43 results about "Moving load" patented technology

The invention relates to a stress analysis method and system based on a small and medium span bridge steel-concrete composite structure, and belongs to the technical field of stress analysis, and the method comprises the following steps: S1, building a finite element parameterized model of a steel-concrete composite bridge; s2, constructing a slippage effect model of a steel-concrete interface based on the constitutive relationship of the steel-concrete composite bridge; s3, applying a moving load working condition, and dividing a load position of the steel-concrete composite bridge through a dynamic grid; s4, solving and correcting the structural stress of the steel-concrete composite bridge; s5, key section stress distribution of the steel-concrete composite bridge is output so as to identify the maximum tension and compression stress area; the method has the beneficial effects that the dynamic change of the load action can be accurately reflected in the model so as to reflect the stress state of the bridge under the actual traffic load; and an accurate structural stress solution is gradually approximated, and a reliable stress analysis result is obtained by comprehensively considering material characteristics, structural geometrical shapes and load distribution factors.

The invention discloses a method for dynamically determining an early warning threshold value of a bridge structure monitoring system, and belongs to the technical field of bridge structure monitoring. According to the method, the temperature and structural response data of a bridge are obtained, the structural response data are deflection data or strain data, and the obtained data are divided into the structural response data affected by moving loads and the structural response data only affected by the temperature and not affected by the moving loads; fitting the relationship between the temperature and the strain by using the data only influenced by the temperature, and determining a temperature response baseline according to the real-time temperature and the relationship; according to the data influenced by the moving load, an extreme event responded by the moving load is determined by using generalized Pareto distribution, a current dynamic early warning upper bound value and a current dynamic early warning lower bound value are determined in combination with a temperature response baseline, and early warning is carried out on the bridge state according to the dynamic early warning upper bound value and the dynamic early warning lower bound value. Through the design of multi-factor early warning and a dynamic early warning threshold value, the problem that an existing early warning system is inaccurate in early warning is solved.

The present invention relates to a picking device (1) for picking at least one object (4), comprising a support structure, a movable load handling manipulator (2) arranged on the support structure, a handling element (3) arranged on the load handling manipulator (2) for handling the object (4), and a control unit (5) for controlling the load handling manipulator (2) and the handling element (3), wherein the handling element (3) has a vertically displaceable contact element (6) which can be applied to a front side (4-1) of an object (4) facing the handling element (3) and is configured to displace the front side (4-1) of the object (4) along a vertical object axis (8) in order to create a gap (9) below the front side (4-1) of the object (4), wherein the handling element (3) has two displaceable support elements (10, 10-1, 10-2).which are displaceable along a longitudinal axis (11) and along a transverse axis (12), wherein the displaceable support elements (10, 10-1, 10-2) can be attached to a bottom surface (4-2) of the object (4) through the gap (9) created below the front surface (4-1) of the object (4) in order to receive the object (4). The support elements (10, 10-1, 10-2) each have at least two spaced-apart fixing elements (13, 13-1, 13-2, 13-3, 13-4) that can be switched between a fixed state and a non-fixed state. The control (5) is configured to switch one fixing element (13, 13-1, 13-2, 13-3, 13-4) of the two support elements (10, 10-1, 10-2) into the fixed state during a rotation step and to cause a synchronous displacement of the two support elements (10, 10-1, 10-2) along the longitudinal axis (11) and transverse axis (12) in order to achieve a rotation of the object (4) about the vertical object axis (8).

The application provides a method and system for planning reconstruction and expansion of an airport underpass, and relates to the technical field of airport engineering planning. The method comprises the following steps: generating at least one feasible reconstruction and expansion planning scheme based on the geological conditions of the target underpass and the non-stop construction constraint conditions of the flight area; establishing a three-dimensional finite element model considering the action of the airplane moving load, using the three-dimensional finite element model to verify the structural safety of the scheme, adjusting the relevant parameters and re-verifying the structural safety of the scheme when the scheme fails to pass the verification, and verifying the structural safety of the scheme until the scheme passes the verification; when the number of schemes is at least two, constructing a simulation model, simulating the schemes by using the simulation model, calculating the comprehensive influence degree of the schemes on the airport operation efficiency according to the simulation results, and selecting the scheme with the minimum comprehensive influence degree as the first target feasible reconstruction and expansion planning scheme. The application can improve the comprehensiveness of the planning results, reduce the whole life cycle cost and safety hidden danger of the project, and improve the airport operation efficiency.

The invention discloses a method for forecasting stress and fatigue life of an articulated joint of a marine emergency bridge under a moving load. A wave-bridge action numerical model is established in fluid software, and an external drainage basin and bridge motion numerical model is constructed according to computational fluid mechanics (fluid). Finite element calculation is carried out under the same model proportion, and the fluid and the finite element model have the same size and the same position in the coordinate system of the fluid and the finite element model. And constraining the finite element model, and further applying a moving load. And operating the fluid software, and mapping the pressure data of the fluid software to the finite element software. And feeding back the movement of the bridge and the deformation of the joint structure obtained in finite element analysis in the finite element software to the fluid solver through a grid mapping technology so as to update grid data in the fluid solver. By forecasting the deformation of the hinge joint of the marine emergency bridge in a multi-field coupling environment, more accurate reference data is provided for the design of the joint of the marine emergency bridge.

The invention relates to a moving load applying method for a non-uniform discretization finite element model, which comprises the following steps: constructing the non-uniform discretization finite element model, determining the node number of each finite element node in the non-uniform discretization finite element model and the corresponding space coordinate of each finite element node, and enabling the unit length acted by the moving load to be in non-uniform distribution; calculating the spatial position of the jth moving load under the ith time step; judging the unit where the jth moving load is located under the ith time step, obtaining the node number of the left node of the unit where the moving load is located under the time step, defining the node number as a track matrix, calculating the distance between the moving load and the left node under the time step, and defining the distance matrix; repeating the steps to obtain a track matrix and a distance matrix of all moving loads in the total time step; and calculating the equivalent node force borne by the left node and the right node of the unit when the moving load acts on the unit. In a full-time-history analysis range, the moving load is dynamically tracked and accurately positioned so as to be accurately applied.

The present invention relates to a method, system, device and medium for simulating Rayleigh surface waves of a high-speed railway earthquake source, and belongs to the technical field of numerical simulation of earthquake waves. A high-speed train is a moving line source in a fixed direction. Based on the train moving load model, the loads applied by the four pairs of axles of each carriage to the sleepers under the track are taken as point sources, and the moving line source is decomposed into a superposition of a series of point sources. Considering the elastic effect of the track rails, a time function of the high-speed railway earthquake source is constructed based on the Euler-Bernoulli elastic beam theory. Considering the absorption and attenuation of seismic waves by the underground medium, the staggered grid finite difference method is used to solve the Kelvin viscoelastic wave equation, and at the same time, considering the free surface boundary, the wave field of the earthquake Rayleigh surface wave excited by the high-speed railway moving earthquake source is numerically simulated. It provides the basis and data for the subsequent waveform inversion based on the high-speed railway earthquake source and the inversion of the high-speed railway earthquake source surface wave dispersion curve.

The application provides a modeling method of time-varying moving load in finite element method, comprising the following steps: establishing an initial mechanical finite element model of a structure to be calculated, and performing initial finite element mesh division; calculating the radius R of a contact spot between a force application surface and a force receiving surface by using a finite element method; selecting contact points within a width R range along a load moving path, and sequentially renumbering the contact points according to a load action time sequence to obtain finite element mesh nodes; establishing independent unit time load base functions at the finite element mesh nodes; calculating a total load F(t) of the structure at a time t; obtaining a coefficient item in a base function weighting coefficient vector at the time t by using a linear interpolation method; and decomposing the moving load F(t) to a plurality of mesh nodes near the load contact points based on an equation L(t) = f t ·W(t) to obtain a time-varying moving load loading result within a time [0, t1]. The method solves the moving load problem in the finite element environment.

The present application relates to the field of state monitoring, especially to a kind of monitoring method for the health state of subway train, by determining track regularity and track stress distribution characteristic value;Calculate the load bearing characteristic coefficient of the opposite track of subway train, determine the change coefficient in combination with the historical track load bearing characteristic coefficient, determine whether the track exists abnormal tendency, determine the processing method;If the track does not exist abnormal tendency, then keep the continuous monitoring state to the opposite track of subway train;If the track exists abnormal tendency, then determine the moving load of subway train, calculate the derailment risk coefficient in combination with the track regularity, determine the derailment early warning state of subway train;In response to the result of subway train derailment early warning state, locate the risk point, determine the risk point and the running distance of subway train, adjust the running speed of subway train;Or determine that subway train needs to be stopped.The present application determines the processing method by monitoring the track operable state of subway train, improves the running efficiency and safety factor.

This application relates to the field of building construction technology and discloses a vertical precast component positioning and installation system and method. The system includes a moving load-bearing mechanism, a component clamping and flipping mechanism, and a rebar correction and positioning mechanism. The component clamping and flipping mechanism clamps the vertical precast component and drives it from a horizontal transport state to an upright installation state. The rebar correction and positioning mechanism is used to position and correct the upper end of the exposed section of the pre-embedded rebar at the installation location. The rebar correction and positioning mechanism includes a correction bracket and multiple correction claws. In the retracted state, the correction bracket can be inserted into the installation area through the gap between adjacent pre-embedded rebars from one side. In the open state, the multiple correction claws respectively clamp the upper end of the corresponding exposed section of the pre-embedded rebar. After correction is completed, the component clamping and flipping mechanism drives the vertical precast component to descend, aligning the bottom precast hole with the pre-embedded rebar and fitting it in place for installation. This application can improve the hole alignment accuracy and construction efficiency of precast component installation.

The invention relates to a real-time bridge monitoring method based on a double-input self-encoding neural network. The method comprises the following steps: (1) deploying a small number of dynamic vibration sensors at any position of a bridge to collect vibration signals under the action of a moving load; (2) performing spectral analysis on the signal, extracting a fundamental frequency f1 of a bridge structure as a core parameter, and calculating an interception moving window length according to a criterion that a formula l is greater than or equal to 2fs / f1 on the basis of a dynamic relationship between a sampling frequency fs and the fundamental frequency f1; (3) inputting the windowed signal into a dual-channel auto-encoder neural network for training; and (4) realizing structural state judgment by utilizing the trained network, inputting response data to be tested, outputting a corresponding feature vector, calculating to obtain a feature sensitive factor, and judging whether the bridge structure is damaged or not according to a change trend of the feature sensitive factor, thereby realizing real-time structural damage identification under an unsupervised condition.

This invention discloses a modular crossbeam structure for a gantry coordinate measuring machine, relating to the technical field of coordinate measuring equipment. It includes a modular triangular crossbeam, with a triangular socket at one end and a triangular plug at the other. The triangular plug and socket are fitted together. An inner shaft groove is formed at the center of the triangular plug, and an inner insertion shaft is rotatably mounted at the center of the triangular socket, fitting into the inner shaft groove. This invention employs a three-layer coaxial and concentric connection of the outer triangular profile, a middle locking pin layer, and a central inner insertion shaft, resulting in high joint stiffness, far exceeding that of traditional flange connections. The central inner insertion shaft penetrates the center of both crossbeam sections, forming a composite force transmission system of external triangular bending resistance and internal circular shaft torsion resistance, significantly improving bending, shear, and torsional stiffness. This completely eliminates bending deformation and step errors caused by the self-weight and moving loads of large-span crossbeams, ensuring long-term stability of the guide rail installation reference.

The invention belongs to the technical field of building robot detection, and particularly relates to a device and method for testing dumping and load of a wheeled robot on a slope, and the device comprises a counter-force beam support frame part which is disposed on a bottom platform and comprises a support oil cylinder used for preventing the robot from dumping left and right and being damaged; the counter-force beam moving load part is arranged at the top of the counter-force beam support frame part and is used for carrying out load test on the robot; the lane support frame part is arranged on the bottom platform and is used for carrying out a toppling test on the robot; and the wheel limiting liftable bottom plate part is arranged on the lane supporting frame part and is used for bearing a robot. According to the device and method for testing the toppling and load of the wheeled robot on the slope, the problem that existing detection equipment is difficult to adapt to wheeled engineering robots of different specifications to carry out slope range tests in which the wheeled engineering robots can safely pass under different load conditions can be solved.

This invention discloses a bridge damage identification method, system, electronic device, and storage medium based on multi-scale Gaussian filter residuals. The bridge damage identification method comprises the following steps: acquiring displacement response data of a simply supported beam of the bridge under test under moving load; performing principal component analysis (PCA) on the displacement response data and extracting key principal components using cumulative contribution rate (CCR); using a moving average filter (MAF) to filter out the high-frequency components in the dynamic components and obtaining low-frequency damage mode shapes; then using a Gaussian filter (GF) to simultaneously eliminate high-frequency dynamic components and most of the modal abrupt changes caused by damage, i.e., using a Gaussian function as a weighting kernel to reduce noise in the signal; and by analyzing the filtering residuals of the two filters, introducing an exponential function to amplify local peak values, effectively extracting damage features, thereby completing the structural damage identification and determining its specific location.

The invention relates to a transport system (100, 200, 300, 400, 500) for moving loads on an underlying surface, comprising: at least one rail travel path; and at least one transport vehicle (50) which runs on wheels (12, 12A) on the rail travel path, characterised in that: the rail travel path comprises a single rail (10, 312, 314, 412, 414, 512, 514) for receiving the load of the transport vehicle (50); the transport vehicle (50) comprises at least one front wheel (12) and at least one rear wheel (12A) which each rest on the rail (10, 312, 314, 412, 414, 512, 514) one behind the other in the travel direction by means of a running surface (14) having a concave cross-section; and the transport vehicle (50) further comprises support rollers (52A, 52B) which are arranged on both sides of the front and rear wheels (12, 12A) and run on the underlying surface on both sides of the rail (10, 312, 314, 412, 414, 512, 514).

"Portable and mobile construction crane under load" Portable and mobile construction crane under load (1), referred to as crane (1), comprising a chassis (2, 3) on which are mounted four wheels (230, 240, 330, 340), of which at least two are swiveling, a mast (4) the base of which is mounted swiveling on said chassis, said mast being swiveling, in a median longitudinal plane of the crane, around a transverse axis, a jib (6) fixed on the head of said mast, said jib being swiveling, relative to said head of said mast, around a transverse axis, and sliding, on the head of said mast, along a sliding axis, included in the median longitudinal plane of the crane, adjustable by swiveling said jib. The boom is suitable for receiving a gripping means (7) for a load to be moved (16), or one or more force transmission means (8) intended to support, at least in part, a load to be moved and / or a lifting means (9) for said load to be moved.The crane includes a jack (10), arranged to pivot said mast so as to carry a distal end of said boom cantilevered from said chassis, the base of which is mounted pivotally about a transverse axis distinct from the transverse axis about which the mast pivots, on the chassis; a head is mounted pivotally about a transverse axis on an upper quarter of the mast located on the side of said head of said mast, said jack being pivotable, relative to the mast and the chassis, in the median longitudinal plane of the crane. Figure for the abbreviation: Figure 1.

The invention relates to a crane system for handling a load (3, 4) and a method for controlling a load (3, 4) during a lifting operation. The method is used to control the orientation of the load (3, 4) during a lifting operation using a speed control method. A capstan (5) control system controls a capstan (5) arrangement, where the capstan (5) arrangement is arranged relative to the crane system. The method comprises the steps of: placing a load (3, 4) at a first load (3, 4) position and attaching a first tail cord (8) and a second tail cord (8, L2) to a first attachment point and a second attachment point on the load (3, 4); determining a predicted virtual axis of the position of the next load (3, 4) relative to the previous virtual axis; moving the load (3, 4) to the next load (3, 4) position relative to the predicted virtual axis while controlling each of the first and second winches (9) such that each of the first and second tail rope lengths (8) is individually adjusted relative to the predicted virtual axis; at the next load (3, 4) position, acquiring at least one piece of first tail line length (LI) information from the first measuring device and at least one piece of second tail line length (8) information from the second measuring device; analyzing the first tail rope length information and the second tail rope length (8) information relative to each other to determine an offset value for each of the first tail rope length and the second tail rope length (8), and comparing the offset values to a predicted virtual axis related to the current load (3, 4) position; an offset correction is calculated for the first tail line length and the second tail line length (8) compared to each offset value based on the predicted virtual axis. When the load (3, 4) moves towards another load (3, 4) position having another predicted virtual axis, the length of each respective tail rope (8) is adjusted relative to the predicted virtual axis such that the load (3, 4) is moved by pre-controlling the length of each respective tail rope (8).

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 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.

The application relates to the technical field of mechanical arms and discloses a mechanical arm fine control method and system based on machine learning, which comprises the following steps: determining a first grabbing strategy or a second grabbing strategy based on the relationship between material parameters and a historical material set; when the first grabbing strategy is determined, determining the grabbing strength of the mechanical arm based on the historical material set; when the second grabbing strategy is determined, determining the grabbing strength of the mechanical arm based on the clustering result of the historical material set and a grabbing strength model; determining the minimum moving load based on a moving load curve diagram and determining the grabbing load of a driving motor; judging whether the grabbing strength needs to be adjusted according to the load relationship between the minimum moving load and the grabbing load; determining the grabbing strength factor based on the minimum moving load and the grabbing load; and completing grabbing according to the adjusted grabbing strength. The first grabbing strategy, the second grabbing strategy and the grabbing strength factor ensure the stability of the grabbing process.

The present application relates to a kind of bridge real-time monitoring methods based on double input self-encoding neural network, comprising the following steps: ①First, a small amount of dynamic vibration sensor is deployed in arbitrary position of bridge to collect vibration signal under the action of moving load;②Subsequently, signal is analyzed in spectrum, extract bridge structure fundamental frequency f1 as core parameter, based on the dynamic relationship of sampling frequency fs and fundamental frequency f1, according to the formula l≥2fs / f1 The rule is calculated to intercept moving window length;③Windowed signal is input into double-channel self-encoder neural network for training;④The network is used to realize structure state judgment after training, input the response data to be tested, output corresponding feature vector, and characteristic sensitive factor is obtained by calculation, whether the bridge structure has been damaged according to the change trend of characteristic sensitive factor is judged, and the real-time recognition of structure damage under the condition of unsupervised is realized.

The invention relates to a loading device and method for simulating the moving load of a real train, the device comprises a loading assembly, a load moving circulating assembly and a track model, a walking part is arranged above a loading rod, a bogie is arranged below the loading rod, the walking part is connected with a forward crawler belt and a counter-force cross beam, wheels are arranged below the bogie, and the loading rod is connected with the bogie. The counter-force cross beam applies a train load to the bogie through the walking part and the loading rod, the counter-force cross beam has the functions of providing counter force and being matched with the walking part for limiting and guiding, and the advancing track drives the walking part and the loading rod to achieve circulating movement of the bogie on the track model; and a nonlinear elastic element is arranged in the loading rod to realize the expansion and contraction of the loading rod. Compared with the prior art, the method has the advantages that the redistribution of the load of the wheel rail near the poor bearing sleeper and the sub-rail foundation can be considered, the test result is closer to the real wheel rail stress condition, and the working condition of normal service of the sub-rail infrastructure and the poor bearing damage condition caused by deterioration of the sub-rail foundation can be considered at the same time.

The application discloses a bridge damage identification method under a moving load, comprising the following steps: 1, substituting bridge damage displacement data obtained through finite element simulation into a residual neural network to obtain a predicted damage reduction coefficient; 2, based on a Newmark-beta method, embedding available physical knowledge of a bridge structure into a feature learning process, and substituting the damage reduction coefficient predicted by the network into a physical equation to obtain predicted damage displacement data; 3, substituting the damage reduction coefficient and the displacement damage data obtained by solving into a loss function to obtain a loss value, and updating network parameters; and 4, predicting bridge damage by using the trained physical-guided residual neural network. The application has high damage identification precision under the condition of considering the uncertainty of vehicle weight and the uncertainty of bridge structure parameters, and can improve the accuracy of damage identification of the network when the measured data is less.

This application relates to a method for applying moving loads to a non-uniformly discretized finite element model, comprising: constructing a non-uniformly discretized finite element model, determining the node number and corresponding spatial coordinates of each finite element node, wherein the element length of the moving load is non-uniformly distributed; calculating the length of the element subjected to the moving load; and calculating the length of the moving load. i The time step j The spatial location of the moving load; determine the first i The time step j For each moving load element, the node number of the left node of the element at that time step is obtained and defined as a trajectory matrix. The distance between the moving load and the left node at that time step is calculated and defined as a distance matrix. This process is repeated to obtain the trajectory matrix and distance matrix of all moving loads within the total time steps. The equivalent nodal forces borne by the left and right nodes of the element when the moving load acts on it are calculated. This application dynamically tracks and precisely locates moving loads for accurate application throughout the entire time-history analysis.

The application discloses a bridge damage positioning method of high-resolution modal flexibility influence line, which comprises the following steps: collecting displacement response of a bridge under a moving load by using at least two sensors to form a displacement matrix U; performing FFT transformation on the displacement response to determine inherent frequency ω of the bridge; performing analysis on the displacement matrix U to obtain a principal component matrix G; filtering high-order dynamic components in each order principal component according to physical meaning of the principal component matrix to obtain each order high-resolution modal vibration mode; constructing a modal flexibility matrix C by using the inherent frequency ω and the modal vibration mode; discretizing a moving process of a unit load into a unit load matrix F; and constructing deflection influence lines at multiple degrees of freedom by using the modal flexibility matrix C and the unit load matrix F; and constructing deflection influence lines of the bridge in a damage-free state and a damaged state to obtain a damage index and identify a position. The method constructs the influence line by using modal parameters of the bridge, and accurately positions the damage by using a small number of sensors and simple calculation.

The application provides a BVE quasi-static influence line identification method based on multi-observation joint estimation, comprising the following steps: S1, obtaining structural dynamic response data of a target bridge under the action of a moving load; S2, performing EMD-VMD multi-source observation construction and preprocessing on the structural dynamic response data to obtain multi-source observation data corresponding to the same quasi-static influence line; S3, establishing a quasi-static influence line parameterization expression model based on a shared node B spline, and performing joint fitting on the multi-source observation data; S4, performing adaptive adjustment on the joint fitting process of the shared node B spline based on an improved generalized cross-validation MGCV and a node encryption index; and S5, outputting the quasi-static influence line identification result of the target bridge. This method can reduce the influence of a single decomposition path, fixed smoothing parameters and fixed node configuration on the identification result, and improve the stability and peak area feature retention capability of the bridge quasi-static influence line identification.