31 results about "Influence line" patented technology

The invention discloses a bridge structure monitoring method based on multi-source data and digital twinning and a related device, and relates to the technical field of bridge engineering.The method comprises the steps that an initial finite element model of a target bridge is constructed based on a design drawing and structural parameters of the target bridge, and the initial finite element model of the target bridge is constructed based on the initial finite element model and preset load conditions; calculating to obtain simulation mechanical response data of each grid node of the target bridge; based on the simulation mechanical response data and the obtained actually measured mechanical response data of each grid node of the target bridge, obtaining a corrected finite element model; inputting the obtained traffic load data passing through the target bridge into a digital twinborn calculation model constructed based on the corrected influence line data for numerical calculation to obtain an overall structure response cloud picture and a structure response-time curve of the key monitoring point, and fusing the overall structure response cloud picture and the structure response-time curve with the obtained three-dimensional visualization model to obtain a three-dimensional visualization model; and obtaining the structural state of the target bridge. According to the invention, accurate monitoring and real-time state evaluation of the bridge structure are realized.

The invention discloses a bridge bearing capacity dynamic evaluation method based on multi-source monitoring data driving, and aims to solve the problem that the bearing evaluation precision is difficult to guarantee under a sparse sensing coverage condition. According to the method, through cross-modal attention alignment guided by event anchor points, mask codes influencing line and propagation time delay constraints and geometric position coding, Green function kernels and time-varying boundary flexibility latent variables are introduced into a physical constraint neural operator model, symplectic integral propulsion is adopted, and block shape-preserving interval estimation and order-preserving calibration weighted according to working conditions are adopted. According to the method, the full-bridge space-time response and the bearing utilization coefficient are calculated, the risk level and the load limiting suggestion are output, and the technical effects of reliability improvement, physical consistency and long-time energy stability evaluation under the complex working conditions and the low signal-to-noise ratio are achieved.

This invention discloses a method for assessing the load-bearing capacity of bridges under random traffic flow, belonging to the technical field of bridge load-bearing capacity assessment. This method improves the accuracy and efficiency of the assessment by extracting the bridge deflection influence line and calculating the compliance matrix through traffic flow statistics, Monte Carlo simulation, finite element analysis, and signal processing. Employing non-destructive testing technology, this method provides real-time health status of the bridge. By analyzing dynamic response data during heavy vehicle travel and combining it with the deflection influence line model, the method predicts the bridge's load-bearing limit and potential damage areas, providing a scientific basis for bridge safety assessment and maintenance. This invention is characterized by high efficiency, accuracy, and strong applicability, avoiding the problems of long testing times, traffic disruption, and large workload associated with traditional static load tests. It is suitable for the load-bearing capacity assessment and condition monitoring of small and medium-span bridges.

The present application relates to the technical field of bridge health monitoring and detection, and discloses a prefabricated assembled beam bridge longitudinal damage rapid diagnosis method, which comprises the following steps: collecting actual structure parameters of a bridge, establishing a bridge finite element calculation model for calculating a theoretical strain influence line; arranging strain measuring points at the longitudinal midspan of the two outer side beams and the middle beam of the prefabricated assembled beam, and performing a pseudo-static loading test; extracting the strain of the beam bridge strain measuring points, fitting and drawing a strain influence line; calculating the total strain meters of the two outer side beam strain measuring points; calculating the total strain meter change amplitude ΔS of the two outer side beam measuring points; establishing a ΔS column chart of the two in the same coordinate axis, and comparing with a longitudinal damage qualitative diagnosis graph system to obtain a qualitative diagnosis result. The prefabricated assembled beam bridge longitudinal damage rapid diagnosis method has the advantages of short diagnosis time, no interruption of traffic, improved economy, realization of rapid comprehensive diagnosis of the prefabricated assembled beam bridge longitudinal damage, and improved diagnosis accuracy.

The invention relates to the technical field of highway bridge safety monitoring, and discloses a bridge dynamic weighing algorithm based on a regularization algorithm. According to the method, a penalty term is added into an error function to obtain an axle load calculation formula with a regularization matrix, and the regularization matrix is determined by an axle load covariance matrix and a load response covariance matrix. The method specifically comprises the steps of obtaining influence line distribution through a calibration test; giving an initial regularization matrix to obtain an initial axle weight; calculating a load response covariance matrix based on the influence line distribution, the initial axle load and the measurement noise, and iterating a stable axle load covariance matrix in combination with a preset initial axle load covariance matrix; generating a regularization matrix according to the load response covariance matrix and the updated axle load covariance matrix, and calculating a new axle load; and repeating the iteration process until the axle load update difference value is smaller than a preset value, and finally outputting an axle load result. According to the invention, the axle load identification precision of the bridge dynamic weighing system is effectively improved.

This application provides a bridge dynamic weighing algorithm based on maximum entropy regularization. The steps include: First, obtain the measured response M of the bridge when the vehicle crosses the bridge m and the influence line matrix IL; Second, use M m and IL to calculate the initial value A of the axle weight 0 , and define the initial value r of the regularization parameter i=1 , where i represents the number of times of the main loop; Third, enter the sub-loop, substitute r i and A 0 into the iterative formula of the non-linear conjugate gradient method for calculation until the axle weight converges, and the absolute value of the difference between the axle weights obtained from the previous and the current iterations is less than e, that is: |A i k - A i k‑1 | < e. Assign the axle weight A i k at the k-th iteration after the convergence of the sub-loop to A i ; Fourth, substitute A i into the Regińska formula to obtain the parameter V, and calculate the next regularization parameter r i+1 ; Fifth, judge whether i is greater than 10. If not, substitute r i=i+1 into step three, and repeat the calculation process of steps three to five; If so, draw the r-V curve; Sixth, observe whether there is a minimum value in the curve. If not, substitute r i=i+1 into step three, and repeat the calculation process of steps three to five; If there is, output the axle weight corresponding to the minimum value and use it as the axle weight identification result.

The present application relates to the technical field of bridge, especially to a bridge dynamic calibration coefficient calculation method, system and device based on space-time characteristics and a storage medium, the method comprises: obtaining a theoretical displacement change value caused by temperature according to main beam temperature time series data; correcting the main beam displacement time series response data by using the theoretical displacement change value to obtain the corrected main beam displacement measured response value; obtaining dynamic load time series distribution data and time-varying influence line, and obtaining a theoretical displacement value based on real operating conditions and bridge time-varying state; obtaining a time series sequence of calibration coefficients according to the corrected main beam displacement measured response value and the theoretical displacement value; dividing the time series sequence of calibration coefficients into windows and extracting statistical characteristics to obtain a representative calibration coefficient corresponding to each window, and fusing the representative calibration coefficient corresponding to each window to obtain a final comprehensive representative calibration coefficient.

This invention discloses a method, device, equipment, and storage medium for identifying abnormal states of light rail bridges. The method includes the following steps: for bridges with the same structural form and span arrangement, monitoring data of each measuring point on the bridge is acquired based on dynamic strain measuring points set at the same control section and spatial location on the bridge; based on the monitoring data, the dynamic strain response when the first train crosses the bridge is determined, and the dynamic strain influence line of the first train crossing the bridge is obtained through the dynamic strain response; based on the dynamic strain influence line, it is determined whether there is an abnormality in the light rail bridge. This application can effectively determine the abnormal state of light rail bridges when trains pass over them, solving the problem of abnormal diagnosis of light rail bridges in actual operation. At the same time, by judging the abnormal state of light rail bridges, the structural safety and health monitoring of light rail bridges is realized, ensuring the smooth operation of the line.

The application belongs to the technical field of engineering structure detection data analysis, and discloses a bridge modal parameter identification method and device combined with vehicle dynamic weighing. First, the influence line of the bridge is tested and obtained, and the bridge response under the vehicle excitation is tested and obtained. The weight of the vehicle is obtained by fitting the bridge response and the influence line, and then the input excitation of the bridge is obtained. Then, the frequency response function matrix of the bridge is obtained by the input excitation and the output response. The maximum singular value curve and the singular vector are obtained by singular value decomposition of the frequency response function matrix of the bridge. The frequency corresponding to the peak value of the curve is the natural frequency of the bridge, and the corresponding singular vector is the vibration mode of the bridge. The frequency corresponding to the half peak value of the curve is the half power point. The damping ratio of the bridge is obtained by bringing the half power point into the damping ratio calculation formula. In the process of bridge operating modal parameter identification, the vehicle excitation is solved for the identification of the bridge modal, and the identification accuracy of the bridge modal parameters is improved.

The invention belongs to the technical field of engineering structure detection data analysis, and discloses a bridge modal parameter identification method and device combined with vehicle dynamic weighing, and the method comprises the steps: firstly, testing to obtain an influence line of a bridge, testing to obtain a bridge response of the bridge under vehicle excitation, and obtaining the weight of a vehicle through the fitting of the bridge response and the influence line; and the input excitation of the bridge is obtained. A frequency response function matrix of the bridge is obtained through input excitation and output response, a maximum singular value curve and a singular vector are obtained through singular value decomposition of the frequency response function matrix of the bridge, the frequency corresponding to the peak value of the curve is the inherent frequency of the bridge, and the corresponding singular vector is the vibration mode of the bridge; the frequency corresponding to the half of the peak value of the curve is a half-power point, and the half-power point is substituted into a damping ratio calculation formula to obtain the damping ratio of the bridge. In the bridge operation modal parameter identification process, the problem of bridge modal identification by vehicle excitation is solved, and the bridge modal parameter identification precision is improved.

The application belongs to the field of bridge health monitoring and rapid detection, and discloses a bridge bending stiffness identification method based on multi-point deflection influence line input, and steps are as follows: firstly, a linear model for solving bending stiffness is established by using measured deflection influence lines at multiple positions of a bridge and linear elasticity theory; then, a redundant dictionary composed of multiple types of global basis functions is used for sparse representation of the bending stiffness distribution curve, and the bending stiffness reconstruction problem is converted into a sparse vector solving problem; finally, a sparse vector solution model with 1-norm regularization constraint is established, and the optimal bending stiffness distribution is obtained by solving the model. l The application can realize continuous bending stiffness curve solving by using multi-point measured deflection influence lines only, is suitable for stiffness evaluation of statically indeterminate in-service bridges such as continuous girder bridges, and has the advantages of strong applicability, high solving efficiency and strong robustness.

This invention discloses a constraint conversion device and a demonstration teaching aid for constructing the influence line of a multi-span statically determinate beam using the kinematic method. The device includes: a first connecting member for connecting and fixing a first rigid member; a second connecting member for connecting and fixing a second rigid member; several shear constraint conversion boxes of the same shape, height, and proportionally varying length and width, with adjacent shear constraint conversion boxes nested together to form a retractable shear constraint conversion box group; each shear constraint conversion box has a first pin hole, and after all shear constraint conversion boxes are nested and overlapped, all the first pin holes can be fixed by a first pin shaft; and a hinge constraint conversion track, one end of which is fixedly connected to the first connecting member, and the other end of which is hinged or fixedly connected to the shear constraint conversion box group. Advantages: This invention allows switching between shear constraints and hinge constraints; it allows students to assemble the required structural form and release the corresponding constraints, intuitively displaying the structural motion form and deepening students' understanding of the mechanism's motion mode under external forces.

The present disclosure relates to a bridge sensor optimization layout and response reconstruction method, system and medium, relating to the field of bridges. The method comprises: establishing a finite element model of the bridge; deleting measurement points in the initial sensor layout scheme; calculating load transverse influence lines using the bridge finite element model, reconstructing strain response data of the deleted transverse strain measurement points; reconstructing displacement data of the deleted displacement measurement points and / or acceleration data of the acceleration measurement points based on the relationship between displacement and acceleration; reconstructing strain response data of the deleted longitudinal strain measurement points based on the relationship between strain and displacement, using sensor data of the retained longitudinal strain measurement points and using data of the longitudinal displacement measurement points; constructing the architecture of the BiLSTM neural network model; all sensor data and all reconstructed data are input into the network model, and the network model is used to predict the data of the deleted measurement points. The present disclosure realizes the optimization of the sensor layout while improving the reconstruction accuracy.

The present application belongs to the field of bridge and culvert engineering quality detection technology in transportation industry. Based on the method for quickly evaluating the bearing capacity of continuous beam by the area of bending moment influence line of arbitrary section, the method firstly adopts a vehicle with known axle load, axle distance and axle number as a loading vehicle, sets the weight P1 of rear axle I, the weight P2 of rear axle II and the weight P3 of rear axle III; then constructs the effect function of bending moment at arbitrary section x changing with the moving vehicle; finally, the integral value of the effect function of bending moment at section x changing with the moving vehicle under the same condition is taken as the numerator, and n is 0-1; the ratio of the integral value of the effect function of bending moment at section x changing with the moving vehicle under the same condition to the denominator is less than 1, which indicates that the bearing capacity of the bridge meets the requirements. The present application can improve the detection precision and efficiency of existing bridge load and reduce the cost of manpower and material resources.

The application discloses a method for regulating and controlling segmented length of outer concrete during a process of segmental construction of a concrete arch bridge into an arch state, and relates to the technical field of bridge engineering. The method comprises the following steps: constructing a multi-objective optimization function with the stress performance and linear shape of a main arch ring after bridge completion as targets, and determining design variables and constraint conditions; establishing and verifying a finite element model of the whole construction process of the concrete arch bridge; based on the finite element model, iteratively optimizing the design variables by using a non-dominated sorting genetic algorithm II (NSGA-II), and solving a Pareto front solution set; establishing an evaluation index, screening the Pareto front solution set, and determining an optimal regulation and control scheme; and verifying the optimal regulation and control scheme by a moving loading test based on the influence line superposition principle. The application can effectively reduce the stress and deformation of the main arch ring after bridge completion, improve the stress distribution state of the concrete, and improve the stress performance of the bridge based on the multi-objective optimization algorithm.

This invention provides a method, device, system, and storage medium for assessing the load-bearing capacity of bridges, relating to the field of bridge load-bearing capacity assessment technology. The method includes: acquiring structural response data of the target bridge from the moment a valid test vehicle crosses the bridge to the moment it exits; performing signal decomposition on the structural response data to obtain the quasi-static response of the target bridge based on the decomposition results; alternately inverting the influence line of the target bridge and the axle load of the valid test vehicle based on the quasi-static response to obtain the inverted influence line and the inverted axle load; calculating the fitted deflection value and fitted strain value of the target bridge based on the inverted influence line, the inverted axle load, and a preset loading scheme in the load test; calculating the deflection verification coefficient and the strain verification coefficient based on the fitted deflection value and the fitted strain value; and obtaining the load-bearing capacity assessment result of the target bridge based on the deflection verification coefficient and the strain verification coefficient. This invention enables automated and rapid assessment of bridge load-bearing capacity.

The present application relates to the technical field of railway bridge design, and particularly relates to a method and device for fixed-length loading of live load of a large-span railway bridge, which comprises the following steps: loading a moving load track on the bridge by using a moving unit concentrated force method to obtain an influence line of a set parameter; dividing the fixed-length live load into loads of left-end uniform force, middle concentrated force and right-end uniform force; adjusting the setting position of the middle concentrated force end and the length of the left-end uniform force region at each setting position; obtaining the response value of the fixed-length live load corresponding to the setting position of the middle concentrated force end and the length of the left-end uniform force according to the influence line; and taking the most unfavorable loading form corresponding to the response value as a static load working condition to perform a most unfavorable effect nonlinear analysis on the bridge. The method can solve the problem in the prior art that the loading lengths of the left-end and right-end uniform forces are directly assumed to be equal, only an approximate solution can be obtained, and the most unfavorable effect value of the fixed-length live load obtained is inaccurate.

This invention relates to the field of bridge testing and inspection technology, specifically disclosing a test method for damage identification of precast assembled beam bridges based on strain curves. The method includes: arranging multiple strain test points on the precast assembled beam bridge to be tested; applying a moving load and collecting strain data from the strain sections; extracting the strain data from each strain section and performing noise reduction processing on the strain data to obtain the strain influence lines for each strain section; determining the longitudinal damage location: determining the longitudinal damage location based on the changes in the intersection positions of strain influence lines at different spans. This invention uses strain influence lines at different spans of the longitudinal beams of the precast assembled beam bridge to correct errors caused by residual strain influence and reduce noise in the test data, reducing errors caused by equipment and environmental factors. Changes in the intersection points of the strain influence lines enable longitudinal damage identification of the precast assembled beam bridge. The test is short, has minimal impact on bridge traffic, reduces test costs, and improves economic efficiency.

The application discloses a PC track beam influence line determination method and system and a storage medium. The method comprises the following steps: firstly, obtaining response data of a train passing through a PC track beam; then, determining a train position fitting model through linear fitting according to the collection time corresponding to a wave trough in the response data and train parameters; finally, solving the influence line based on the train position fitting model to obtain the PC track beam influence line. The PC track beam influence line determination method, system and storage medium are used for determining the vehicle position on the PC track beam by using the bridge response data, so that high-precision positioning devices and clock synchronization devices do not need to be additionally purchased, and the positioning and synchronization costs in the influence line determination process are reduced.

The invention relates to the field of structural health monitoring, and discloses a multi-moving load identification method based on an influence line. Through calibration and comparison of bridge displacement response, high-precision inversion of an unknown moving load is realized. The method comprises the steps that firstly, a displacement sensor is arranged on a bridge, and the real-time displacement change of a structure in the vehicle passing process is obtained; then, a calibration vehicle with a known load passes through the bridge at a constant speed, displacement response of the calibration vehicle is collected, function fitting is carried out, and a calibration function with the load moving distance as an independent variable is obtained; on the basis, for a vehicle with an unknown load, the displacement response of the vehicle is also obtained, and functions D (x) and d (x) are established. And identifying the size of the unknown moving load by comparing the function relationship between the D (x) and the d (x). The method is clear in structure, simple to implement and high in anti-noise capability, can effectively improve the precision and stability of multi-load recognition, and has a good engineering application prospect.

This invention provides a bridge damage detection method and system based on integrated crash barriers, belonging to the field of bridge damage detection technology. It is applied to the left and right crash barriers of a bridge, connected by force transmission blocks and sliding plates. The method includes: applying a test load to the longitudinal loading points of the bridge main girder; installing a distance measuring instrument on the force transmission block to collect measured vertical displacement values ​​corresponding to the positions of each loading point; fitting and extracting the actual vertical displacement influence line function based on the measured vertical displacement values; obtaining the benchmark displacement data of the bridge in an undamaged state, and constructing an undamaged basis function through data fitting; calculating damage indicators based on the actual influence line function and the undamaged basis function. This invention enables the left and right crash barriers to share the load, save materials, adapt to settlement, and consume energy efficiently, and can complete the quantitative detection of main girder damage without interrupting traffic.

The present disclosure relates to a bridge influence line identification method and system based on two-stage spatial weighted regularization. The method comprises: acquiring dynamic response data of measuring points when a moving vehicle passes through a bridge; using a standard Tikhonov regularization method to solve an influence line to obtain a preliminarily identified influence line; identifying a peak value position; constructing a weight matrix of a smoothing constraint and a weight matrix of a structure preservation constraint according to the distance between the bridge position and the nearest peak value region; the smoothing constraint weight of the bridge position located in the peak value region is smaller than that of the bridge position located in the non-peak value region, and the structure preservation constraint weight of the bridge position located in the peak value region is smaller than that of the bridge position located in the non-peak value region; and using a second objective function to solve the influence line to obtain a finally identified influence line. The present disclosure maintains smoothness, avoids peak reduction, more accurately restores the peak value of the influence line, and takes into account the calculation efficiency.

The application discloses a bridge distributed stiffness identification method based on curvature envelope area and microwave radar, and has the advantages of multi-point deformation synchronous monitoring based on the microwave interference radar, application of the radar realizes synchronous measurement of the deformation displacement influence line of the multiple measuring points in the observation area when the calibration mobile load passes through the bridge, then the curvature envelope area influence line of the test area is calculated based on the essential relationship among the curvature, the rotation angle and the displacement through the measured displacement influence line, the bending moment envelope area influence line caused by the calibration mobile load is calculated through structural mechanics, and finally the unit stiffness of the bridge test area can be obtained by taking the average of the quotient of the bending moment envelope area and the curvature envelope area in the time scale. The application has the advantages of convenient equipment installation, quick and convenient measurement, good robustness and non-contact, overcomes the problems of difficult sensor layout and poor stability of the existing method, and has a good prospect of wide application in actual bridge stiffness identification.

The invention discloses a method for testing the anti-overturning performance of a reinforced single-column pier bridge, and relates to the technical field of bridge assessment, and the method comprises the steps: obtaining bridge structure parameters, building a finite element model containing a reinforced structure to simulate working conditions, and recognizing the most unfavorable section; a loading and measuring scheme is formulated according to the loading and measuring scheme, hierarchical synchronous jacking is executed through a PLC jacking system, and dead-load support counterforce is obtained; then unbalanced load distribution jacking is conducted, and the vertical rigidity of the support is obtained through fitting of collected force and displacement data; then eccentric loading is carried out, and a rigidity value is used for converting counter force of an eccentric load support; and finally, the most unfavorable load is arranged based on the influence line, the response of the reinforcing component is monitored, the reaction force and the anti-overturning stability coefficient are checked by integrating all data, and finally, an anti-overturning performance and reinforcing effect evaluation report of the reinforced bridge is output. According to the method, accurate evaluation of the whole process from theoretical analysis to field actual measurement is achieved, and a crucial decision basis is provided for operation safety and later maintenance of the reinforced single-column pier bridge.

The application relates to the technical field of bridge test detection, and particularly discloses a prefabricated assembled beam bridge transverse damage rapid diagnosis method based on strain influence lines, which comprises the following steps: arranging two strain measuring points on a to-be-detected prefabricated assembled beam bridge; applying a moving load to the span direction of the prefabricated assembled beam bridge by adopting a quasi-static loading mode; extracting the strain of the two measuring points under the action of the moving load; and fitting and drawing a strain influence line; calculating the total envelope area S between the strain influence line of the bridge measuring point and the transverse coordinate axis 总 , then calculating the change amplitude of the total envelope area i ; and qualitatively diagnosing the prefabricated assembled beam bridge transverse damage according to the measuring point i . The prefabricated assembled beam bridge transverse damage rapid diagnosis method can comprehensively diagnose the prefabricated assembled beam bridge transverse damage, and improves the accuracy of the damage diagnosis result. The method has the advantages of short diagnosis time, uninterrupted traffic and the like, can rapidly diagnose, reduces the test cost, and improves the economy.

The application discloses a kind of single-column pier bridge reinforcement post-anti-overturning performance test methods, it is related to bridge evaluation technical field, the method includes: obtaining bridge structure parameter, establishes finite element model including reinforcement structure to simulate working condition and identify the most unfavorable section;Accordingly, load and measurement scheme is formulated, and hierarchical synchronous jacking is executed by PLC jacking system, and constant load support reaction force is obtained;Then, eccentric load distribution jacking is carried out, and force and displacement data are fitted to obtain support vertical stiffness;Subsequently, eccentric loading is carried out, and stiffness value is converted eccentric load support reaction force;Finally, based on influence line arrangement most unfavorable load, monitor reinforcement component response, and all data are checked to calculate support reaction force and anti-overturning stability coefficient, and finally output the anti-overturning performance of bridge after reinforcement and reinforcement effect evaluation report.The method realizes the whole process accurate evaluation from theoretical analysis to field measurement, and provides important decision basis for the operation safety and later maintenance of single-column pier bridge after reinforcement.

The application provides a bridge health monitoring system calibration method and device based on a sub-region loading test and a storage medium, wherein the calibration method comprises the following steps: performing a sub-region loading test on a target real bridge based on an influence line, and obtaining monitoring data; calling and performing loading on a bridge benchmark state finite element model of the target real bridge at the same position and with the same load as the sub-region loading test on the real bridge, and obtaining corresponding structure response theoretical data; obtaining a first fitting relationship and a second fitting relationship based on a monitoring data sequence and a structure response theoretical data sequence; determining a target fitting relationship in the first fitting relationship and the second fitting relationship based on a first priority feature obtained from the monitoring data sequence and a preset standard threshold value, determining a fitting model corresponding to the target fitting relationship as a calibration model of the bridge health monitoring system, and calibrating the monitoring data by using the calibration model. The calibration method provided by the application is more convenient to implement and can improve the calibration effect of the monitoring data.

The invention relates to a bridge influence line identification method and system based on two-stage space weighted regularization. The method comprises the following steps: acquiring dynamic response data of a measuring point when a moving vehicle passes through a bridge; solving the influence line by adopting a standard Tikhonov regularization method to obtain an preliminarily identified influence line; identifying a peak value position in the identification; according to the distance between the bridge position and the nearest peak region, constructing a weight matrix of smooth constraint and a weight matrix of structure preserving constraint; the weight of the smooth constraint of the bridge position in the peak region is smaller than the weight of the smooth constraint of the bridge position in the non-peak region, and the weight of the structure retention constraint of the bridge position in the peak region is smaller than the weight of the structure retention constraint of the bridge position in the non-peak region; and solving the influence line by using a second objective function to obtain a final identified influence line. According to the method, smoothness is kept, peak reduction is avoided, the influence on the line peak is recovered more accurately, and calculation efficiency is taken into account.

The invention relates to the technical field of bridges, in particular to a spatial-temporal characteristic-based bridge dynamic verification coefficient calculation method, system and device and a storage medium, and the method comprises the steps of obtaining a theoretical displacement change value caused by temperature according to main beam temperature time sequence data; correcting the main beam displacement time sequence response data by using the theoretical displacement change value to obtain a corrected main beam displacement actual measurement response value; obtaining dynamic load time sequence distribution data and a time-varying influence line, and obtaining a theoretical displacement value based on a real operation condition and a bridge time-varying state; according to the corrected actual measurement response value of the main beam displacement and the theoretical displacement value, obtaining a time sequence of a verification coefficient; and performing window division and statistical feature extraction on the sequential sequence of the verification coefficients to obtain a representative verification coefficient corresponding to each window, and fusing the representative verification coefficients corresponding to each window to obtain a final comprehensive representative verification coefficient.