226 results about "Bridge vibration" patented technology

The invention discloses a large-span bridge vibration response prediction method based on data driving, and relates to the technical field of bridge vibration response prediction, and the method comprises the following steps: arranging a plurality of sensors at a plurality of key structure parts of a bridge, collecting vibration response data of the bridge during operation in real time based on an initial sampling frequency set based on the inherent frequency of the bridge structure; performing frequency domain analysis on the collected vibration response data, extracting a main excitation frequency component under the current working condition, and constructing a current excitation frequency spectrum; the method comprises the following steps: calling structural modal parameters obtained in a design stage, a static load test or a modal test of a bridge, extracting the natural vibration frequency of each order of structure, and constructing a bridge inherent frequency feature library; according to the method, the resonance state is dynamically identified through frequency domain analysis and the fuzzy risk index, the sampling frequency is intelligently adjusted, high-frequency response accurate capture and resource efficiency optimization are realized, and the sensitivity, the real-time performance and the safety of a bridge health monitoring system are remarkably improved.

The invention discloses a bridge vibration identification method and system based on an artificial intelligence technology, and relates to the technical field of data identification, and the method comprises the steps: dividing a bridge into a plurality of bridge segments, collecting the vibration data of the bridge segments in a preset time, forming a vibration data set, and analyzing the stress bearing capability of the bridge segments based on the data. The method comprises the following steps: identifying a stress bearing limit value of each bridge section, establishing a health safety threshold value of the bridge section, providing indexes for dangerous bridge section identification, inputting real-time monitoring data into a vibration identification model, predicting a vibration influence degree, dynamically monitoring a bridge state, discovering risks in advance and taking measures. And analyzing vibration influence factors, determining influence sources, and helping to optimize coping strategies. Predicting vibration deformation trend, evaluating bridge structure change, avoiding major accidents, reducing overload stress based on a balance strategy, prolonging the service life of the bridge, regularly monitoring the health state, formulating optimized operation time and mechanism, and ensuring safe operation of the bridge.

The invention discloses a monitoring method and device for a cable-supported bridge, a storage medium and a program product, and relates to the technical field of bridge engineering, and the method comprises the steps: obtaining a vibration signal of each bridge cable of a to-be-detected bridge in a current monitoring period; for any target inhaul cable in the bridge inhaul cables, fast Fourier transform is carried out on the target vibration signal to obtain a target spectrogram, and the target vibration signal is the vibration signal of the target inhaul cable; identifying a main frequency peak of each amplitude value in the target spectrogram, determining a respective frequency order of each main frequency peak based on a main peak frequency value of each main frequency peak, and determining an inhaul cable force value of the target inhaul cable based on each frequency order; and performing anomaly detection on the to-be-detected bridge based on the cable force value of each inhaul cable to obtain a monitoring result. The vibration frequency order of the inhaul cable is identified, so that the cable force value of the inhaul cable is calculated based on the frequency order, the accuracy of the cable force value is improved, and the accuracy of bridge vibration monitoring is improved.

The invention provides a bridge built-in multi-dimensional self-adaptive tuning vibration reduction and monitoring device based on air energy. The bridge built-in multi-dimensional self-adaptive tuning vibration reduction and monitoring device mainly comprises a bridge health monitoring system, an air energy device, a steel plate spring, a belleville spring, an electromagnetic damper, a hydraulic damper, a hydraulic displacement amplification mechanism and an actuator. The bridge health monitoring system is used for monitoring and analyzing the state of a bridge in real time, finding potential structural problems in time and driving the tuning vibration reduction device to respond according to the monitored vibration and temperature conditions to achieve self-adaptive control over bridge vibration, and the air energy device uses the quality characteristic of the air energy device as a mass block of the tuning vibration reduction device to achieve self-adaptive control over bridge vibration. The damping device plays a key role in vibration reduction, can provide temperature and humidity control for stable operation of a bridge and a monitoring system, and is matched with a spring, a damping system, a hydraulic displacement amplifying mechanism and an actuator to effectively control multi-directional complex vibration of the bridge, adjust the temperature difference between the inside and the outside of the bridge and prolong the service life of the bridge.

The invention relates to the technical field of bridge monitoring, and provides a multi-mode bridge vibration monitoring system. The system comprises a data acquisition and processing module, a bridge monitoring module, a monitoring precision optimization module and a bridge health assessment and early warning module. Intelligent analysis and health state evaluation of multi-dimensional data are realized through a bridge safety fusion network; according to the system, a k and r two-parameter optimization algorithm is adopted to dynamically adjust hyper-parameters of the bridge safety fusion network, the learning rate, regularization parameters and batch size are optimized to adapt to different bridge environments and operation conditions, and the monitoring precision and long-term stability are improved; through multi-modal data fusion, intelligent optimization and adaptive adjustment, the comprehensiveness, accuracy and adaptability of bridge vibration monitoring are improved, and efficient and scientific technical guarantee is provided for bridge safety management.

The invention discloses a steel-concrete composite beam sound and vibration calculation method based on FEM-BEM-SEA, and belongs to the technical field of rail transit bridge vibration and noise reduction. The method comprises the following steps: determining the upper limit cut-off frequency of boundary element calculation; determining a lower limit starting frequency of statistical energy analysis; determining a boundary frequency based on the upper limit cut-off frequency and the lower limit start frequency; constructing a bridge finite element model of a bridge structure, and calculating vibration response in a full-frequency-band range when the train passes through the bridge; inputting the vibration response into the bridge boundary element model, and calculating an acoustic response within a range below the boundary frequency when the train passes through the bridge; establishing a bridge statistical energy analysis model of the bridge structure, and calculating acoustic response in a range above the boundary frequency; and jointly using the vibration response and the acoustic response as an acoustic vibration calculation result of the steel-concrete composite beam. According to the method, the problem that high-precision calculation and low calculation workload cannot be met at the same time during sound and vibration calculation of an existing bridge structure is solved.

The invention provides a bridge structure damage detection method based on image processing and CNN-LSTM, relates to the field of graphic image processing, and solves the problems that bridge vibration monitoring in the prior art is time-consuming, labor-consuming, high in cost and limited in precision, and adopts the technical scheme that the method comprises the steps of obtaining a recorded vibration video of a to-be-detected bridge structure; extracting the vibration video frame by frame to obtain bridge image data; detecting angular points by using a Harris algorithm, screening image data, and calculating vertical displacement of each feature point one by one; using a Lucas-Kanade optical flow algorithm to calculate the motion vectors of the feature angular points of the adjacent frame images; calculating the actual vibration displacement of the bridge; and carrying out standardization processing on the actual vibration displacement to obtain a two-dimensional matrix, inputting the two-dimensional matrix into the trained CNN-LSTM model, and outputting a final identification result of each type of damage. According to the scheme of the invention, high-precision bridge vibration displacement can be calculated, and efficient, accurate and high-precision bridge damage detection can be realized through the CNN-LSTM damage identification model.

The invention discloses an intelligent controllable road bridge vibration detection method based on magnetorheological fluid and a damping device, and belongs to the technical field of bridge engineering structure health monitoring and vibration control, and the method comprises the steps: calculating a comprehensive vibration strength index through multi-source signal fusion and adaptive Kalman filtering, and estimating the bridge speed; the damping force is mapped through the pre-calibration database, and a damper state verification mechanism is introduced; a gain self-adaptive ceiling algorithm is combined with a fuzzy PID control force algorithm for tracking to realize accurate control; finally, the health state of the system is evaluated through performance degradation indexes of temperature compensation, corresponding devices are integrated with a sensing network, a control unit and a distributed acquisition architecture, and the problems that a traditional system is single in state sensing, fixed in control strategy, lack of a self-diagnosis function, complex in engineering wiring and the like are solved. The comprehensive solution integrating intelligent monitoring, self-adaptive control and health self-diagnosis is realized, and the reliability, adaptability and maintainability of the bridge damping system are remarkably improved.

The invention provides a bridge stay cable video multi-target identification tracking and vibration extraction method based on an unmanned aerial vehicle. The method comprises the following steps: 1, constructing a bridge stay cable refined inclined slender target detection model based on a YOLOv11 model; 2, providing a multi-target tracking algorithm fusing the inclined slender target detection model and a StrongSORT algorithm; step 3, improving a displacement extraction method combining SIFT / ORB feature point matching and a sub-pixel refinement technology; 4, designing an unmanned aerial vehicle motion correction algorithm based on variational mode decomposition and time-frequency domain combined screening; and 5, constructing a joint working modal analysis algorithm for realizing combination of a natural excitation technology and a random subspace recognition algorithm. According to the method, high-precision extraction of the vibration signals of the stay cable and identification of modal parameters of the stay cable are realized, and technical support is provided for health monitoring of the large-span cable-stayed bridge.

The invention relates to a self-adaptive force output and energy consumption bridge vibration and vibration control inerter tuning device, and belongs to the technical field of vibration control. Comprising a roll shaft support, a spring rod, a main inerter element, a box chamber main body, a secondary inertia flywheel, a flow guide pipe, a transmission connecting rod and a flow baffle, the main inerter element penetrates through and is arranged in the box chamber main body, the outer end of the main inerter element is connected with the spring rod, the spring rod is connected with the roll shaft support, and the roll shaft support is respectively fixed with the bottom surface of a main beam and the top of a bridge pier; in addition, the flow guide pipe is arranged in the box chamber body, a flow baffle and a transmission connecting rod are further arranged in the flow guide pipe, and the transmission connecting rod is further connected with a secondary inertia flywheel. The damping device is achieved through a hydraulic mechanism, and the damping device with the self-adaptive inerter coefficient is formed through linkage of the inerter devices in the main box chamber and the auxiliary box chamber, so that the purposes of changing the inerter coefficient in real time and damping are achieved. The shock resistance, the transmission efficiency, the energy consumption effect, the structural rigidity and the stability of a vibration reduction system can be improved.

The invention discloses a bridge floor elevation dynamic measurement system and method suitable for a vehicle passing condition, and the system comprises high-precision dynamic level gauges which are arranged at key measurement points of a bridge and are used for collecting bridge floor elevation data in real time; the vibration sensor array is arranged at key measuring points of a bridge and used for collecting bridge vibration signals caused by vehicle passing, and the bridge vibration signals comprise acceleration, speed and displacement information; the laser-assisted positioning module is used for positioning and correcting the spatial position of the observation point; and the data acquisition and processing terminal is internally provided with a dynamic error compensation module, a self-adaptive filtering module and a multi-source data fusion module and is used for processing the acquired elevation data and vibration signals and synchronously outputting a high-precision bridge floor elevation measurement result.

The invention discloses a vibration sensing bridge detection robot and a dynamic characteristic detection method. The robot comprises a walking and fixing system, a signal acquisition system and an electromechanical control system. The bridge dynamic characteristic detection method detects the bridge and identifies the vibration frequency and modal shape of the bridge. According to the invention, the detection robot strides on the anti-collision guardrail of the bridge to carry out detection operation, traffic control is not needed, and identification of the dynamic characteristics of the bridge can be realized without installing a structure health detection system on the bridge; the bridge detection robot does not need to be fixed by manually distinguishing the widths of the guardrails during debugging before detection operation, self-adjustment and fixation of the robot can be achieved only through remote control of wireless signals, the safety risk possibly caused by high-speed passing vehicles to detection personnel in the detection process is reduced, and the detection efficiency is improved. And the detection cost and the labor cost are saved.

The invention relates to the technical field of bridge accessory structures, and provides a power generation device using bridge vibration and a bridge, the power generation device comprises a first piezoelectric part and a second piezoelectric part, the first piezoelectric part and the second piezoelectric part are both located in a cavity of a bridge body, and the first piezoelectric part and the second piezoelectric part are arranged in the cavity. One side of the first piezoelectric component is connected with one side of the second piezoelectric component, the other side of the first piezoelectric component is connected to the side wall through a first elastic component, and the other side of the second piezoelectric component is connected to the side wall through a second elastic component. The deformation directions of the first elastic component and the second elastic component are parallel to each other, the second piezoelectric component is compressed when the first piezoelectric component is stretched, and the second piezoelectric component is stretched when the first piezoelectric component is compressed. The device can generate power through vibration generated by the bridge, the power generation efficiency can be improved, and the continuity and stability of power generation are guaranteed.

The invention discloses a driving risk assessment method based on a coupled vibration model, and the method comprises the steps: S1, obtaining a vehicle dynamic parameter and a geometric dimension parameter, and building a vehicle dynamic model based on the vehicle dynamic parameter and the geometric dimension parameter by employing finite element analysis software or directly calculating a dynamic differential equation set; s2, acquiring bridge vibration excitation, roughness excitation and crosswind excitation; s3, inputting the bridge vibration excitation, the roughness excitation and the crosswind excitation into the vehicle model for coupled vibration analysis, and obtaining vehicle vibration response data; and S4, based on the vehicle vibration response data, obtaining a driving safety index and a comfort index, and performing risk assessment according to preset threshold values of safety and comfort. According to the method, multi-dimensional factors such as the wind environment, the vehicle dynamic response, the bridge structure vibration characteristic and the driving comfort degree are considered, and a high-precision and high-reliability risk assessment basis can be provided for a bridge operation unit.

The invention relates to the technical field of bridge safety, in particular to an intelligent defect analysis method based on bridge vibration data, and the method comprises the steps: collecting vibration signals through an acceleration sensor, and carrying out the grouping recording and storage; performing single-point failure test processing and continuous failure test processing on the bridge vibration data; calculating frequency domain features, time domain features and statistical features of the bridge vibration data, inputting the frequency domain features, the time domain features and the statistical features into an anomaly recognition model, and outputting a defect detection result; and carrying out visualization processing on the defect detection result and the bridge structure part with the corresponding serial number. The method is used for improving the reliability and accuracy of a bridge vibration monitoring system and effectively improving the intelligent defect analysis capability of bridge vibration data, so that more accurate support is provided for maintenance and safety of a bridge.

The invention discloses a lightweight spliced bridge vibration monitoring system for cooperative work performance intelligent perception, and belongs to the technical field of bridge structure health monitoring, and the lightweight spliced bridge vibration monitoring system comprises a lightweight targeted sensing subsystem which comprises a plurality of perception assemblies arranged in a targeted manner; the intelligent edge acquisition and transmission subsystem has an independent addressing function and a time synchronization function and is used for preprocessing and lightweight processing; the cloud edge collaborative storage management subsystem performs hierarchical storage, security control and efficient retrieval on the data to form monitoring data; and the cooperative performance perception early warning subsystem realizes state evaluation and graded early warning of the cooperative work performance of the spliced bridge through multi-index fusion. By adopting the lightweight spliced bridge vibration monitoring system for cooperative work performance intelligent perception, the problems of insufficient lightweight and targeting performance, low data processing, transmission and storage efficiency, and inaccurate cooperative performance evaluation, damage positioning and early warning of traditional spliced bridge vibration monitoring are solved.

The invention discloses a bridge detection method and system based on Internet of Things and big data, and the method comprises the steps: regularly obtaining bridge image data and bridge vibration data, and carrying out the preprocessing of the bridge image data and the bridge vibration data, and obtaining first monitoring data; performing state evaluation on the bridge according to the first monitoring data to obtain a bridge evaluation report, acquiring bridge real-time vibration data as second monitoring data according to the bridge evaluation report, and analyzing the second monitoring data to obtain a bridge health report; and generating a bridge use decision and a maintenance suggestion according to the bridge health report. Through secondary analysis and processing of the data, a comprehensive and complete bridge health report is obtained; the generated use decision can play a role in warning and early warning, for example, for a use decision in a dangerous state, a manager can be prompted to adjust the use of the bridge in time, cope with the crisis of the bridge in time, make up defects in time, and avoid danger caused by update lag.

The invention relates to the technical field of image processing, and discloses a method and system for high-precision acquisition of bridge vibration based on computer vision, and the method comprises the steps: determining a to-be-detected bridge, recording a vibration video of the to-be-detected bridge, carrying out the frame-by-frame extraction of the vibration video, and obtaining the image data of a plurality of to-be-detected bridges; performing gray processing on the image data to obtain gray image data of the to-be-detected bridge; performing edge detection on the grayscale image data by using a Canny operator to obtain a plurality of edge points of the to-be-detected bridge, and calculating the vertical displacement of each edge point one by one; calculating the sub-pixel precision of the edge displacement by using a Zernike moment, and obtaining the actual size data of the to-be-detected bridge; and calculating a scale factor corresponding to each piece of image data according to the sub-pixel precision and the actual size data, and calculating the actual vibration displacement of the to-be-detected bridge according to the scale factors. The defects of a traditional displacement sensor are overcome, and efficient, accurate and high-precision bridge displacement detection is achieved.

The invention relates to the technical field of bridge vibration reduction, in particular to a double-spring frequency conversion lever tuned mass damper device and a regulation and control method. The double-spring frequency conversion lever tuned mass damper device comprises a base, a lever, a mass block, a first spring and a second spring. Wherein the base is used for being connected with a to-be-damped structure; the middle of the lever is rotationally connected with the base; the mass block is arranged on the lever and located on one side of the base. The first spring and the second spring are located on the two sides of the base respectively, connected with the lever or abut against the lever and used for balancing the gravity of the mass block, and the first spring is located between the mass block and the base. The problems that in the prior art, when the spring end stress and the mass block end stress are amplified in a lever proportion, the pin shaft stress is too large, damping is too large, debugging is difficult, the pin shaft and a lever need to be thickened or made of special alloy, the manufacturing cost is increased, and potential safety hazards are possibly caused by material fatigue are solved.

The invention belongs to the technical field of vibration control, and discloses a tuned mass damping device for controlling low-frequency vertical bending vortex vibration of a large-span bridge, which consists of a fixed pulley, a mass block, a high-strength light force transmission cable, a spring, a hanging ring and a damper. Fixed pulleys and mass blocks are arranged at the positive and negative maximum displacement positions of a longitudinal bridge direction mode of a main beam respectively, a suspension system is formed by a full-length force transmission cable, and the gravity of the two mass blocks is basically balanced; the mass block is connected through the spring and is close to the bridge vibration control target frequency. When the bridge vibrates, the two mass blocks generate inertia forces which are opposite in direction but overlapped with each other, the driving system and the bridge form resonance, and therefore bridge vibration is effectively restrained. The gravity of the mass block can be self-balanced, the strength and the number of the springs are greatly reduced compared with those of a traditional TMD, any low-frequency tuning can be conducted in a vertical limited space, and the engineering cost is remarkably reduced. The device can be used for controlling vertical bending and torsional vibration of various engineering structures; the damper is replaced by an actuator, so that active control can be realized or the damper can be used as a structural excitation device.

A bridge vortex vibration detection method based on IMU and GNSS fusion positioning includes: first, collecting inertial measurement unit data, inputting it into a prediction module and calculating a double integral to generate a temporary displacement; then, performing bridge vortex-induced vibration (VIV) detection, and determining the occurrence of VIV by identifying harmonic motion and amplitude detection; if it is determined that there is a possibility of VIV vibration, the update module starts the GNSS module controller in the GNSS-RTK to activate the GNSS receiver and obtain GNSS-RTK data and multipath data; finally, after the update module receives the GNSS-RTK data and GNSS data quality, the GNSS and IMU data are fused through a Kalman filter; wherein the fused data is temporarily cached in the temporary displacement, realizing real-time monitoring of bridge vibration and VIV, and calibrating it when necessary to ensure the accuracy and reliability of the data. The present invention achieves a stable VIV detection rate while maintaining low power consumption, providing comprehensive protection for the safety and stability of the bridge structure.

The invention relates to the field of bridge structure performance monitoring, in particular to a method, system and device for recognizing vortex-induced vibration of a bridge, and the method comprises the steps: carrying out the mean removal and high-pass filtering of time history monitoring signal data # imgabs0 # of bridge vibration; determining a 0 phase point and a # imgabs2 phase point in the # imgabs1 #, and eliminating redundant data before the 0 phase point and redundant data after the # imgabs3 phase point to obtain a data sequence # imgabs4 # of a complete period; according to the # imgabs5 #, an amplitude sequence # imgabs7 # of an upper envelope line of the # imgabs6 # is obtained through calculation; the identification index # imgabs9 # of bridge vortex-induced vibration is obtained through calculation according to # imgabs8 #, # imgabs10 # is set to be a preset identification threshold value, when # imgabs11 # is larger than or equal to # imgabs12 #, vortex-induced vibration of the bridge is identified, the system adopts the method for identifying the bridge vortex-induced vibration, the device can execute the method for identifying the bridge vortex-induced vibration, and through the setting, the method for identifying the bridge vortex-induced vibration can be used for identifying the bridge vortex-induced vibration. The stability degree of the bridge vortex-induced vibration identification index is improved, and the calculation amount of the analysis process is reduced.

The invention relates to the technical field of vibration reduction and isolation devices, in particular to bridge vibration reduction equipment and a bridge vibration reduction optimization method and system. The bridge vibration reduction equipment comprises a friction pendulum support used for being installed between a main beam and a bridge pier; the damper is used for being installed between the main beam and the bridge pier; the damper is configured in the mode that when the relative displacement speed between the main beam and the bridge pier is smaller than a preset threshold value, the damper is kept in a dormant state and does not provide damping force; and when the relative displacement speed between the main beam and the bridge pier is larger than a preset threshold value, the damper enters an activated state to generate damping force between the main beam and the bridge pier until the relative displacement speed between the main beam and the bridge pier is smaller than the preset threshold value. The damper is arranged between the main beam and the bridge pier, so that damping force is generated when the bridge and the bridge pier have sudden displacement change, the stick-slip phenomenon of the bridge friction pendulum support is prevented, frequent stick-slip acceleration of support abrasion is avoided, and the service life of the friction pendulum support is prolonged.

The invention discloses a bridge damage detection method and system, and the method comprises the steps: collecting a bridge vibration signal through an acceleration sensor, carrying out the band-pass filtering preprocessing, converting a time domain signal into a frequency domain vibration signal through fast Fourier transform, and extracting a feature frequency through gradient change detection and threshold screening; a pairing difference value sequence of a monitoring characteristic frequency and a healthy baseline frequency is constructed, and a pairing sample T test is applied to perform statistical significance analysis on a difference value, so that the abnormal frequency change caused by structural rigidity degradation is effectively identified. According to the method, complex modal analysis is replaced by simplified frequency domain features, environmental interference influences are eliminated in combination with a pairing inspection mechanism, the micro-damage detection sensitivity and the false alarm resistance are remarkably improved, and the method is suitable for engineering scenes of long-term bridge monitoring and rapid damage screening.

The invention relates to the technical field of bridge detection, and discloses bridge crack automatic detection equipment, which is characterized in that a support column is mounted above a detection instrument to ensure the stability of the detection instrument, the height of the support column is adjusted through a hydraulic rod to adapt to bridges with different heights and spans, and the operation of the equipment can be controlled through a control panel. The device box is installed on the sliding block, various detection instruments can be placed in the device box, parameters such as the length, the width and the height of a bridge are measured through the distance measuring instrument, the vibration condition of the bridge is detected through the wireless data transmission bridge vibration detector, and the position and the depth of a concrete crack are detected through the concrete crack comprehensive detector. The industrial endoscope is used for detecting the internal structure condition of the bridge, the bridge flatness detector is used for detecting the flatness of the surface of the bridge, and all detection data are checked and recorded on the control panel so as to be conveniently analyzed and processed.

The invention discloses a pedestrian bridge vibration comfort evaluation platform considering human-bridge interaction. The pedestrian bridge vibration comfort evaluation platform comprises a self-energized sensing vibration force measurement platform and an analysis control system, the self-energized sensing vibration force measuring platform comprises a plurality of self-energized sensing force measuring tables and a servo control motor; friction nanometer generator self-powered three-way force measuring blocks are densely distributed on the self-powered sensing force measuring table; the analysis control system comprises a data acquisition module, a feedback control module and a data output module, acquires a three-dimensional pedestrian load on the self-energized sensing vibration force measuring platform in real time, calculates bridge dynamic response based on a pedestrian bridge finite element model, and further feeds back and controls the vibration state of the self-energized sensing vibration force measuring platform to simulate the actual vibration condition of the bridge; and finally, evaluating the vibration comfort of the bridge according to the dynamic response characteristics of the bridge in the whole loading process. According to the invention, real-time interaction between the computer end and the self-energized sensing vibration force-measuring platform is realized, sensing energy consumption is reduced, and a pedestrian bridge vibration comfort assessment result closer to a real situation is obtained.

The embodiment of the invention discloses a vibration control method and system for a steel-concrete combined box girder bridge, and the method comprises the steps: carrying out the vehicle-bridge coupling vibration analysis through building a space finite element model which accurately considers the interface slippage and shear hysteresis effect; an initial optimal parameter group of the multi-tuned mass damper is optimized and determined based on an analysis result, and installation tuning is carried out; in the operation stage of the bridge, vibration is monitored in real time through the sensor system, parameters of the damper are dynamically adjusted by the controller according to the deviation between measured data and a target value, and self-adaptive control is achieved. Thus, high-precision simulation, optimization design and intelligent control are combined, the problem that the control effect is poor due to model simplification and fixed parameters in a traditional method is solved, and vibration suppression accuracy and environmental adaptability are remarkably improved.

The invention discloses a bridge modal parameter identification method based on random subspace and biaxial vehicle response, belongs to the technical field of bridge health detection, and solves the problem of precision misalignment when a traditional indirect detection method synchronously identifies the inherent frequency, vibration mode and damping ratio of a bridge. And the technical bottleneck that the modal shape is easily interfered by bridge damping is overcome. The method comprises the following steps: eliminating vehicle frequency interference based on a double-axle vehicle-bridge contact point response algorithm, identifying the frequency and damping ratio of a bridge of detection data by using a random subspace method, and identifying a bridge modal shape by using a spatial relationship between front and rear contact point responses; contact point response signals are obtained through a double-axle vehicle-bridge contact point response algorithm, interference of vehicle frequency can be effectively removed, front and back contact point response signals are processed through a random subspace method, the accurate frequency and damping ratio of a bridge can be obtained, and when the vibration mode of the bridge is recognized, the vibration mode of the bridge is recognized. And the influence of bridge damping on bridge vibration mode identification can be effectively eliminated.

The invention provides a bridge vibration displacement detection method and system based on image enhancement and space-time tracking, and relates to the technical field of bridge detection and computer vision, and the method comprises the steps: obtaining a video image frame sequence of a bridge structure, carrying out the cooperative processing of image frames through employing an ACAE adaptive image enhancement algorithm, and obtaining an enhanced reconstructed image; inputting the reconstructed image into an AHSD-Net detection model, introducing a depth separable convolution module into a backbone network of the AHSD-Net detection model, performing spatial aggregation of preliminary features in a neck network by combining a dynamic upsampling mechanism, and finally outputting to obtain a target position detection result; based on a cascaded ST-Refine Track strategy, density denoising and position correction of a space dimension, cross-frame association of a time sequence dimension and adaptive smoothing processing of a state dimension are sequentially executed on a target position detection result, and a continuous and stable bridge vibration displacement curve is obtained. According to the invention, the displacement measurement precision and reliability are improved.

The invention relates to the technical field of wind tunnel tests, and discloses a bridge wind tunnel test device and test method.The device comprises a base, a lifting mechanism, a supporting frame, a swing mechanism and a bridge segment model; the base comprises a base and a mounting groove; the lifting mechanism is arranged in the mounting groove, the output end of the lifting mechanism is connected with the first end of the supporting frame, and the lifting mechanism is used for driving the supporting frame to do reciprocating rectilinear motion in the vertical direction; the second end of the supporting frame is provided with a swing mechanism, and the bridge segment model is rotatably arranged on the supporting frame through the swing mechanism. Displacement and vibration in the vertical direction are provided through the lifting mechanism, meanwhile, periodic rotation and swing around the axial direction of the bridge segment model are provided through the swing mechanism, three-degree-of-freedom motion simulation of the bridge model is achieved, a bridge vibration scene can be more truly and accurately reproduced, and the simulation precision is improved. Especially, scenes such as real bridge vortex-induced vibration and flutter can be reproduced, and the simulation performance and accuracy of bridge wind-induced vibration scene simulation are improved.