Bridge damage detection device based on machine vision

Abstract

The utility model relates to the technical field of road traffic safety, in particular to a bridge damage detection device based on machine vision. A bridge damage detection device based on machine vision comprises a moving module, a cross beam, sliding rails, a driving module and an electric power module, the number of the sliding rails is two, the moving module is installed between the two sliding rails, the cross beam is installed above the two sliding rails, the moving module is in sliding connection with the sliding rails, and the driving module is connected with the driving module. A driving module and a monitoring module are installed below the mobile module, and the power module is in circuit connection with the driving module and the monitoring module. According to the utility model, the moving module, the driving module and the monitoring module are integrated, so that the full-automatic process of bridge structure damage detection is realized; automation, accuracy, flexibility and reliability are realized.

Description

Technical Field

[0001] The utility model relates to the technical field of road traffic safety, and more particularly to a bridge damage detection device based on machine vision. Background Art

[0002] As an important part of transportation infrastructure, the safety of bridges is directly related to the safety of people's lives and property and the smooth flow of traffic. With the increase in the service life of bridges and the influence of the natural environment, the bridge structure gradually becomes damaged and aged, posing a threat to the safety of bridges. Cracks on bridges, especially on viaducts, seriously affect the structural strength of bridges, and their location is relatively hidden and difficult to find.

[0003] The current method of using manual crack detection is limited by the structural characteristics of elevated bridges, making it difficult to conduct comprehensive crack detection on bridges. Traditional bridge damage detection methods mainly rely on manual inspections and simple physical testing methods. These methods have limitations such as low efficiency, poor accuracy, and susceptibility to human factors. They are difficult to meet the needs of modern bridge management. In the process of using manual crack detection, there are many limiting factors such as human errors, time efficiency, labor costs, and construction safety.

[0004] Therefore, providing a machine vision-based bridge damage detection device that can significantly improve the efficiency and accuracy of bridge damage detection is an urgent problem that needs to be solved by those skilled in the art. Utility Model Content

[0005] In order to overcome the deficiencies of the prior art, the purpose of the present invention is to provide an intelligent, high-precision, machine vision-based bridge damage detection device that is not affected by human factors.

[0006] To achieve the above objectives, the present invention provides the following technical solutions, which mainly include:

[0007] A bridge damage detection device based on machine vision includes a mobile module, a crossbeam, a slide rail, a drive module and a power module. There are two slide rails, the mobile module is installed between the two slide rails, a crossbeam is installed above the two slide rails, the mobile module is slidably connected to the slide rails, a drive module and a monitoring module are installed below the mobile module, and the power module is respectively connected to the circuits between the drive module and the monitoring module.

[0008] Preferably, the mobile module includes a mounting platform and a slider, wherein sliders are provided on both sides of the mounting platform, the sliders are engaged with the slide rails on both sides of the mounting platform, the sliders are slidably connected to the slide rails, and a driving module is installed under the mounting platform.

[0009] Preferably, the driving module includes a motor, a driving gear, a rack, a box, a limit block and a chain. The box is installed under the mounting platform, and a motor is installed inside the box. The slide rail is provided with a rack on the side facing the mobile module. The motor transmission shaft passes through the box and is connected to the driving gear. The driving gear is meshed with the rack. The other side of the slide rail is provided with a ring chain towards the mobile module. A limit block is provided on the other side of the box, and the limit block is engaged with the ring chain.

[0010] Preferably, the crossbeam is in a "C" shape as a whole, and a mounting bracket is installed above the crossbeam, and the mounting bracket is installed on the back side of the bridge.

[0011] Preferably, a monitoring module is installed at the rear of the box.

[0012] Preferably, a power module is installed on one side of the guide rail.

[0013] It can be seen from the above technical solution that compared with the existing technology, the utility model will realize a fully automated process for bridge structure damage detection by integrating a mobile module, a drive module and a monitoring module. Automated detection significantly reduces manual participation and improves detection efficiency, which is especially advantageous on large bridges or areas that are difficult to reach manually. The precise coordination of the motor drive in the drive module and the mechanical structures such as the slide rail, rack, and chain ensures the smooth and rapid movement of the mobile module on the bridge, thereby realizing a rapid scan of the entire bridge surface and solving the problem of inaccurate manual detection of bridge damage. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are merely embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying any creative work.

[0015] Figure 1 It is a structural diagram of the present utility model.

[0016] Figure 2 This is a structural diagram of the drive module of the utility model.

[0017] Figure 3 This is a structural diagram of the mobile module of the utility model.

[0018] Figure 4 It is a structural diagram of the slide rail of the utility model.

[0019] Figure 5 This is a schematic diagram of the structure of the monitoring module of the utility model.

[0020] Explanation of the reference numerals: 1-mobile module, 101-mounting platform, 102-slider, 2-crossbeam, 201-mounting bracket, 3-slide rail, 4-drive module, 401-motor, 402-drive gear, 403-rack, 404-chain, 405-box, 406-limit block, 5-power module, 6-monitoring module. DETAILED DESCRIPTION

[0021] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0022] Example

[0023] A bridge damage detection device based on machine vision, such as Figure 1 As shown, it includes a mobile module 1, a beam 2, a slide rail 3, a drive module 4 and a power module 5. There are two slide rails 3. The mobile module 1 is installed between the two slide rails 3. The beam 2 is installed above the two slide rails 3. The mobile module 1 is slidably connected to the slide rails 3. The drive module 4 and the monitoring module 6 are installed below the mobile module 1. The power module 5 is respectively connected to the circuits between the drive module 4 and the monitoring module 6.

[0024] In order to further optimize the above solution, the mobile module 1 includes an installation platform 101 and a slider 102. Sliders 102 are provided on both sides of the installation platform 101. The sliders 102 are engaged with the slide rails 3 on both sides of the installation platform 101. The sliders 102 are slidably connected to the slide rails 3. A driving module 4 is installed under the installation platform 101. The mobile module 1 is the core moving component of the entire detection device, which is responsible for moving along a predetermined path on the bridge so as to perform comprehensive detection of different areas of the bridge.

[0025] In order to further optimize the above scheme, the driving module 4 includes a motor 401, a driving gear 402, a rack 403, a box 405, a limit block 406 and a chain 404. The box 405 is installed under the mounting platform 101, and the motor 401 is installed inside the box 405. The slide rail 3 is provided with a rack 403 on the side facing the mobile module 1. The transmission shaft of the motor 401 passes through the box 405 and is connected to the driving gear 402. The driving gear 402 is engaged with the rack 403. The other side of the slide rail 3 facing the mobile module 1 is provided with a ring chain 404, and the other side of the box 405 is provided with a limit block 406. The limit block 406 is engaged with the ring chain 404. The driving module 4 provides power for the mobile module 1, drives it to move along the slide rail 3, and adjusts the moving speed and direction as needed.

[0026] In order to further optimize the above solution, a monitoring module 6 is installed at the rear of the box 405. The monitoring module 6 adopts machine vision technology. Through advanced image processing and recognition algorithms, the monitoring module 6 can automatically analyze the image of the bridge surface and identify signs of damage such as cracks, rust, and deformation. This non-contact detection method not only reduces the potential damage to the bridge structure, but also greatly improves the accuracy and efficiency of the detection. The data recorded by the monitoring module 6 can be uploaded to the data center in real time through wireless transmission, etc., to facilitate subsequent data analysis and management.

[0027] In order to further optimize the above solution, the crossbeam 2 is in a "C" shape as a whole, and a mounting bracket 201 is installed above the crossbeam 2, and the mounting bracket 201 is installed on the back side of the bridge.

[0028] In order to further optimize the above solution, a power module 5 is installed on one side of the guide rail. The circuit connection between the power module 5 and the drive module 4 and the monitoring module 6 ensures that the power supply of the entire detection device is stable and reliable during operation. This integrated design reduces the impact of external factors on the detection process and improves the overall stability and reliability of the system.

[0029] To further optimize the above solution, comprehensive bridge damage inspection can assess the overall health of the bridge, including its load-bearing capacity, stability, durability, etc. This helps to formulate scientific and reasonable maintenance plans and repair programs, thereby extending the service life of the bridge.

[0030] Working principle: By integrating the mobile module 1, the driving module 4 and the monitoring module 6, a fully automated process for bridge structure damage detection is realized. The mobile module 1 slides freely between the two slide rails 3 and is connected to the slide rails 3 through the engagement and sliding of the slider 102. The monitoring module 6 is installed at the rear of the box 405 and moves with the mobile module 1. It can capture high-definition images or videos of the bridge surface in real time, provide accurate data support for subsequent damage identification, and realize precise position control.

[0031] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. Reference can be made to the common and similar parts between the various embodiments. For the devices disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple, and the relevant parts can be referred to the method description.

[0032] The above description of the disclosed embodiments will enable one skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to one skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Therefore, the present invention is not limited to the embodiments shown herein but is intended to conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A bridge damage detection device based on machine vision, characterized in that: The invention comprises a mobile module (1), a crossbeam (2), a slide rail (3), a drive module (4) and a power module (5); the slide rail (3) is provided with two, the mobile module (1) is installed between the two slide rails (3), a crossbeam (2) is installed above the two slide rails (3), the mobile module (1) and the slide rail (3) are slidably connected, a drive module (4) and a monitoring module (6) are installed below the mobile module (1), and the power module (5) is respectively connected to the circuit between the drive module (4) and the monitoring module (6); The mobile module (1) includes a mounting platform (101) and a slider (102), wherein the sliders (102) are provided on both sides of the mounting platform (101), the sliders (102) are engaged with the slide rails (3) on both sides of the mounting platform (101), the sliders (102) are slidably connected to the slide rails (3), and a driving module (4) is installed below the mounting platform (101); The driving module (4) comprises a motor (401), a driving gear (402), a rack (403), a box (405), a stop block (406) and a chain (404); the box (405) is installed below the mounting platform (101); the motor (401) is installed inside the box (405); the rack (403) is provided on the side of the slide rail (3) facing the moving module (1); the transmission shaft of the motor (401) passes through the box (405) and is connected to the driving gear (402); the driving gear (402) is meshed with the rack (403); the other side of the slide rail (3) facing the moving module (1) is provided with an annular chain (404); the other side of the box (405) is provided with a stop block (406); the stop block (406) is engaged with the annular chain (404).

2. The machine vision-based bridge damage detection device according to claim 1, characterized in that: The crossbeam (2) is in a "C" shape as a whole. A mounting bracket (201) is mounted above the crossbeam (2), and the mounting bracket (201) is mounted on the back side of the bridge.

3. The bridge damage detection device based on machine vision according to claim 1, characterized in that: A monitoring module (6) is installed at the rear of the box (405).

4. The machine vision-based bridge damage detection device according to claim 1, characterized in that: A power module (5) is installed on one side of the guide rail.

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