,2 =(m+d i-1 +…+d2),…,x i,i-1 =(m+d i-1 ); i-1 is the dynamic response correction coefficient of the i-1th axis to the i-th axis; P j is the axle weight of the jth axle; d1…d i-1 is the wheelbase of each axle.

Images