23 results about "Bridge Collapses" patented technology

The invention belongs to the technical field of bridge monitoring, and particularly relates to an intelligent detection and early warning method and system for bridge collapse, and the method achieves the continuous and synchronous monitoring of a key region of a bridge through the deployment of a composite sensing node with a multi-physical field sensing capability. The time-frequency domain joint analysis and empirical mode decomposition technology is combined to effectively separate environmental interference and structure real response components; constructing a local rigidity evolution trajectory based on the structural response dominant component, and identifying a starting moment when the rigidity is significantly reduced by using a dual-threshold criterion; and multi-scale precursor features in the damage evolution process are further mined through time alignment recombination, space thermodynamic diagram generation and multi-region collaboration analysis. According to the method, the accuracy of small damage identification and the reliability of early warning are remarkably improved, the structure performance degradation process can be stably tracked under the actual service condition with complex environmental interference, and interpretable and traceable intelligent early warning support is provided for the bridge collapse risk.

The invention relates to an expressway bridge collapse identification and early warning method based on vehicle dynamic monitoring, which belongs to the technical field of bridge safety monitoring, and comprises the following steps: if a vehicle falls into a bridge in a target bridge section, comparing with a bipartite model threshold based on a vertical acceleration, a vertical acceleration change rate and a three-axis resultant acceleration; whether the vehicle falls on the bridge or not is judged; under the condition that the vehicle falls to the bridge and falls to the water surface, the number of vehicles falling to the bridge, the first disaster correlation of the weather data associated with the vehicle falling to the bridge and the second disaster correlation of the social media data associated with the vehicle falling to the bridge are obtained; determining the credibility of the collapse state of the target bridge section based on the number of the vehicles falling into the bridge, the first disaster correlation of the vehicles falling into the bridge associated with the meteorological data and the second disaster correlation of the vehicles falling into the bridge associated with the social media data; and based on the credibility of the collapse state of the target bridge road section, issuing early warning information of the collapse state of the target bridge road section.

The application relates to a bridge collapse identification method and system based on vehicle mobile terminal sensing data, and belongs to the technical field of bridge safety monitoring. The method comprises the following steps: in the case that a target vehicle is determined to be located on a bridge section based on relative positions, monitoring driving acceleration of the target vehicle according to IMU data of a vehicle mobile terminal; in the case that a mutation occurs in vertical acceleration in the driving acceleration of the target vehicle, judging whether the target vehicle appears a bridge falling state caused by bridge collapse based on the vertical acceleration and synthetic lateral acceleration; if the target vehicle appears the bridge falling state caused by bridge collapse, obtaining jerk of the vertical acceleration, and determining bridge falling time information of the target vehicle based on the jerk; and based on the bridge falling time information of the target vehicle and falling heights of multiple vehicles when falling off the bridge, adjusting the credibility of the bridge collapse based on the falling heights of the multiple vehicles when falling off the bridge, so as to improve the determination accuracy and credibility of the bridge collapse state.

The invention discloses a test method for judging whether a damaged T-beam bridge target can meet the passing requirement of an armored vehicle, and belongs to the field of test and evaluation. According to the method, factors such as brake, wheel track and wheel base of the armored vehicle are considered, an equivalent loading block is used for simulating the armored vehicle, and a loading test is carried out at the most unfavorable position of a T-beam bridge target through graded load loading. If the bridge collapses in the loading process, taking a lower level of load to represent the target traffic capacity of the damaged T-beam bridge; and if the bridge is not collapsed, loading a larger level of load until the load is loaded to the maximum tonnage of the simulated armored vehicle, and finally judging whether the T-beam bridge target can meet the passing of the armored vehicle or not. According to the test method, the equivalent loading block is used for replacing the armored vehicle, a graded load loading mode is used, the traffic capacity of the damaged T-beam bridge target is obtained, the test cost is saved, safety risks are avoided, and accurate judgment can be provided for whether the military armored vehicle passes through the damaged T-beam bridge target or not.

The embodiment of the invention discloses a method and equipment for determining ship-collision-resistant fortification ship type parameters of a bridge and a medium, and relates to the technical field of bridge risk assessment. The method comprises the steps that a ship-to-bridge collision model is constructed, and the ship-to-bridge collision model is used for reflecting the relation among ship-to-bridge displacement, mass and rigidity; determining a calculation formula of a net displacement ratio and an energy ratio of the ship and the bridge according to the ship-bridge collision model; according to the calculation formula and the law of conservation of energy, determining an expression of the initial navigational speed of the ship about the energy absorbed by the pier; determining a navigational speed threshold expression for preventing the bridge from collapsing under different ship tonnages according to the expression and the maximum threshold of the bridge pier displacement; and according to the ship speed threshold expression, determining fortification ship type parameters of the bridge pier. According to the embodiment, fortification ship type parameters can be determined according to bridge pier structure characteristics and service stages.

The application discloses a bridge collapse early warning method and system based on a bridge image and a neural network. The method comprises the following steps: acquiring a bridge image of a bridge prone to collapse; performing pretreatment and feature extraction on the bridge image to obtain bridge high-level features containing bridge structures and vehicle distribution; inputting the bridge high-level features containing the bridge structures and the vehicle distribution into a trained neural network model to output a prediction result of bridge collapse and vehicle drop; evaluating whether the bridge has a bridge collapse risk or a vehicle drop risk based on the prediction result of the bridge collapse; and performing bridge collapse early warning of a corresponding level according to the evaluation result of the bridge collapse risk or the vehicle drop risk. The application realizes bridge collapse prediction by extracting high-level features of a bridge image and combining a neural network, and can perform real-time early warning according to the predicted bridge collapse risk, thereby improving the accuracy of bridge collapse prediction and the real-time performance of early warning.

The present application belongs to the technical field of intelligent transportation, and relates to a bridge structure state intelligent monitoring method and system based on multi-modal optical feature cross-validation. The present application ingeniously utilizes the existing and ubiquitous mobile light source (i.e. the vehicle lights of the driving vehicles) on the night road and the optical reflection target (i.e. the facade contour marker) on the bridge, takes the interaction of the two as a kind of new passive monitoring signal, combines the tail light point trajectory of the dynamically captured vehicles passing through the bridge, and constructs an intelligent monitoring system of cross-validation and mutual complementation by fusing the double optical feature abnormalities of the dynamic traffic flow (vehicle tail light) and the static facility (bridge marker anomaly), so as to realize the instantaneous early warning of the bridge collapse and other major risks with higher reliability and lower false alarm rate.

The invention relates to a bridge collapse dual-mode trigger grading early warning method, and the method achieves the grading early warning through the combined judgment of a risk through a dual-mode trigger mechanism based on data deviation and load type recognition, and the combination of the self-adaptive adjustment of a threshold value based on reinforcement learning. The invention further relates to an early warning system using the bridge collapse dual-mode triggering grading early warning method. The early warning system comprises a multi-mode data acquisition and abnormity triggering module, a model fine adjustment module, a risk judgment module and an optimization and synchronization module. According to the invention, the early warning response speed is improved, the balance of rapidity and reliability of the early warning system is realized, and the accuracy and practicability of the early warning system are improved.

The utility model provides a road and bridge collapse automatic alarm system, comprising a first mounting plate arranged on a first pavement slab body; a mounting column is arranged on the first mounting plate; the second mounting plate is arranged on the second pavement slab body; a rotating column and an alarm body are adjacently arranged on the second mounting plate; the alarm rod is rotatably arranged on the rotating column; one end of the alarm rod sleeves the mounting column, and the other end of the alarm rod is arranged below the alarm body; a limiting block and an adjusting block are arranged on the mounting column, an action space is formed between the limiting block and the adjusting block, and one end of the alarm rod sleeves the action space; the alarm device is arranged on a fence of the road and bridge and is connected with the alarm body; the road and bridge collapse automatic alarm system provided by the utility model is in a detection state before the road and bridge collapse, and at the moment, excessive energy consumption is not needed; and when collapse occurs, the collapse condition can be detected in time, and an alarm is given, so that accidents are avoided.

The invention discloses a bridge collapse accident flexible water curtain blocking system based on Beidou automatic monitoring, which comprises an intelligent control terminal, a base, a water curtain device mounted on the base, a high-brightness laser projection device, a tweeter and a detection device, the water curtain device, the high-brightness laser projection device, the tweeter and the detection device are connected with the intelligent control terminal, and the intelligent control terminal receives accident warning information sent by the bridge monitoring and early warning system based on Beidou automatic monitoring and controls the water curtain device to form a water curtain barrier at a bridge entrance. The high-brightness laser projection device projects high-brightness laser displaying accident warning information on the water curtain barrier, meanwhile, the tweeter gives out alarm sound to prevent vehicles from entering the bridge, and the detection device collects bridge running state information and vehicle information in the bridge and uploads the information in real time. According to the invention, the barrier-free flexible blocking effect which is clear and visible from a long distance in all weathers in daytime or sunny days is realized, and the effect of effectively blocking vehicles at the bridge entrance is realized.

The invention relates to a construction method for newly building an arch bridge in situ of an old bridge. The construction method comprises the steps that arch foot foundations are newly built at the two ends of a main beam of the old bridge, and steel pipe arch construction is conducted on the arch foot foundations; a plurality of slings are installed on the steel pipe arch, supporting ropes are installed at the bottom of the old bridge girder section by section, and each supporting rope section is connected with the corresponding sling; the old bridge girder is cut and dismantled segment by segment with the old bridge pier as the center, and the old bridge girder is transported to the set position segment by segment; and a new bridge girder is erected, and the new bridge girder is connected with the steel pipe arch through the slings to form the newly-built arch bridge. A sling on a new bridge steel pipe arch is used for lifting an old bridge girder, and the old bridge girder is symmetrically cut and dismantled section by section with an old bridge pier as the center, so that the risk that an old bridge collapses due to unbalanced stress in the dismantling process is reduced, normal navigation in the dismantling and building construction process is guaranteed, and the construction efficiency is improved. The technical problems that in the prior art, the construction period for dismantling and rebuilding a conventional old bridge is long, the old bridge is prone to collapse in the dismantling process, and navigation is interrupted are solved.

The present application belongs to the field of automobile active safety and intelligent transportation technology, and relates to a night road and bridge collapse early warning method and system based on visual perception. The method comprises the following steps: step one, establishing a normal disappearance rule benchmark model of a preceding vehicle tail light and a normal optical characteristic model of a roadside vertical sign; step two, performing preliminary calculation of a collapse confidence, giving a first collapse confidence A1, and simultaneously analyzing the roadside vertical sign, if the optical characteristics of the vertical sign detected do not conform to the normal optical characteristic model rule, then giving a second collapse confidence A2; step three, comparing the bridge collapse comprehensive confidence A with a preset threshold value to determine whether to issue a warning. The present application can quickly detect bridge collapse hazards at night, provide instant warning for vehicles in motion, and avoid the delay and non-real-time problems of traditional fixed sensors or manual inspection.

The utility model discloses a bridge collapse monitoring, alarming and damage reducing device, which relates to the technical field of bridge safety monitoring and comprises an abutment and a cover beam in a bridge. The bridge collapse monitoring, alarming and loss reducing device comprises a power supply module for supplying power to the whole device, an abutment monitoring assembly for monitoring the displacement of bridge parts, a monitoring box for recording the state of a bridge, a signal lamp display module for prompting the state of the bridge, and a centralized monitoring terminal arranged outside the bridge, the abutment monitoring assemblies are arranged on the abutments of the bridges, each abutment monitoring assembly comprises a distribution box and a displacement change sensing switch, and the plurality of abutment monitoring assemblies are connected in series for redundancy. When the displacement of the abutment and the bridge exceeds the preset value, the bridge of the fixed section is monitored through the abutment assemblies connected in series, and the monitoring accuracy is improved.

The invention discloses a bridge collapse alarm system based on an inclination angle and acceleration, and relates to the technical field of bridge safety monitoring, a distributed acquisition unit is adopted, acquisition nodes are arranged at key positions of a bridge at preset intervals, and vertical acceleration data and inclination angle data of the bridge are monitored and acquired in real time; the information is collected to the acquisition unit through wireless communication; the data processing host receives and stores the data, determines a reference characteristic average inclination angle and an inherent frequency reference value, processes the real-time data, extracts a rigidity degradation index, an inclination angle variable quantity and a torsion variable quantity, and calibrates state identifiers for bridge segments according to the rigidity degradation index, the inclination angle variable quantity and the torsion variable quantity; the host synthesizes each identifier to evaluate a risk bridge segment, triggers grading alarm signals of different risk grades, and issues the grading alarm signals to the sound-light alarm execution unit through a wireless network, and the sound-light alarm execution unit responds to the signals and issues on-site sound-light warnings; through accurate monitoring and intelligent analysis, real-time early warning of bridge collapse risks is realized, and bridge safety is guaranteed.

The present invention provides a bridge collapse prevention buffer chain that can prevent stress concentration at the contact points between rings when an impact load is applied. [Solution] A bridge collapse prevention buffer chain 1, comprising a ring connector 2 in which multiple rings are connected to each other, and a covering 3 covering the ring connector 2, connects a bridge superstructure such as a bridge girder to a bridge substructure such as a bridge abutment or bridge pier to prevent the bridge superstructure from falling, wherein the ring connector 2 is covered with a rubber elastic material except for a part of the end rings 21a (21b) at the ends, the end rings 21a (21b) and adjacent rings 22a (22b) are brought into contact, and the wire diameter of the ring steel material of one or both of the end rings 21a (21b) and adjacent rings 22a (22b) is set to be larger than the wire diameter of the ring steel material of the other rings of the ring connector 2.

The invention discloses a slope landslide and bridge collapse disaster monitoring and early warning method and system, and relates to the technical field of traffic safety monitoring, and the method comprises the steps: constructing a heterogeneous graph structure of multi-source nodes, inputting the heterogeneous graph structure into a heterogeneous graph attention coding model for feature fusion, and outputting a first alarm score of each node; weighting the first alarm score based on image confidence of adjacent camera nodes to obtain a re-calibrated alarm score of each node; and constructing time sequence input, performing graph convolution and time convolution processing on the time sequence input based on a dynamic space-time graph convolution network, when a node re-calibration alarm score exceeds a threshold value, triggering an early warning blocking action, returning a processing result as a training sample, and performing incremental updating on the model. According to the method provided by the invention, large-range and full-link disaster monitoring is realized, and the false alarm rate is reduced. Risk features are captured at the same time in the time sequence dimension and the space topology, and early warning of the disaster trend is achieved.

The invention discloses a bridge intelligent safety alert method and system for road traffic, and the method comprises the steps: collecting vibration frequency, displacement deformation and stress distribution data in real time, and generating a state monitoring data set of a bridge structure in combination with bridge deck vehicle load distribution information obtained by an image recognition unit; based on the state monitoring data set, utilizing a pre-trained deep neural network model to carry out structure health degree evaluation, and outputting a structure safety situation map containing a structure stability index and a potential risk area; generating multi-color early warning signals corresponding to different danger levels according to the structure safety situation map; and triggering a grading response mechanism according to the multi-color early warning signal, and automatically controlling the intelligent warning device installed at the bridgehead position to switch a warning mode and execute a corresponding warning combination. According to the embodiment of the invention, the prospective accurate perception of the bridge collapse risk can be realized, and the automation level of safety alert and the emergency disposal efficiency are improved by means of a graded early warning and linkage control mechanism.

The invention relates to the related technical field of intelligent cable bridges, in particular to an intelligent large-span cable bridge crumple active compensator with break angle allowance and a compensation method thereof.The active compensator is arranged between two bridges and comprises two sets of frame structures; the frame structure comprises a first frame body and a second frame body which are rotationally connected through a shaft piece. The first cross arm is arranged between the first frame body and the second frame body, the second cross arm is fixed with the first cross arm, a cross rod is arranged on the first cross arm, and two symmetrically arranged cylindrical springs sleeve the periphery of the cross rod; the two first sliding blocks are arranged on the first cross arm in a sliding mode, the first sliding blocks are further connected with the cross rod in a sliding mode, and the head ends of the cylindrical springs are connected with the first sliding blocks; active compensation of the cable bridge is achieved through the cylindrical spring, the adverse effect of the longitudinal offset factor on the telescopic compensation capacity in the length direction of the cable bridge is avoided, and compared with a passive compensation mode, effective guarantee is provided for the stability of the large-span cable bridge.

The invention relates to the technical field of bridge structure safety monitoring, and discloses a simple bridge collapse alarm device based on relative displacement of a beam pier, comprising a transmission assembly connected with the beam pier and used for sensing the relative displacement between a bridge body and the beam pier; the mounting shell is located on one side of the bridge body; the triggering assembly is used for converting the relative displacement generated by the transmission assembly into different circuit access states; the alarm assembly is used for generating alarm signals according to different circuit access states output by the trigger assembly so as to realize collapse alarm of the bridge body; a cavity is formed in the installation shell and used for containing the trigger assembly and the alarm assembly. According to the invention, by arranging the alarm assembly, high and low resistance contact pins are correspondingly matched with different sliding strips, so that the displacement degree of the beam pier can be converted into differential electric signals, signal processing is carried out in cooperation with the power panel, graded early warning is realized, and displacement risk grades are accurately distinguished.

The application belongs to the technical field of bridge anti-collision, and particularly relates to an ultrahigh vehicle impact bridge early warning system, which comprises a monitoring module, a data processing module and an early warning module, wherein the monitoring module and the early warning module are connected with the data processing module; the monitoring module comprises a bridge-under monitoring unit and a bridge vehicle monitoring device connected with the data processing module, and the early warning module comprises a bridge-under ultrahigh vehicle early warning device and a bridge early warning device connected with the data processing module; the data processing module comprises a bridge deformation prediction model and a bridge collapse prediction model, the bridge deformation prediction model is used to predict whether the bridge-under clearance at the moment when a bridge-under pre-passing vehicle reaches a bridge position meets the height of the bridge-under pre-passing vehicle, and the bridge collapse prediction model is used to predict the residual bearing capacity of the bridge after the pre-passing vehicle impacts the bridge. The application greatly reduces the possibility of vehicle impact on the bridge.

The application relates to the technical field of traffic transportation, and provides a warning method and system for vehicles affected by a road-bridge disaster event based on trajectory entropy. The behavior feature sequence of a vehicle in a time period before and after a target road-bridge disaster event is extracted, and the trajectory entropy value of the vehicle is calculated through a trajectory entropy model, so as to identify the vehicle affected by the disaster event. Based on the vehicle set affected by the disaster event, the warning range of the target road-bridge disaster event is dynamically determined according to real-time traffic flow data. Through the vehicle trajectory big data, the abnormal degree of the vehicle driving behavior is quantified, the vehicle affected by the disaster is accurately, efficiently and dynamically identified, the warning range is scientifically determined, reliable data support is provided for emergency response and traffic relief, and the processing efficiency and safety of the road-bridge disaster event are effectively improved.

The invention discloses a bridge collapse disaster early warning method and system, and relates to the technical field of bridge monitoring. The method comprises the following specific steps: acquiring multi-source health monitoring data of a bridge in real time, wherein the multi-source health monitoring data comprises strain monitoring data, displacement monitoring data, settlement monitoring data, vibration monitoring data, crack monitoring data and environment and load data; performing preprocessing operation on the multi-source health monitoring data and then performing data fusion to obtain multi-source fusion data; constructing a bridge damage evolution prediction model by taking the multi-source fusion data as input based on the long and short term memory neural network, and predicting the dynamic damage evolution trend of the bridge; calculating collapse probabilities of the bridge in different time scales by adopting Monte Carlo simulation in combination with the static risk reference value and the dynamic damage evolution trend of the bridge; and setting a critical threshold: when the collapse probability reaches the critical threshold, triggering an early warning signal, and performing graded early warning. According to the method, collapse precursor signals are recognized in advance, and early warning is accurate and efficient.