Road tunnel concrete surface disease inspection system and method

Abstract

The invention provides a highway tunnel concrete surface disease inspection system and method, and belongs to the highway tunnel technology.The highway tunnel concrete surface disease inspection system comprises an initial inspection module, a reinspection module and a spot inspection module.According to the highway tunnel concrete surface disease inspection system, a track is installed on the tunnel wall, an automatic inspection device can automatically walk on the track, and the inspection efficiency is improved; and then detecting apparent diseases in a detection area by using an optical method, wherein the following main indexes and functions can be realized: identifying and positioning a crack of more than 0.2 mm in a target area; identification and positioning of other diseases or defects (such as water seepage and epidermis shedding) in the target area are realized; the positioning precision of diseases such as cracks, water seepage or epidermis falling is required to be within + / -(2-3) mm; and continuous viewing of the apparent area photos of the target area is realized, that is, further judgment and analysis of diseases can be further realized through other auxiliary photos by overall determination of disease positions.

Description

Technical Field

[0001] The invention relates to the technical field of highway tunnels, and in particular to a highway tunnel concrete surface disease inspection system and method. Background Art

[0002] Highway tunnel operation, maintenance and rescue are important components of tunnel management and are important means to institutionalize, standardize and scientificize tunnel operations. The equipment in the tunnel is widely distributed, with many types and quantities and complex composition. For a long time, people have been mainly doing manual operation and maintenance of tunnels. If the operation status of the tunnel equipment can be automatically monitored for a long time, so as to evaluate the health status of the tunnel equipment and formulate targeted operation and maintenance plans, then corresponding maintenance measures can be taken according to the actual situation, basically eliminating the safety hazards of the tunnel and avoiding major accidents in the tunnel. This requires the construction of a tunnel automatic inspection system that can perform daily monitoring of the tunnel.

[0003] The tunnel automatic inspection system combines advanced robotics technology with non-destructive sensing Internet of Things technology to obtain long-term, real-time, and spatially free and continuous information on the equipment operating status inside the tunnel, and analyze various status characteristics including tunnel structure status, equipment working status, vehicle driving status, road surface status, and tunnel meteorological status, so as to understand the changes caused by damage or degradation in tunnel operation, and use diagnostic methods to determine the occurrence, location, and extent of damage, and evaluate the normal operation health of the tunnel. Abnormalities can be detected early before the critical point that endangers the safety performance of the tunnel structure arrives, and early warning signals can be triggered for the tunnel under special climate and traffic conditions or when the tunnel operation status is seriously abnormal, providing a basis and guidance for tunnel maintenance, care and management decisions.

[0004] However, the tunnel inspection robots currently on the market integrate various functions into one, and there is no robot or corresponding tunnel inspection system that can perform daily and regular inspections of minor diseases / defects on the tunnel concrete surface.

[0005] The information disclosed in this background technology section is only intended to enhance the understanding of the overall background of the invention and should not be regarded as an acknowledgment or any form of suggestion that the information constitutes the prior art already known to a person skilled in the art. Summary of the invention

[0006] The object of the present invention is to provide a robot for daily inspection and periodic inspection of minute diseases / defects on the surface of tunnel concrete and a corresponding tunnel inspection system and method.

[0007] To achieve the above object, the present invention provides the following solutions:

[0008] A highway tunnel concrete surface disease inspection system, comprising:

[0009] Initial inspection module, re-inspection module and random inspection module.

[0010] Optionally, the initial inspection module is used to control the automatic inspection system to automatically inspect from the starting point of the track to the end point of the track. During the inspection process, the electric zoom lens always works in the large focal length mode, and the entire tunnel surface is finely scanned, photographed and stored in a high-resolution mode.

[0011] Optionally, the re-inspection module is used to automatically move to the tunnel disease location for high-resolution re-inspection based on the disease location information in the most recent initial inspection results in the system, and the re-inspection cycle is set as needed.

[0012] Optionally, the sampling inspection module is used to control the automatic inspection system to perform inspections according to a specified optical resolution or a specified historical disease location or a specified partial section of the tunnel.

[0013] Optionally, a track is installed on each of the left and right tunnel walls, with a total of 2 sets of automatic inspection devices to achieve full coverage of the entire tunnel surface.

[0014] Optionally, the system includes a charging station, a wireless router, a track, an automatic inspection device and a software system.

[0015] Optionally, the automatic inspection device includes: a robot body, a one-dimensional electric pan-tilt platform and an optical detection subsystem; the robot body is composed of a suspension mechanism, a track automatic dust cleaning mechanism, an automatic walking mechanism, an embedded industrial computer, a 4G / Wi-Fi module, a mileage detection and reset circuit, a wireless / contact charging management circuit, a power module and a lithium battery pack;

[0016] The optical detection subsystem is composed of an electric zoom lens, an infrared fill light and an infrared surface array camera;

[0017] The software system includes image acquisition and control software running on an embedded industrial computer, server software and front-end programs deployed on a cloud server; the server software is tunnel surface defect recognition and processing software, which takes AI visual algorithm as the core and integrates traditional visual algorithm as an auxiliary, combining AI algorithm and traditional algorithm to give full play to their respective advantages to meet the specific applications of defect detection and dimensional measurement.

[0018] Optionally, in the optical detection subsystem, the lens adopts an infrared short-wave 30x 420mm continuous zoom lens; the infrared fill light: adopts an infrared light with a wavelength of 850nm, which is invisible to the human eye to avoid affecting normal driving; the camera adopts an array camera with a quantum efficiency of up to 80% in the 850nm band;

[0019] The calculation formula for optical detection resolution d is:

[0020] d=D×ps / f

[0021] d——optical detection resolution, unit: mm / pixel;

[0022] D——Detection distance, unit: m;

[0023] ps——camera pixel size, unit um;

[0024] f——focal length of the lens, in mm.

[0025] A road tunnel surface disease inspection method includes: initial inspection, re-inspection and random inspection.

[0026] The specific steps of the initial inspection are:

[0027] Initial inspection begins; synchronize network time and start system self-inspection; determine whether the system has faults; if there are faults, send a repair message via SMS or WeChat; end initial inspection and wait for maintenance; if there are no faults, the robot body automatically walks a fixed distance and stops, and the zoom lens works in the large focal length mode; the electric pan-tilt head rotates to a fixed angle and stops, and fine image acquisition / storage is performed on the body; determine whether the current cross-section acquisition is completed. If not, the electric pan-tilt head rotates to a fixed angle and stops again, and fine image acquisition / storage is performed on the body; if completed, determine whether the track end point has been reached. If not, the robot body automatically walks a fixed distance and stops again, and the zoom lens works in the large focal length mode; if the track end point has been reached, the pictures / videos temporarily stored locally are uploaded to the cloud server; end initial inspection and wait for the next re-inspection;

[0028] The steps of the re-examination are specifically as follows:

[0029] Re-inspection starts; network time is synchronized and system self-inspection starts; determine whether the system has faults. If so, send a repair message via SMS or WeChat; end re-inspection and wait for maintenance; if there is no fault, the inspection device automatically moves to determine whether the inspection device has reached the historical defect location. If not, return to the automatic walking step of the inspection device; if it has reached the historical defect location, the zoom lens works in the large focal length mode, and fine pictures are collected / stored locally; determine whether all defects have been re-inspected. If not, return to the automatic walking step of the inspection device and execute in sequence; if the re-inspection is completed, upload the pictures / videos temporarily stored locally to the cloud server; end re-inspection and wait for the next re-inspection;

[0030] The random inspection is an inspection performed by the automatic inspection device according to a specified optical resolution or a specified historical disease location or a specified partial section of the tunnel.

[0031] Optionally, it also includes: mileage detection and cumulative error elimination; the mileage detection adopts a high-resolution incremental photoelectric rotary encoder, and is calculated based on the photoelectric encoder resolution of 5000P / R and the outer diameter of the walking wheel of 50mm, then its pulse equivalent is: 50mm×3.14159 / 5000P=0.0314mm / P; a magnet is buried every 20m or 50m in the track to trigger the Hall detection switch in the robot body. Each time the Hall detection switch is triggered, the mileage is automatically reset and the pulse counting starts again.

[0032] Compared with the prior art, the present invention has the following beneficial effects:

[0033] The highway tunnel concrete surface disease inspection system provided by the present invention installs a track on the tunnel wall, and the automatic inspection device can realize automatic walking on the track, and then detect the apparent disease in the detection area by optical method, which can achieve the following main indicators and functions:

[0034] 1) Identify and locate cracks larger than 0.2 mm in the target area;

[0035] 2) Identify and locate other diseases or defects (such as water seepage, epidermal peeling, etc.) in the target area;

[0036] 3) The positioning accuracy of cracks, water seepage or epidermal peeling is required to be within ±(2-3)mm;

[0037] 4) Realize continuous viewing of photos of the surface area of ​​the target area, that is, by determining the location of the disease overall, further judgment and analysis of the disease can be achieved through other auxiliary photos. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0039] Figure 1 A schematic diagram of the composition of an automatic inspection system provided in an embodiment of the present invention.

[0040] Figure 2 A schematic diagram of the field of view of an optical detection subsystem provided in an embodiment of the present invention.

[0041] Figure 3 A schematic diagram of the flow of the initial inspection method provided in an embodiment of the present invention.

[0042] Figure 4A schematic diagram of a re-inspection method flow chart provided in an embodiment of the present invention.

[0043] Figure 5 It is a schematic diagram of a conventional automatic tunnel inspection system in the prior art. DETAILED DESCRIPTION

[0044] 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 described embodiments 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 creative work are within the scope of protection of the present invention.

[0045] The object of the present invention is to provide a robot for daily inspection and periodic inspection of minute diseases / defects on the surface of tunnel concrete and a corresponding tunnel inspection system and method.

[0046] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0047] Embodiment 1:

[0048] This embodiment provides a highway tunnel concrete surface disease inspection system and method, such as Figure 1 and Figure 2 , the system includes:

[0049] Initial inspection module, re-inspection module and random inspection module.

[0050] Furthermore, the initial inspection module is used to control the automatic inspection system to automatically inspect from the starting point of the track to the end point of the track. During the inspection process, the electric zoom lens always works in the large focal length mode, and the entire tunnel surface is finely scanned, photographed and stored in a high-resolution mode.

[0051] Furthermore, the re-inspection module is used to automatically move to the tunnel defect location for high-resolution re-inspection based on the defect location information in the most recent initial inspection result in the system, and the re-inspection cycle is set as needed.

[0052] Furthermore, the sampling inspection module is used to control the automatic inspection system to perform inspections according to a specified optical resolution or a specified historical disease location or a specified partial section of the tunnel.

[0053] Furthermore, a track is installed on each of the left and right tunnel walls, and a total of 2 sets of automatic inspection devices are used to achieve full coverage of the entire tunnel surface.

[0054] Furthermore, the system includes a charging station, a wireless router, a track, an automatic inspection device and a software system.

[0055] Furthermore, the automatic inspection device includes: a robot body, a one-dimensional electric pan-tilt platform and an optical detection subsystem; the robot body is composed of a suspension mechanism, a track automatic dust cleaning mechanism, an automatic walking mechanism, an embedded industrial computer, a 4G / Wi-Fi module, a mileage detection and reset circuit, a wireless / contact charging management circuit, a power module and a lithium battery pack;

[0056] The optical detection subsystem is composed of an electric zoom lens, an infrared fill light and an infrared surface array camera;

[0057] The software system includes image acquisition and control software running on an embedded industrial computer, server software and front-end programs deployed on a cloud server; the server software is tunnel surface defect recognition and processing software, which takes AI visual algorithm as the core and integrates traditional visual algorithm as an auxiliary, combining AI algorithm and traditional algorithm to give full play to their respective advantages to meet the specific applications of defect detection and dimensional measurement.

[0058] Furthermore, in the optical detection subsystem, the lens adopts an infrared short-wave 30x 420mm continuous zoom lens; the infrared fill light: adopts an infrared light with a wavelength of 850nm, which is invisible to the human eye to avoid affecting normal driving; the camera adopts a planar array camera with a quantum efficiency of up to 80% in the 850nm band;

[0059] The calculation formula for optical detection resolution d is:

[0060] d=D×ps / f

[0061] d——optical detection resolution, unit: mm / pixel;

[0062] D——Detection distance, unit: m;

[0063] ps——camera pixel size, unit um;

[0064] f——focal length of the lens, in mm.

[0065] like Figure 3 and Figure 4 As shown, the method includes:

[0066] Initial inspection, re-inspection and random inspection;

[0067] The steps of the initial inspection are specifically as follows:

[0068] Initial inspection begins; synchronize network time and start system self-inspection; determine whether the system has faults; if there are faults, send a repair message via SMS or WeChat; end initial inspection and wait for maintenance; if there are no faults, the robot body automatically walks a fixed distance and stops, and the zoom lens works in the large focal length mode; the electric pan-tilt head rotates to a fixed angle and stops, and fine image acquisition / storage is performed on the body; determine whether the current cross-section acquisition is completed. If not, the electric pan-tilt head rotates to a fixed angle and stops again, and fine image acquisition / storage is performed on the body; if completed, determine whether the track end point has been reached. If not, the robot body automatically walks a fixed distance and stops again, and the zoom lens works in the large focal length mode; if the track end point has been reached, the pictures / videos temporarily stored locally are uploaded to the cloud server; end initial inspection and wait for the next re-inspection;

[0069] The steps of the re-examination are specifically as follows:

[0070] Re-inspection starts; network time is synchronized and system self-inspection starts; determine whether the system has faults. If so, send a repair message via SMS or WeChat; end re-inspection and wait for maintenance; if there is no fault, the inspection device automatically moves to determine whether the inspection device has reached the historical defect location. If not, return to the automatic walking step of the inspection device; if it has reached the historical defect location, the zoom lens works in the large focal length mode, and fine pictures are collected / stored locally; determine whether all defects have been re-inspected. If not, return to the automatic walking step of the inspection device and execute in sequence; if the re-inspection is completed, upload the pictures / videos temporarily stored locally to the cloud server; end re-inspection and wait for the next re-inspection;

[0071] The random inspection is an inspection performed by the automatic inspection device according to a specified optical resolution or a specified historical disease location or a specified tunnel section.

[0072] Furthermore, it also includes: mileage detection and cumulative error elimination; the mileage detection adopts a high-resolution incremental photoelectric rotary encoder, and is calculated based on the photoelectric encoder resolution of 5000P / R and the outer diameter of the walking wheel of 50mm, then its pulse equivalent is: 50mm×3.14159 / 5000P=0.0314mm / P; a magnet is buried every 20m or 50m in the track to trigger the Hall detection switch in the robot body. Each time the Hall detection switch is triggered, the mileage is automatically reset and the pulse counting starts again.

[0073] In this specification, each embodiment is described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same or similar parts between the embodiments can be referred to each other. For the system disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part.

[0074] The principles and implementation methods of the present invention are described in this article using specific examples. The description of the above embodiments is only used to help understand the method and core idea of ​​the present invention. At the same time, for those skilled in the art, according to the idea of ​​the present invention, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting the present invention.

Claims

1. A highway tunnel concrete surface disease inspection system, characterized in that: include: Initial inspection module, re-inspection module and random inspection module.

2. The highway tunnel concrete surface disease inspection system according to claim 1 is characterized in that: The initial inspection module is used to control the automatic inspection system to automatically inspect from the starting point of the track to the end point of the track. During the inspection process, the electric zoom lens always works in the large focal length mode, and the entire tunnel surface is finely scanned, photographed and stored in a high-resolution mode.

3. The highway tunnel concrete surface disease inspection system according to claim 1 is characterized in that: The re-inspection module is used to automatically move to the tunnel disease location for high-resolution re-inspection based on the disease location information in the most recent initial inspection results in the system, and the re-inspection cycle can be set as needed.

4. The highway tunnel concrete surface disease inspection system according to claim 1 is characterized in that: The sampling inspection module is used to control the automatic inspection system to perform inspections according to a specified optical resolution or a specified historical disease location or a specified partial section of the tunnel.

5. The highway tunnel concrete surface disease inspection system according to claim 1 is characterized in that: A track is installed on each of the left and right tunnel walls, and a total of 2 sets of automatic inspection devices are used to achieve full coverage of the entire tunnel surface.

6. The highway tunnel concrete surface disease inspection system according to claim 1 is characterized in that: The system includes charging stations, wireless routers, tracks, automatic inspection devices and software systems.

7. The highway tunnel concrete surface disease inspection system according to claim 6 is characterized in that: The automatic inspection device includes: a robot body, a one-dimensional electric pan-tilt platform and an optical detection subsystem; the robot body is composed of a suspension mechanism, a track automatic dust cleaning mechanism, an automatic walking mechanism, an embedded industrial computer, a 4G / Wi-Fi module, a mileage detection and reset circuit, a wireless / contact charging management circuit, a power module and a lithium battery pack; The optical detection subsystem is composed of an electric zoom lens, an infrared fill light and an infrared surface array camera; The software system includes image acquisition and control software running on an embedded industrial computer, server software and front-end programs deployed on a cloud server; the server software is tunnel surface defect recognition and processing software, which takes AI visual algorithm as the core and integrates traditional visual algorithm as an auxiliary, combining AI algorithm and traditional algorithm to give full play to their respective advantages to meet the specific applications of defect detection and dimensional measurement.

8. The highway tunnel concrete surface disease inspection system according to claim 7 is characterized in that: In the optical detection subsystem, the lens adopts an infrared short-wave 30x 420mm continuous zoom lens; the infrared fill light adopts an infrared light with a wavelength of 850nm, which is invisible to the human eye and avoids affecting normal driving; the camera adopts a planar array camera with a quantum efficiency of up to 80% in the 850nm band; The calculation formula for optical detection resolution d is: d=D×ps / f d——optical detection resolution, unit: mm / pixel; D——Detection distance, unit: m; ps——camera pixel size, unit um; f——focal length of the lens, in mm.

9. An inspection method of a highway tunnel concrete surface disease inspection system according to any one of claims 1 to 8, characterized in that: Including initial inspection, re-inspection and random inspection; The steps of the initial inspection are specifically as follows: Initial inspection begins; network time is synchronized and system self-inspection begins; determine whether the system has faults; if there are faults, a repair message is sent via SMS or WeChat; initial inspection ends and maintenance is awaited; if there are no faults, the robot body automatically walks a fixed distance and stops, and the zoom lens works in large focal length mode; the electric pan-tilt head rotates to a fixed angle and stops, and the body is finely imaged / stored; determine whether the current cross-section acquisition is complete, and if not, the electric pan-tilt head rotates to a fixed angle and stops again, and the body is finely imaged / stored; If it is finished, it is determined whether it has reached the end of the track. If it has not reached the end of the track, the robot body will automatically walk a fixed distance and then stop, and the zoom lens will work in the large focal length mode; if it has reached the end of the track, the pictures / videos temporarily stored locally will be uploaded to the cloud server; the initial inspection is completed and the next re-inspection is awaited; The steps of the re-examination are specifically as follows: The re-inspection starts; the network time is synchronized and the system self-inspection starts; it is determined whether the system has a fault. If so, a repair message is sent via SMS or WeChat; the re-inspection ends and the system waits for maintenance; if there is no fault, the inspection device automatically moves to determine whether the inspection device has reached the historical defect location. If not, the system returns to the automatic movement step of the inspection device; If the historical defect location is reached, the zoom lens will work in the large focal length mode, and fine pictures will be collected / stored locally; determine whether all defects have been re-inspected. If not, return to the automatic walking step of the inspection device and execute in sequence; If the re-inspection is completed, the pictures / videos temporarily stored locally will be uploaded to the cloud server; the re-inspection ends and waits for the next re-inspection; The random inspection is an inspection performed by the automatic inspection device according to a specified optical resolution or a specified historical disease location or a specified partial section of the tunnel.

10. The inspection method according to claim 9, characterized in that: Also includes: Mileage detection and cumulative error elimination; the mileage detection adopts a high-resolution incremental photoelectric rotary encoder. The pulse equivalent is calculated based on the photoelectric encoder resolution of 5000P / R and the outer diameter of the walking wheel of 50mm. The pulse equivalent is: 50mm×3.14159 / 5000P=0.0314mm / P; a magnet is buried every 20m or 50m in the track to trigger the Hall detection switch in the robot body. Each time the Hall detection switch is triggered, the mileage is automatically reset and the pulse counting starts again.

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