CN117705800A - Mechanical arm vision bridge detection system based on guide rail sliding and control method thereof - Google Patents

Mechanical arm vision bridge detection system based on guide rail sliding and control method thereof Download PDF

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Publication number
CN117705800A
CN117705800A CN202311573734.4A CN202311573734A CN117705800A CN 117705800 A CN117705800 A CN 117705800A CN 202311573734 A CN202311573734 A CN 202311573734A CN 117705800 A CN117705800 A CN 117705800A
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sub
bridge
mechanical arm
guide rail
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贾布裕
陈兆喆
余晓琳
陈扬文
杨铮
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South China University of Technology SCUT
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T1/00—General purpose image data processing
    • G06T1/0014—Image feed-back for automatic industrial control, e.g. robot with camera
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/01—Arrangements or apparatus for facilitating the optical investigation
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/01—Arrangements or apparatus for facilitating the optical investigation
    • G01N2021/0106—General arrangement of respective parts
    • G01N2021/0112—Apparatus in one mechanical, optical or electronic block
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/84—Systems specially adapted for particular applications
    • G01N21/88—Investigating the presence of flaws or contamination
    • G01N21/8851—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges
    • G01N2021/8887—Scan or image signal processing specially adapted therefor, e.g. for scan signal adjustment, for detecting different kinds of defects, for compensating for structures, markings, edges based on image processing techniques

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Abstract

The invention relates to a mechanical arm vision bridge detection system based on guide rail sliding and a control method thereof, wherein the mechanical arm vision bridge detection system comprises a linear guide rail sub-module, a mechanical arm sub-module, an onboard computer sub-module and a high-speed camera sub-module; the high-speed camera sub-module shoots bridge disease images, the mechanical arm sub-module drives the high-speed camera sub-module to translate on a plane vertical to the longitudinal direction of the bridge, and the linear guide rail sub-module drives the mechanical arm sub-module and the airborne computer sub-module to translate along the longitudinal direction of the bridge; the linear guide rail sub-module is additionally arranged on the bridge structure and is cut into a region outside the driving region; the airborne computer sub-module comprises a guide rail displacement control system, a mechanical arm rotation control system, a bridge disease image recognition system and a network transmission system. The invention has no influence on traffic in the later detection, has good universality and belongs to the technical field of bridge disease detection.

Description

Mechanical arm vision bridge detection system based on guide rail sliding and control method thereof
Technical Field
The invention relates to a bridge defect detection technology, in particular to a mechanical arm vision bridge detection system based on guide rail sliding and a control method thereof.
Background
The bridge structure is coupled by multiple factors such as aging of concrete materials, serious overload of vehicles, bad operation environment and the like, and in-service bridges can inevitably generate diseases such as cracking, peeling of protective layers, water seepage and flashing, exposed rib corrosion and the like, so that the safety and the durability of the bridge are extremely tested. Therefore, it is necessary to discover defects in bridge structures as early as possible to prevent further reduction in structural load-carrying capacity and durability. The apparent structural diseases are the most obvious signs, which indicate that the structure is possibly degraded or damaged, and are also key evaluation indexes in numerous bridge technical condition evaluation manuals such as highway bridge technical condition evaluation standards (JTG/TH 21-2011), highway bridge and culvert maintenance standards (JTG/H11-2004), urban bridge detection and evaluation technical standards (CJJ/T233-2015) and the like.
CN 116147505A discloses an intelligent detection terminal for bridge defect detection, which comprises a bridge detection platform, a mechanical arm, a crack recognition system and a crack detection system, wherein the crack recognition system is arranged on the mechanical arm, and then the mechanical arm is arranged on a carrying vehicle, and the detection of the back of the bridge is realized through the movement of the carrying vehicle. The technology has the following defects that the carrying vehicle drives the mechanical arm to translate along the length direction of the bridge: 1. the bridge deck lane is occupied during detection, and traffic is affected; 2. the carrying vehicle is difficult to ensure straight line running, and if the carrying vehicle deflects in the left-right direction, the alignment of the crack recognition system is influenced; 3. the carrying vehicle has left and right direction deflection in the running process and is influenced by the road surface, so that the carrying vehicle is not easy to realize automatic control and accurate alignment, and the bridge detection efficiency and the bridge detection effect are influenced.
Disclosure of Invention
Aiming at the technical problems existing in the prior art, the invention aims at: the mechanical arm vision bridge detection system based on the guide rail sliding, which does not influence traffic in the detection process, is provided.
Another object of the invention is: the control method of the mechanical arm vision bridge detection system based on the guide rail sliding, which can realize intelligent control and accurate detection, is provided.
In order to achieve the above purpose, the invention adopts the following technical scheme:
a mechanical arm vision bridge detection system based on guide rail sliding comprises a linear guide rail sub-module, a mechanical arm sub-module, an onboard computer sub-module and a high-speed camera sub-module; the high-speed camera sub-module shoots bridge disease images, the mechanical arm sub-module drives the high-speed camera sub-module to translate on a plane vertical to the longitudinal direction of the bridge, and the linear guide rail sub-module drives the mechanical arm sub-module and the airborne computer sub-module to translate along the longitudinal direction of the bridge; the linear guide rail sub-module is additionally arranged on the bridge structure and is cut into a region outside the driving region; the airborne computer sub-module comprises a guide rail displacement control system, a mechanical arm rotation control system, a bridge disease image recognition system and a network transmission system; the guide rail displacement control system controls the linear guide rail sub-module so as to control the longitudinal position of the mechanical arm sub-module; the mechanical arm rotation control system controls the mechanical arm submodule to act so as to control the target position and shooting angle of the high-speed camera submodule; the bridge defect image recognition system recognizes the shot bridge defect image; the network transmission system transmits the result of the identification to the terminal.
Preferably, the linear guide rail submodule comprises a servo motor, a guide rail sliding block mechanism, an encoder, a gear rack mechanism and a position feedback loop; in the guide rail sliding block mechanism, a guide rail is longitudinally paved along a bridge, and a sliding block bears a mechanical arm sub-module and an airborne computer sub-module; in the gear and rack mechanism, racks are arranged parallel to the guide rails, and a servo motor drives gears to rotate; the servo motor drives the sliding block to translate along the guide rail through the gear rack mechanism; the encoder detects the position of the slide and transmits the position information to the guide rail displacement control system through a position feedback loop.
Preferably, the sliding block is provided with a sliding block base for installing the mechanical arm sub-module and the airborne computer sub-module.
Preferably, the guide rail is laid outside the deck rail, on the side of the bridge or at the bottom of the bridge.
Preferably, the mechanical arm submodule is a six-degree-of-freedom mechanical arm, and a carrying device is arranged at the tail end of the mechanical arm and used for installing the high-speed camera submodule; the mechanical arm rotation control system controls the rotation angle of the mechanical arm, and the high-speed camera sub-module carried at the tail end of the mechanical arm is moved to the bottom of the bridge.
Preferably, the high speed camera sub-module comprises a high speed camera and illumination system; the high-speed camera is used for shooting bridge disease images, and the lighting system is used for improving the quality of picture shooting, so that the picture identification accuracy is improved.
Preferably, in the on-board computer sub-module, through presetting the working route, the guide rail displacement control system and the mechanical arm rotation control system automatically calculate the optimal working route and the pause time for image recognition by the high-speed camera sub-module, the bridge disease image recognition system receives the picture transmitted by the high-speed camera sub-module, performs recognition of the bridge disease by using a deep learning algorithm, and transmits the recognition to the terminal through the network transmission system.
Preferably, the algorithm for identifying the bridge diseases is selected according to different tasks.
Preferably, the mechanical arm vision bridge detection system based on guide rail sliding is detachably mounted on a bridge structure.
A control method of a mechanical arm vision bridge detection system based on guide rail sliding comprises the following steps:
the method comprises the steps that firstly, a working route for bridge detection is preset at a terminal, the working route is transmitted to an onboard computer sub-module through a network transmission system, and the onboard computer sub-module automatically calculates an optimal working route and shooting pause time through a guide rail displacement control system and a mechanical arm rotation control system by utilizing the predefined working route; controlling the linear guide rail sub-module to carry the mechanical arm sub-module and the high-speed camera sub-module to move to a target position by the onboard computer sub-module, and then controlling the mechanical arm sub-module to adjust the rotation angle so that the high-speed camera sub-module is positioned at a position for clearly shooting the bottom of the bridge; step three, the high-speed camera sub-module transmits the shot bridge disease pictures to the airborne computer sub-module, and the airborne computer sub-module carries out image recognition through the bridge disease image recognition system; and step four, the airborne computer sub-module transmits the identification result to the terminal through the network transmission system.
The invention has the following advantages:
1. the system is arranged in an area outside the driving area, does not need to carry out detection by whole-process road sealing, only carries out short-term enclosing construction when the linear guide rail sub-module is installed, has small influence on traffic, has no influence on traffic by later detection, and can carry out detection uninterruptedly.
2. The system of the invention does not need to be permanently and fixedly connected with the structure, can be disassembled and easily deployed on different detection structures, and has strong structure applicability and good universality.
3. The system of the invention does not need manual field operation, and has low cost and high safety.
4. The system provided by the invention is based on image recognition of a deep learning algorithm, and has the advantages of high recognition precision and good robustness.
5. The system disclosed by the invention has the advantages that all the submodules work cooperatively, the longitudinal bridge positions of the mechanical arm submodule and the high-speed camera submodule are adjusted based on the parameters of all the submodules calculated by the onboard computer, and the rotation angle of the mechanical arm submodule is adjusted to adapt to the shooting position of the high-speed camera submodule, so that the system can adapt to bridge detection requirements of different bridges; the system has the characteristics of easy installation and disassembly, good structural integration, high device utilization rate, high control efficiency and wide application range.
6. The system of the invention can be added to various bridges without changing bridge structures, and has strong universality.
Drawings
Fig. 1 is a perspective view of a robotic arm sub-module.
Fig. 2 is a perspective view of a linear guide sub-module.
FIG. 3 is a schematic diagram of an example application of the system of the present invention.
Fig. 4 is a control flow diagram of the system of the present invention.
In the figure, a 1-guide rail, a 2-sliding block, a 3-mechanical arm, a 4-high-speed camera and a 5-bridge are arranged.
Detailed Description
The present invention will be described in further detail with reference to the following embodiments.
A mechanical arm vision bridge detection system based on guide rail sliding comprises a linear guide rail sub-module, a mechanical arm sub-module, an onboard computer sub-module and a high-speed camera sub-module; the high-speed camera sub-module shoots bridge disease images, the mechanical arm sub-module drives the high-speed camera sub-module to translate on a plane vertical to the longitudinal direction of the bridge, and the linear guide rail sub-module drives the mechanical arm sub-module and the airborne computer sub-module to translate along the longitudinal direction of the bridge; the linear guide rail sub-module is additionally arranged on the bridge structure and is cut into a region outside the driving region; the airborne computer sub-module comprises a guide rail displacement control system, a mechanical arm rotation control system, a bridge disease image recognition system and a network transmission system; the guide rail displacement control system controls the linear guide rail sub-module so as to control the longitudinal position of the mechanical arm sub-module; the mechanical arm rotation control system controls the mechanical arm submodule to act so as to control the target position and shooting angle of the high-speed camera submodule; the bridge defect image recognition system recognizes the shot bridge defect image; the network transmission system transmits the result of the identification to the terminal.
The linear guide rail submodule comprises a servo motor, a guide rail sliding block mechanism, an encoder, a gear rack mechanism and a position feedback loop, and has certain additional load capacity. In the guide rail sliding block mechanism, a guide rail is longitudinally paved along a bridge, and a sliding block bears a mechanical arm sub-module and an airborne computer sub-module; in the gear and rack mechanism, racks are arranged parallel to the guide rails, and a servo motor drives gears to rotate; the servo motor drives the sliding block to translate along the guide rail through the gear rack mechanism; the encoder detects the position of the slide and transmits the position information to the guide rail displacement control system through a position feedback loop.
The sliding block is provided with a sliding block base for installing the mechanical arm sub-module and the airborne computer sub-module. The slider base has a storage compartment therein for housing an onboard computer sub-module.
The guide rail is paved outside the bridge deck fence, on the side surface of the bridge or at the bottom of the bridge. In this embodiment, the guide rail is laid on the outer edge of the bridge.
The mechanical arm sub-module is a six-degree-of-freedom mechanical arm, and a carrying device is arranged at the tail end of the mechanical arm and used for mounting the high-speed camera sub-module; the mechanical arm rotation control system controls the rotation angle of the mechanical arm, and the high-speed camera sub-module carried at the tail end of the mechanical arm is moved to the bottom of the bridge.
The high-speed camera sub-module comprises a high-speed camera and an illumination system; the high-speed camera is used for shooting bridge disease images, and the lighting system is used for improving the quality of picture shooting, so that the picture identification accuracy is improved.
In the on-board computer sub-module, through presetting the working route, the guide rail displacement control system and the mechanical arm rotation control system automatically calculate the optimal working route and the pause time for the high-speed camera sub-module to perform image recognition, the bridge disease image recognition system receives the pictures transmitted by the high-speed camera sub-module, performs recognition of bridge disease by using a deep learning algorithm, and transmits the bridge disease to the terminal through the network transmission system.
The algorithm for identifying the bridge diseases is selected according to different tasks. For example, the YOLOv8 algorithm can be selected for bridge crack identification.
A mechanical arm vision bridge detection system based on guide rail sliding is detachably mounted on a bridge structure, can be additionally mounted on the existing bridge structure when needed, and is easy to detach when not needed.
A control method of a mechanical arm vision bridge detection system based on guide rail sliding comprises the following steps:
the method comprises the steps that firstly, a working route for bridge detection is preset at a terminal, wherein the working route comprises initial space position parameters of a mechanical arm sub-module and a high-speed camera sub-module, space position parameters of protruding obstacles along a linear guide rail sub-module, interval distance parameters of bridge disease shooting points and shooting time parameters, and the parameters are transmitted to an airborne computer sub-module through a network transmission system; the airborne computer sub-module automatically calculates the optimal working path and shooting pause time by utilizing a predefined working path through a guide rail displacement control system and a mechanical arm rotation control system;
after the linear guide rail submodule receives the space position updating instruction, the onboard computer submodule controls the linear guide rail submodule to carry the mechanical arm submodule and the high-speed camera submodule to move to the target position, and after the mechanical arm submodule receives the rotating angle updating instruction, the mechanical arm submodule is controlled to adjust the rotating angle, so that the high-speed camera submodule is positioned at a position for clearly shooting the bottom of the bridge, and shooting of bridge diseases is carried out;
step three, the high-speed camera sub-module transmits the shot bridge disease pictures to the airborne computer sub-module, and the airborne computer sub-module carries out image recognition through the bridge disease image recognition system;
and step four, the airborne computer sub-module transmits the identification result to the terminal through the network transmission system.
And then the airborne computer continues the calculation of the spatial position parameters of each sub-module of the next point position until the whole bridge detection process is completed.
The above examples are preferred embodiments of the present invention, but the embodiments of the present invention are not limited to the above examples, and any other changes, modifications, substitutions, combinations, and simplifications that do not depart from the spirit and principle of the present invention should be made in the equivalent manner, and the embodiments are included in the protection scope of the present invention.

Claims (10)

1. Mechanical arm vision bridge detecting system based on guide rail sliding, its characterized in that: the system comprises a linear guide rail sub-module, a mechanical arm sub-module, an onboard computer sub-module and a high-speed camera sub-module; the high-speed camera sub-module shoots bridge disease images, the mechanical arm sub-module drives the high-speed camera sub-module to translate on a plane vertical to the longitudinal direction of the bridge, and the linear guide rail sub-module drives the mechanical arm sub-module and the airborne computer sub-module to translate along the longitudinal direction of the bridge;
the linear guide rail sub-module is additionally arranged on the bridge structure and is cut into a region outside the driving region;
the airborne computer sub-module comprises a guide rail displacement control system, a mechanical arm rotation control system, a bridge disease image recognition system and a network transmission system; the guide rail displacement control system controls the linear guide rail sub-module so as to control the longitudinal position of the mechanical arm sub-module; the mechanical arm rotation control system controls the mechanical arm submodule to act so as to control the target position and shooting angle of the high-speed camera submodule; the bridge defect image recognition system recognizes the shot bridge defect image; the network transmission system transmits the result of the identification to the terminal.
2. A rail slide based robotic vision bridge inspection system in accordance with claim 1, wherein: the linear guide rail submodule comprises a servo motor, a guide rail slide block mechanism, an encoder, a gear rack mechanism and a position feedback loop; in the guide rail sliding block mechanism, a guide rail is longitudinally paved along a bridge, and a sliding block bears a mechanical arm sub-module and an airborne computer sub-module; in the gear and rack mechanism, racks are arranged parallel to the guide rails, and a servo motor drives gears to rotate; the servo motor drives the sliding block to translate along the guide rail through the gear rack mechanism; the encoder detects the position of the slide and transmits the position information to the guide rail displacement control system through a position feedback loop.
3. A rail slide based robotic vision bridge inspection system in accordance with claim 2, wherein: the sliding block is provided with a sliding block base for installing the mechanical arm sub-module and the airborne computer sub-module.
4. A rail slide based robotic vision bridge inspection system in accordance with claim 2, wherein: the guide rail is paved outside the bridge deck fence, on the side surface of the bridge or at the bottom of the bridge.
5. A rail slide based robotic vision bridge inspection system in accordance with claim 1, wherein: the mechanical arm sub-module is a six-degree-of-freedom mechanical arm, and a carrying device is arranged at the tail end of the mechanical arm and used for mounting the high-speed camera sub-module; the mechanical arm rotation control system controls the rotation angle of the mechanical arm, and the high-speed camera sub-module carried at the tail end of the mechanical arm is moved to the bottom of the bridge.
6. A rail slide based robotic vision bridge inspection system in accordance with claim 1, wherein: the high-speed camera sub-module comprises a high-speed camera and an illumination system; the high-speed camera is used for shooting bridge disease images, and the lighting system is used for improving the quality of picture shooting, so that the picture identification accuracy is improved.
7. A rail slide based robotic vision bridge inspection system in accordance with claim 1, wherein: in the on-board computer sub-module, through presetting the working route, the guide rail displacement control system and the mechanical arm rotation control system automatically calculate the optimal working route and the pause time for the high-speed camera sub-module to perform image recognition, the bridge disease image recognition system receives the pictures transmitted by the high-speed camera sub-module, performs recognition of bridge disease by using a deep learning algorithm, and transmits the bridge disease to the terminal through the network transmission system.
8. A rail slide based robotic vision bridge inspection system as defined in claim 7, wherein: the algorithm for identifying the bridge diseases is selected according to different tasks.
9. A rail slide based robotic vision bridge inspection system in accordance with claim 1, wherein: and the detachable bridge is arranged on the bridge structure.
10. A control method of a rail sliding-based robot arm vision bridge inspection system according to any one of claims 1 to 9, comprising the steps of:
the method comprises the steps that firstly, a working route for bridge detection is preset at a terminal, the working route is transmitted to an onboard computer sub-module through a network transmission system, and the onboard computer sub-module automatically calculates an optimal working route and shooting pause time through a guide rail displacement control system and a mechanical arm rotation control system by utilizing the predefined working route;
controlling the linear guide rail sub-module to carry the mechanical arm sub-module and the high-speed camera sub-module to move to a target position by the onboard computer sub-module, and then controlling the mechanical arm sub-module to adjust the rotation angle so that the high-speed camera sub-module is positioned at a position for clearly shooting the bottom of the bridge;
step three, the high-speed camera sub-module transmits the shot bridge disease pictures to the airborne computer sub-module, and the airborne computer sub-module carries out image recognition through the bridge disease image recognition system;
and step four, the airborne computer sub-module transmits the identification result to the terminal through the network transmission system.
CN202311573734.4A 2023-11-23 2023-11-23 Mechanical arm vision bridge detection system based on guide rail sliding and control method thereof Pending CN117705800A (en)

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