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A method and system for identifying bridge dynamic loads based on machine vision positioning

A dynamic load and positioning recognition technology, applied in character and pattern recognition, machine/structural component testing, instruments, etc., can solve the problems of not being able to obtain the weight distribution of axles, limiting the service life of equipment, and becoming stuck in traffic passages, etc. , to achieve the effect of excellent performance, convenient construction and wide applicability

Active Publication Date: 2022-04-26
CHINA RAILWAY SIYUAN SURVEY & DESIGN GRP
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] The identification of vehicle loads on existing bridges is generally divided into dynamic weighing methods and static weighing methods. Among them, static weighing methods are the most widely used, and static weighing methods generally require special scales to detect overweight vehicles, which are costly and require Stop the vehicle and weigh it, which may easily cause traffic jams for bridges with large traffic flow
Using this weighing system often becomes a traffic jam point
Moreover, static weighing can only monitor the total weight, but cannot obtain the weight distribution of each axle of the vehicle
[0003] Another dynamic weighing method based on the pavement uses the equipment laid on the bridge deck to weigh the vehicles on the bridge deck. This method causes a certain degree of damage to the road surface, and the traffic flow is easy to cause damage to the equipment, which limits the use of the equipment. Useful period

Method used

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  • A method and system for identifying bridge dynamic loads based on machine vision positioning
  • A method and system for identifying bridge dynamic loads based on machine vision positioning
  • A method and system for identifying bridge dynamic loads based on machine vision positioning

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Embodiment 1

[0059] This embodiment discloses a method for identifying bridge dynamic loads based on machine vision positioning, such as figure 1 include:

[0060] S100. Obtain the characteristic parameters of the bridge structure to be analyzed. Specifically, in this embodiment, S100 specifically includes:

[0061] S101. The finite element software identifies the displacement-influenced surface of the bridge;

[0062] S102, the static load test identifies the influence line of the bridge calibration point;

[0063]S103. Obtain the correlation coefficient between the influence line of the bridge calibration point identified by the static load test and the displacement influence line identified by the corresponding finite element software;

[0064] S104. Obtain required characteristic parameters of the bridge structure.

[0065] S200. Identifying the real-time dynamic deflection time-history curve of the bridge structure by self-induction, extracting the bridge dynamic deflection value,...

Embodiment 2

[0101] This embodiment discloses a bridge dynamic load recognition system based on machine vision positioning, including: a bridge structure characteristic parameter acquisition unit, a dynamic deflection time history curve acquisition unit, an adaptive filtering algorithm unit, a license plate recognition unit, a license plate coordinate acquisition unit, a license plate Type identification unit, bridge dynamic load acquisition unit; where:

[0102] The bridge structural characteristic parameter acquisition unit is used to obtain the bridge structural characteristic parameters to be analyzed. Wherein, the working method of the bridge structure characteristic parameter acquisition unit has been described in detail in Embodiment 1, so this embodiment will not repeat it here.

[0103] The dynamic deflection time-history curve acquisition unit is used to self-inductively identify the real-time dynamic deflection time-history curve of the bridge structure, extract the bridge dynam...

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Abstract

A method for identifying dynamic loads of bridges based on machine vision positioning, including: extraction of bridge structure characteristic parameters; self-induction identification of real-time dynamic deflection of bridge structures; adaptive algorithm for filtering real-time dynamic deflection; The self-sensing camera recognizes the license plate coordinates; the binocular camera self-learning recognizes the vehicle type; the gateway adaptively calculates and recognizes the dynamic load of the bridge. Aiming at the limitations and effect differences of the traditional bridge load recognition function, the present invention improves the overall scheme of bridge load recognition based on machine vision positioning. Improvements have been made in aspects such as self-decision-making, reducing the dependence on the type of bridge structure, and having great portability and versatility.

Description

technical field [0001] The invention relates to the technical field of dynamic identification of bridge loads, in particular to a method and system for identifying dynamic loads of bridges based on machine vision positioning. Background technique [0002] The identification of vehicle loads on existing bridges is generally divided into dynamic weighing methods and static weighing methods. Among them, static weighing methods are the most widely used, and static weighing methods generally require special scales to detect overweight vehicles, which are costly and require Stopping the vehicle and weighing it will easily cause traffic jams for bridges with large traffic flows. Using this weighing system often becomes a traffic jam point. Moreover, static weighing can only monitor the total weight, but cannot obtain the weight distribution of each axle of the vehicle. [0003] Another dynamic weighing method based on the pavement uses the equipment laid on the bridge deck to wei...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06V20/62G06V20/52G01M5/00
CPCG01M5/0008G06V20/52G06V20/62G06V2201/08G06V20/625
Inventor 文望青严爱国李桂林瞿国钊殷鹏程严定国张晓江姜洪劲赵丹阳张杰王鹏宇胡方杰梁金宝许三平张玲
Owner CHINA RAILWAY SIYUAN SURVEY & DESIGN GRP