1827 results about "Bridge engineering" patented technology

The invention relates to the technical field of bridge engineering, in particular to a cable structure bridge design method adopting a BIM (Building Information Modeling) model, which comprises the steps of three-dimensional bridge foundation model construction, cable structure parameterization configuration, nonlinear mechanical simulation, construction error modeling, feedback optimization and the like. Through introduction of structured geological data and NURBS curved surface reconstruction, a geological-structure integrated model is realized. Adopting a genetic algorithm and a particle swarm optimization method to intelligently configure pile foundation and cable parameters; a construction error closed-loop adjustment mechanism is constructed through dynamic simulation and real-time tension feedback control; and finally, parameter correction write-back and BIM delivery model integration is realized. According to the invention, the design precision, the construction stage adaptability and the digital delivery integrity of the cable structure can be improved, and the method is suitable for cable structure bridge engineering with complex geology and high-precision control requirements.

The invention relates to the technical field of bridge engineering, in particular to a system and method for predicting the service life of a steel structure bridge after fatigue crack repair. The method comprises the steps that load data and stress data in the operation process of a bridge structure after fatigue crack repairing are collected; dynamic response characteristic parameters are extracted in combination with stress distribution characteristics of the fatigue crack repair area; performing multi-dimensional data fusion and preprocessing on the dynamic response characteristic parameters, and constructing a data set for training a deep learning algorithm; combining a deep learning algorithm and a fracture mechanics theory to construct a crack propagation rate prediction model and a residual life prediction model; according to the operation state of the bridge and the performance degradation law of the repairing area, the remaining life of the repaired structure is predicted, and multi-stage early warning is conducted. According to the method provided by the invention, bridge structure performance evaluation, life prediction and potential risk early warning can be realized, and the safety and reliability of bridge operation are ensured.

The invention discloses an on-bridge pedestrian abnormal behavior identification and early warning method based on intelligent monitoring, and relates to the technical field of bridge engineering, and the method comprises the steps: carrying out the registration of a current visible light image and a current infrared image, and obtaining a registration dual-mode image based on a current image coordinate system; considering current bridge deformation to establish a current coordinate mapping conversion model for mapping pixel coordinate points in the current image coordinate system to physical coordinate points of a current bridge physical space coordinate system; obtaining the current three-dimensional actual coordinates of the pedestrian; recognizing abnormal behaviors of the pedestrians on the bridge based on the current three-dimensional actual coordinates of the pedestrians and acquiring current dynamic risk score values of the pedestrians; and determining the current risk level of the pedestrian according to the current dynamic risk score value of the pedestrian and a preset risk threshold value to realize multi-level linkage protection response. The method provided by the invention solves the technical problem in the prior art that the current actual coordinate of the pedestrian is difficult to accurately obtain due to environmental interference, and the abnormal recognition of the pedestrian on the bridge is inaccurate.

The invention discloses a bridge safety assessment method based on multi-intelligent algorithm fusion, and belongs to the technical field of bridge engineering and intelligent algorithms. Aiming at the problems of insufficient multi-source data processing, lack of physical constraints and the like of a traditional evaluation technology, the method integrates multi-dimensional indexes through eight steps of multi-source data fusion preprocessing, physical information neural network construction, adaptive deep forest feature learning and the like, and generates a structural vulnerability index (SVI) to guide a maintenance decision. Innovation points comprise a five-algorithm deep coupling architecture, a physically embedded digital twinborn body, a dynamic weight proof theory and the like. The method has the advantages that high-precision recognition, interpretable prediction and visual decision making of bridge damage are achieved, evaluation precision and operation and maintenance efficiency are remarkably improved, and the method is suitable for full-life-cycle management of various bridges.

The invention relates to the technical field of bridge engineering, and discloses a concrete box girder prefabricated segmental girder formwork system and a construction method thereof.The concrete box girder prefabricated segmental girder formwork system comprises a connecting beam frame and fences, the fences are fixedly connected to the upper surface of the connecting beam frame, and an end formwork is detachably installed on the front surface of the connecting beam frame; a side formwork is fixedly connected to the lower portion of the front surface of the connecting beam frame, a side formwork is detachably installed on the upper surface of the side formwork, and an auxiliary formwork is detachably installed on the lower portion of the side formwork. Through the arrangement of the end formworks, the side formworks, the auxiliary formworks, the movable bottom formworks, the walking sliding shoes, the jacks, the reinforcement cages and the side formwork frames, a short line matching method is adopted for prefabrication, a formwork system is matched, reasonable hydraulic jack arrangement is adopted, precise formwork adjustment, supporting and demolding are achieved, the segmental beam prefabrication precision is improved, the bridge splicing quality is guaranteed, the construction process is optimized, and the construction efficiency is improved. All procedures are closely connected, construction time is shortened, and construction efficiency is improved.

The present invention relates to the field of virtual pre-assembly matching of bridge engineering components based on 3D point clouds, and particularly relates to a method for virtual pre-assembly matching of prefabricated beams based on design-measured point cloud models. An oriented bounding box is computed respectively for 3D point clouds of two prefabricated beams with assembly relationship therebetween, and two point cloud slices and design point cloud are formed; the two point cloud slices are respectively registered with the generated design point cloud by the iterative closest point algorithm; boundary features and corner features of a pre-assembly interface of two components to be assembled are fitted and extracted; and coarse matching and fine matching of the assembly interface are achieved by the Procrustes analysis algorithm and the iterative closest point algorithm in sequence, a matching degree error of the interface is computed, and an assembly result is evaluated. According to the present invention, design point cloud is introduced to achieve the screening of point clouds near features to be extracted, and posture adjustment on components to be assembled is performed by combining a plurality of algorithms, which not only improves the degree of automation and reduces the manual intervention, but also improves the precision of virtual pre-assembly matching and saves the computation time.

The invention relates to the technical field of bridge engineering construction, in particular to a bridge deck concrete flatness detection and correction method, which comprises the following steps: synchronously acquiring bridge deck point cloud, elevation and crack data through a three-dimensional laser scanner, a laser profiler and an ultrasonic sensor, and fusing to generate a three-dimensional digital model; defects such as local protrusions and wave deformation are recognized based on an intelligent analysis algorithm, causes are analyzed, and correction process parameters such as milling, cladding, grouting or ultrathin layer pouring are generated in a targeted mode; operation is executed through equipment such as a finish milling machine, closed-loop control is realized by combining real-time monitoring of a laser profiler, and finally, a traceable digital file is formed through laser detection, inspection and acceptance of an unmanned aerial vehicle and data archiving. By means of the method, the pass percent of the flatness of the bridge floor can be increased to 94% or above, the maximum height difference is controlled within 3 mm, the maintenance period of the bridge is prolonged, and the maintenance cost is reduced.

The invention discloses a nondestructive testing device for a steel profile and a testing method of the nondestructive testing device. According to the method disclosed by the invention, the ultrasonic technology is combined with optical imaging, so that synchronous detection of surface and internal defects can be completed at one time. Ultrasonic waves penetrate through the interior of the steel profile, and hidden defects such as cracks and air holes are accurately recognized; the optical camera module captures visible problems such as surface scratches and corrosion in real time. The integrated detection mode avoids the tedious process of step-by-step operation required by a traditional method, for example, magnetic powder detection of surface defects and ultrasonic scanning of an internal structure are not needed, the detection period is greatly shortened, and the method is especially suitable for steel structure buildings, bridge engineering and other scenes with high requirements for detection efficiency and has good application prospects. The full-process automatic design effectively reduces the influence of human intervention, and ensures the scanning continuity of the detection area; the intelligent algorithm automatically analyzes the ultrasonic echo signal and the optical image data, and judges the defect level according to the preset standard, thereby avoiding subjective misjudgment of manual visual inspection.

The invention relates to a quality risk assessment method for a highway bridge engineering construction stage and a medium, and the method comprises the steps: determining the quality influence factor indexes of the highway bridge engineering construction stage, carrying out the dimension reduction through employing a PCA method, and constructing a quality risk index system, wherein the quality risk index system comprises a risk factor layer and a corresponding index layer; based on the quality risk index system, adopting a DEMATEL method to calculate the subjective influence weight of each index; based on the quality risk index system, an improved CRITIC method is adopted to calculate the objective weight of each index; based on the subjective influence weight and the objective weight, determining a comprehensive weight of each index by adopting a minimum identification information theory; and based on the comprehensive weight, combining the determined grade standard interval, and based on a variable fuzzy set theory, carrying out quality risk assessment, and outputting a quality risk assessment result. Compared with the prior art, the method has the advantages of improving the reliability of risk grade evaluation and the like.

The invention provides a bridge settlement monitoring method and system, and relates to the technical field of bridge engineering monitoring, and the method comprises the steps: firstly selecting a component surface region directly associated with settlement conduction in a bridge structure as a visual clue node, and constructing a bridge structure visual clue network; setting shooting parameters of image acquisition equipment according to spatial distance parameters in the bridge structure visual clue network to form a multi-clue collaborative image set; then, carrying out settlement conduction characteristic modeling on the multi-clue collaborative image set, extracting a visual characteristic variable quantity, establishing a corresponding relation with a settlement conduction path, and generating a settlement conduction characteristic matrix; inputting the settlement conduction characteristic matrix into a preset model, converting the settlement conduction characteristic matrix into settlement displacement parameters of corresponding components, and integrating the settlement displacement parameters to form bridge settlement state information; and finally, based on the settlement state information, generating a monitoring instruction containing a settlement conduction path identifier and settlement parameters of each component, and transmitting the monitoring instruction to a monitoring terminal. The method is comprehensive, accurate, economical and efficient, and can effectively guarantee the safety of the bridge structure.

The invention discloses a bridge engineering-oriented foundation pile quality detection system, which relates to the technical field of engineering quality detection, and comprises a data acquisition module configured to acquire detection data including foundation pile construction parameters, geological environment data, stress wave signals and geometric dimension parameters, the wave velocity correction module is configured to correct a standard wave velocity through a dynamic coupling algorithm, the defect depth calculation module is configured to calculate the defect depth of a foundation pile defect, and the credibility evaluation module is configured to output a credibility correction coefficient and feed back the credibility correction coefficient to the wave velocity correction module by quantifying errors of detection data; according to the method, through multi-physical field wave velocity correction, pile diameter-defect depth double correction and credibility quantitative iteration, a high-precision, objective and traceable integrated solution is systematically provided for bridge engineering foundation pile quality detection.

The invention discloses a cable-stayed bridge tension and compression support service life evaluation method and system under random traffic flow load, and belongs to the field of bridge engineering and structure health monitoring, and the method comprises the steps: carrying out the statistical analysis of traffic load data, building a random traffic flow load model, and generating a load spectrum; correcting stay cable force and modal frequency based on bridge monitoring data, and constructing a refined multi-scale finite element model; a unit fatigue vehicle load is applied to the model, a stress influence line is obtained, a rain flow counting method is adopted to calculate stress amplitude, cycle index and average stress, the stress amplitude, the cycle index and the average stress are converted into daily average equivalent stress amplitude and equivalent daily cycle index through a fatigue damage equivalence principle, and the fatigue life of the tension-compression support is evaluated by utilizing a Miner criterion. According to the method, the problem that the influence of three-way alternating stress on bolt fatigue damage cannot be accurately reflected in the prior art is solved, the service life prediction precision of the cable-stayed bridge tension and compression support is improved, the damage of the tension and compression support can be early warned in advance, and data support is provided for safe operation and maintenance of the cable-stayed bridge.

The invention relates to a large-span bridge anti-seismic performance optimization and evaluation system based on digital twinning, and belongs to the field of computer and bridge engineering. The optimization and evaluation system comprises a data acquisition and pre-processing module, a model updating module and a performance evaluation and optimization module; the optimization and evaluation method comprises the following steps: identifying the modal and frequency of a structure, obtaining the modal shape and natural vibration frequency of a bridge, and establishing a digital twinborn model of an object bridge; and according to the multi-objective optimization design function, carrying out supercomputing driven damping device parameter optimization, outputting an optimal parameter combination, and controlling hierarchical response of the bridge in an earthquake. The artificial waves generated based on the design response spectrum of the bridge can fully consider the dynamic characteristics of the large-span cable-stayed bridge and the seismic oscillation characteristics of the design site; meanwhile, only time history analysis of single seismic oscillation is involved in the anti-seismic optimization design process, the calculation amount of optimization design is greatly reduced, the comprehensive influence of each nonlinear factor on the bridge seismic response is better considered, and the complexity of large-span bridge anti-seismic optimization is remarkably simplified.

The invention relates to the technical field of bridge engineering intelligent construction, discloses a digital twinborn and multi-physics field simulation-based lattice pier assembly error intelligent prediction method, and aims to construct a lattice pier assembly error prediction model. The lattice pier assembly error prediction model is composed of a channel independent feature extraction module of multi-physics field data, a self-adaptive space-time coupling and multi-factor dynamic fusion module and a training lattice pier assembly error prediction model, the multi-physical field data channel independent feature extraction module maps data of each physical field to a high-dimensional feature space through calculation, and according to a state space model, the adaptive space-time coupling and multi-factor dynamic fusion module introduces a plurality of factors to dynamically adjust weights of the physical fields in different time steps. Carrying out adaptive fusion on the processed physical field data through a space-time coupling function to obtain coupled physical field data; and finally, taking the output of the two as the input, and combining a regression model to predict the lattice pier assembly error.

The invention relates to the field of bridge engineering, in particular to a bridge structure toughness dynamic evaluation method and system based on digital twinning, and the system firstly collects the environment, geometry and performance information of a bridge, and then establishes an accurate bridge digital twinning model; a bridge structure toughness prediction model is systematically constructed by using a space-time diagram convolutional network, and the performance degradation process of a bridge in extreme weather can be predicted; meanwhile, toughness evaluation indexes are formulated by the system, and accurate performance evaluation of real-time monitoring data is realized; through multi-source data fusion, the system improves the comprehensiveness and accuracy of data acquisition; the prediction model based on the space-time diagram convolutional network significantly improves the accuracy of performance degradation prediction; a scientific and efficient tool is provided for bridge maintenance and management, and safe operation of the bridge in extreme weather is effectively guaranteed.

The invention relates to the technical field of bridge engineering, and discloses an RGV rail car automatic operation control method and system, and the method comprises the steps: obtaining a target transportation site of an RGV rail car, and carrying out the initial path planning of the target transportation site based on an optimized algorithm; driving according to a preset driving path, performing real-time environment scanning through a sensor, and analyzing scanned data; based on the real-time environment data, utilizing a TEB time elastic band algorithm to perform dynamic path re-planning on a predetermined driving path, driving according to the obstacle avoidance driving path, obtaining the residual electric quantity of the rail car, utilizing a charging demand decision model to judge the residual electric quantity, and if the residual electric quantity cannot support the rail car to drive to the target transportation place, determining that the rail car is not driven to the target transportation place. If yes, acquiring a nearest charging position, and generating a charging driving path according to the charging position. Various people and obstacles in the running process can be effectively avoided, and the safety and smoothness of the transportation process are guaranteed.

The invention belongs to the field of bridge engineering construction monitoring and intelligent control, and provides a Beidou digital twinning system for bridge steel member precision hoisting and a hoisting method aiming at the problems of low efficiency and poor real-time performance of on-site hoisting of a segment steel member in a large-span bridge structure. The system comprises a multi-source data acquisition module, a coordinate conversion module, an attitude calculation module, a three-dimensional virtual model construction module, a hoisting motion state monitoring module and a digital twinning module. The attitude resolving module calculates a standard attitude vector by using a comprehensive deep learning model according to the degree-of-freedom data, the attitude information and the movement speed, and performs attitude resolving based on the standard attitude vector to obtain an attitude angle of the bridge steel member; the hoisting motion state monitoring module can perform safety early warning and posture adjustment when the bridge steel member is abnormal; and the digital twin module can synchronously update the attitude information and the three-dimensional virtual model of the bridge steel member to obtain the current space trajectory and historical state of the bridge steel member.

The invention relates to the technical field of bridge engineering detection and repair, in particular to a bridge crack repair effect prediction method and system based on performance simulation, and the method comprises the following steps: obtaining basic data and environmental load data of a target bridge, and matching at least two candidate repair schemes from a preset repair scheme library; constructing an initial performance model before repair, and calculating an initial bearing capacity loss rate and a crack propagation rate; quantifying the interaction influence of the multi-modal data through a coupling factor matrix, and iteratively calculating the repair condition of a set time period after repair to obtain an initial simulation result; and collecting real-time monitoring data in a set time period in the repairing process and after repairing, and inputting the real-time monitoring data into a preset LSTM adaptive correction model to obtain a corrected simulation result. According to the method, the long-term repair condition after repair can be accurately calculated, the accuracy of a prediction result and the environmental adaptability are remarkably improved, and a scientific basis is provided for long-term service performance pre-judgment.

The invention relates to a wall type-double column combined pier structure system, and belongs to the technical field of bridge engineering. The structure system mainly comprises a cover beam, a swinging pier, a replaceable corrugated steel web wall, a pier bottom energy dissipation device, a swinging steel base, a bearing platform, an unbonded prestressed tendon and the like. A pier bottom energy dissipation device is arranged on the lower portion of the swing pier and composed of energy dissipation steel bars, an outer wrapping steel plate, a bottom steel plate and fixing lug plates. A replaceable corrugated steel web wall is arranged between two piers, and an upper flange plate is directly installed on a cover beam through embedded high-strength bolts and fixed to a bearing platform through a swing steel base. Unbonded prestressed reinforcements penetrate through the center positions of the swinging bridge piers. According to the structural system, a collaborative energy consumption-graded swing mechanism of'corrugated steel web wall deformation energy consumption-corrugated steel web wall swing-pier swing and energy consumption 'is formed under the earthquake action, earthquake energy can be dissipated more effectively, structural residual deformation is reduced, and the structural shock resistance and function restorability are improved.

The invention discloses an automatic control system for a railway bridge static load bending test, which relates to the technical field of bridge engineering detection and comprises an intelligent sensing layer, a digital twin engine, an intelligent control layer, a trusted data management layer, a green energy supply layer and a man-machine interaction layer. The equipment health prediction model integrates oil temperature, vibration and current data to predict mechanical faults, performs early warning 30 minutes in advance, automatically switches to a slow loading mode when the crack propagation rate exceeds the limit, breaks through a passive protection mode of single threshold alarm, realizes multi-dimensional active protection from structural damage to equipment degradation, and drives finite element model updating through sensor data. The simulation prediction reverse correction loading strategy and the RBF neural network online correction material parameters are simulated and predicted, parameter iteration is triggered when the deviation is larger than a set value, the island problem that a traditional BIM only uploads data in a one-way mode is solved, closed-loop verification of test data and design parameters is achieved, and simulation precision is improved.

The invention relates to the technical field of bridge engineering and structure health monitoring, in particular to a safety assessment method and system based on a bridge digital twin model. The method comprises the following steps: performing three-dimensional reconstruction according to geometric information of a bridge to obtain a BIM model of the bridge; based on the BIM model, fusing multi-dimensional special parameters to construct a simulation digital twinborn model of the bridge; correcting the simulation digital twinborn model by using historical monitoring data; and in combination with real-time monitoring data and the corrected simulation digital twinborn model, carrying out safety assessment on the bridge. According to the method, the bridge digital twinborn model is constructed by fusing multi-dimensional special parameters, then the bridge digital twinborn model is dynamically corrected based on historical monitoring data, and finally, the actual state and performance change of the bridge are accurately mapped in real time through the corrected bridge digital twinborn model. The problem of comprehensive, accurate and real-time assessment of bridge structure safety is solved.

The invention discloses a high-pier large-span extra-large bridge suspended pouring beam hanging basket construction method, and belongs to the field of bridge engineering construction.The method comprises the following steps that hanging basket rails are installed, the precision is controlled, and a hanging basket comprising a double-channel-steel main truss, a manganese steel sling, an arc-shaped flow guide plate and a honeycomb formwork is assembled; grading pre-pressing is carried out according to the specified multiple of the design load, and the pre-camber of the template is corrected by adopting a BP neural network to ensure that the finished bridge linear error meets the requirement; a mechanical-hydraulic-electrical integrated intelligent control system is deployed, and the traveling speed and synchronism of the hanging basket are controlled through double-oil-cylinder driving, a 5G digital twin platform and an edge computing technology, so that rapid alarm is realized when the load is abnormal; segmental circulation construction is carried out, and when the environment wind speed reaches a set value, a hydraulic rail clamping device is automatically locked; a model is established by using ANSYS software, and simulation verification is performed on multiple types of key working conditions to ensure that the safety coefficient of the structure meets the specification requirement. The construction precision and safety are guaranteed, and the method adapts to complex environments.

The invention relates to the technical field of bridge engineering structure health monitoring, in particular to a service life prediction method and system for a bridge connection part, and the method comprises the steps: collecting the strain of a grouting sleeve, a reinforcement-grouting interface ultrasonic reflection signal and environment temperature and humidity data through a distributed sensor array; a three-dimensional dynamic void rate model is generated through fusion of a spatial topological mapping algorithm, a correlation function of load circulation and void expansion is established, the dynamic void rate is input into a bond strength coupling degradation model, after strength attenuation is quantized in combination with steel bar corrosion data and bond failure early warning is triggered, stress redistribution is calculated through multi-physics coupling simulation, and the dynamic void rate is obtained. Early warning is taken as a starting node, the actual load spectrum and temperature and humidity data are combined, Monte Carlo sampling is adopted to simulate rigidity degradation and output the residual life probability, the system comprises a multi-source collaborative sensing unit, a micro-void evolution analysis unit and a life prediction decision unit, and the safety control precision of bridge connection parts is improved.

The invention relates to the technical field of bridge engineering material tests, and discloses a bridge structure corrosion fatigue coupling test method and system based on artificial intelligence. The bridge structure corrosion fatigue coupling test method based on artificial intelligence comprises the following steps: accurately expressing interaction among physical fields by constructing a multi-physical field coupling mathematical model; a deep reinforcement learning algorithm is applied, an environment parameter cooperative control model is built, and multi-environment-parameter high-precision self-adaptive regulation and control are achieved; building an environment acceleration test equivalence mapping model, and balancing the optimal acceleration ratio and equivalence of the acceleration test; constructing a generalized predictive control model to achieve multi-physical field cooperative regulation and control; a real-time system identification and parameter updating model is constructed, multi-physical field interaction influence is compensated, and stable control is achieved; according to the method, the test environment control precision is improved, multi-environment-condition cooperative control is realized, the test period is shortened, the test authenticity and the result stability are improved, and reliable data support is provided for bridge structure safety assessment.

The invention relates to the technical field of track bridge engineering, in particular to a high-speed railway track-bridge system earthquake-caused residual irregularity prediction method, which comprises the following steps of: determining a target object, and constructing an earthquake-caused irregularity database based on historical earthquake oscillation data of the target object; based on the earthquake-induced irregularity damage database, constructing an earthquake-induced peak irregularity deep learning prediction model fused with the vibration mode superposition method, and performing prediction by adopting the earthquake-induced peak irregularity deep learning prediction model to obtain an earthquake-induced peak irregularity prediction value; calculating an earthquake-caused residual irregularity equivalent coefficient based on earthquake-caused peak irregularity and earthquake-caused residual irregularity in the earthquake-caused irregularity damage database; and earthquake-caused residual irregularity is predicted based on the predicted earthquake-caused peak irregularity predicted value and the earthquake-caused residual irregularity equivalent coefficient. According to the method, the engineering safety and reliability of the result are ensured based on the mapping relation of the probability assurance rate, and the method has high efficiency and safety and is suitable for practical engineering application.

The invention belongs to the technical field of bridge engineering, and aims to eliminate the problem of systematic underestimation of web bearing capacity under the condition of standard effective loading length. The invention provides a method for correcting a local pressure bearing capacity calculation formula of a steel beam web, which comprises the following steps of: identifying and determining a key parameter ratio and an engineering application range thereof by carrying out sensitivity parameter analysis on a bending reduction coefficient; on the basis of the reference engineering case, fixed values are taken from part of parameters, and other geometric quantities are inversely calculated; based on a preset variable sequence, finite element models are established in Abaqus in batches, and the ultimate bearing capacity and the flange longitudinal stress level of each model are extracted; the standard calculation value is corrected according to a finite element result, the corrected ultimate bearing capacity of the steel beam web is calculated, and a corrected bending reduction coefficient is obtained accordingly; and finally, fitting a corrected formula about the regularized slenderness ratio on the correction coefficient by taking the specification parameter as an independent variable to obtain an expression capable of directly replacing the original specification. The method can significantly improve the calculation precision.

The invention discloses a cable-stayed bridge cross brace optimization system based on system reliability and an intelligent algorithm, which relates to the technical field of bridge engineering, and comprises a multi-source parameter input module used for collecting and processing data such as a main beam section, stay cable parameters, a strain sequence, a vibration sequence, a satellite cloud picture, a traffic monitoring flow, laser point cloud and the like; and outputting the structured design data, the monitoring data flow, the dynamic load spectrum, the probability distribution model and the construction error correction parameters. According to the invention, all-dimensional data such as design, monitoring, load, materials and construction errors are integrated through the multi-source parameter input module, and multi-level and dynamic reliability evaluation is carried out on the component, the subsystem and the system level by using the system reliability analysis module, so that the component failure probability, the system reliability index time sequence and the like can be output; therefore, the real reliability level of the cross brace of the cable-stayed bridge in the whole life cycle is reflected more accurately, and the one-sidedness of a traditional method is avoided.

The invention discloses a construction method and device for controlling the perpendicularity of a high pier, and belongs to the technical field of bridge engineering construction. Determining a plumb aligner control point; mounting a creeping formwork bracket; installing a laser target; correcting and installing an inclination measuring instrument; centering the point position of the laser plumb aligner; measuring a deviation value between the laser beam and the pier body; collecting data of an inclination measuring instrument; and pier body concrete is poured. According to the method, through triple measurement rechecking and chemical deviation calculation, the perpendicularity control precision and efficiency of high pier construction are remarkably improved, and the method is suitable for high pier construction in a complex environment.

The invention relates to the technical field of bridge engineering detection, in particular to a distributed optical fiber strain sensing detection system for a bridge engineering dynamic and static load test, and the system comprises a distributed optical fiber strain sensing module which is used for obtaining the strain information of different positions of a bridge; the dynamic and static load signal acquisition and conversion module is used for converting the strain signal into a strain electric signal suitable for transmission and processing; the temperature compensation module is used for carrying out temperature compensation on the strain signal according to the change of the collected environment temperature; the data processing and analyzing module is used for processing and analyzing the strain electric signal subjected to temperature compensation so as to obtain the strain distribution condition and related parameters of the bridge structure under the action of dynamic and static loads; and the monitoring and early warning module is used for monitoring the state of the bridge in real time according to the result obtained by the data processing and analyzing module and sending out an early warning signal when the strain of the bridge is abnormal. The problem that in the prior art, comprehensive, high-precision and real-time dynamic and static load strain monitoring cannot be carried out on bridge engineering is solved.

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.