A rail transit vehicle pole paint stripping laser cleaning system

Abstract

The present invention relates to the field of laser cleaning technology, and discloses a rail transit vehicle rod stripping laser cleaning system, which is equipped with a laser cleaning device. The laser cleaning device includes a laser and a robot drive mechanism for driving the laser to move. Through the coordinated work of a visual recognition module, a processing module, and a cleaning planning module, the system can intelligently adjust the cleaning parameters according to the specific conditions of the rod to achieve efficient and accurate paint stripping and cleaning. The use of laser cleaning technology avoids the use of chemical solvents and dust pollution generated by mechanical grinding, reducing harm to the environment. At the same time, by optimizing the cleaning parameters, the energy consumption of the laser is reduced, achieving the goal of environmental protection and energy saving. The cleaning database records a large amount of historical cleaning data. By analyzing and mining these data, the system can continuously optimize the cleaning parameters and strategies, improve the cleaning effect and efficiency, and the cleaning performance of the system will continue to improve as the usage time increases.

Description

Technical Field

[0001] The present invention relates to the technical field of laser cleaning, and in particular to a rail transit vehicle rod paint stripping laser cleaning system. Background Art

[0002] Laser cleaning removes material from solid surfaces by irradiating a laser beam. At low laser flux, the absorbed laser energy heats the material and vaporizes or sublimates it. At high laser flux, the material is typically converted into plasma. Laser cleaning, due to its high cleaning speed, low cost, and environmentally friendly characteristics, is widely used in surface cleaning and paint removal. The intelligent inspection and maintenance system for bogie rods primarily consists of modules for automated laser stripping of rods, automated press-fitting of rod joints, and robot-assisted handling. It uses a vision system to identify various rod joints and press-fitting fixtures. Laser paint stripping equipment replaces traditional paint stripping methods using paint strippers. The automated press-fitting module for rod joints enables automated disassembly and press-fitting of different rod joint models. The robot-assisted handling module uses a handling robot to transport rods between the paint stripping, flaw detection, and press-fitting stations.

[0003] During the paint stripping and cleaning process, the vision module captures the shape of the rod to be processed and invokes a pre-set paint stripping path, removing the paint layer from the rod surface according to preset laser parameters. However, in actual applications, the rod surface is affected by the operating environment and coating differences, and different rods require different laser parameters. If the laser power is too low, the coating may not be completely removed. If the laser power is too high, it may cause laser burns on the cleaned workpiece surface, affecting its reuse. Summary of the Invention

[0004] In view of the shortcomings of the prior art, the object of the present invention is to provide a rail transit vehicle rod paint stripping laser cleaning system for improving the laser cleaning efficiency and improving the cleaning effect.

[0005] To achieve the above objectives, the present invention provides the following technical solutions: a rail transit vehicle rod paint stripping laser cleaning system, equipped with a laser cleaning device, the laser cleaning device including a laser, a robot drive mechanism for driving the laser to move, and a fume treatment mechanism,

[0006] A laser cleaning device is provided, which includes a laser, a robot driving mechanism for driving the laser to move, and a fume treatment mechanism.

[0007] The rail transit vehicle rod paint stripping laser cleaning system includes

[0008] A visual recognition module, wherein the visual recognition module is used to identify the rod model;

[0009] An image acquisition module, the image acquisition module is used to acquire a cleaning image of the rod member to define as cleaning image information;

[0010] An information input module, wherein the information input module is used to input pole member information, wherein the pole member information includes a working vehicle and pole member parameters;

[0011] A cleaning database, wherein the cleaning database records the pole model, working vehicle, quantity and historical cleaning data corresponding to each working vehicle;

[0012] A processing module, wherein the processing module calls corresponding historical cleaning data based on the rod model and rod information, and generates cleaning parameters to the laser according to the parameter pre-adjustment strategy to perform preliminary cleaning on the rod;

[0013] A cleaning planning module, after the initial cleaning is completed, regenerates the cleaning execution parameters according to the cleaning degree of the rod to control the laser cleaning device to repeatedly clean until the surface cleanliness of the rod meets the preset cleaning requirements, and records the number of cleanings, cleaning parameters and the surface cleanliness of the rod as historical cleaning data in the cleaning database.

[0014] Furthermore, the parameter pre-adjustment strategy includes

[0015] ,

[0016] ,

[0017] ,

[0018] Where T represents the time span from the last cleaning to the present. represents the preset member foundation power, represents the rod aging correction power, Indicates the duration of the inflection point of the aging rate, They represent the growth coefficient, E represents the environmental corrosion coefficient, V represents the laser's execution scanning speed, and F represents the laser's execution pulse frequency. Indicates the basic scanning speed of the laser, represents the basic pulse frequency of the laser, Indicates the enhancement factor from the last cleaning to the current time span.

[0019] Furthermore, the cleaning planning module is configured with a cleanliness judgment strategy, which includes

[0020] The image acquisition module obtains the surface image of the rod after preliminary cleaning to define it as preliminary cleaning image information, obtains the cleaned surface of the rod in the preliminary cleaning image information to define it as the cleaning area, divides the cleaning area into several cleaning sub-areas, calculates the RGB color value of each cleaning sub-area to define it as the regional color value, compares the regional color value with the preset reference color value, and generates an uncleaned signal if the difference is greater than the preset difference threshold, and executes the preset repeated cleaning strategy.

[0021] Furthermore, the repeated cleaning strategy includes obtaining a cleaning sub-area corresponding to a difference greater than a preset difference threshold and defining it as an area to be cleaned, re-planning several pending cleaning paths based on the position of the area to be cleaned, selecting the shortest pending cleaning path as the re-cleaning path to the robot drive mechanism, and repeatedly cleaning until the difference between the color value of each cleaning sub-area and the preset reference color value meets the preset difference threshold.

[0022] Furthermore, the cleaning planning module is configured with an over-cleaning adjustment strategy, including

[0023] If multiple cleaning sub-areas are still defined as areas to be cleaned after continuous cleaning, they are defined as abnormal areas, and the abnormal color value changes of each abnormal area in each cleaning are determined.

[0024] If the color value of each abnormal area gradually increases with the increase in the number of cleaning times, it is determined to be over-cleaned and the cleaning pulse speed of the abnormal area is increased.

[0025] Furthermore, the cleaning planning module is configured with an environmental factor calculation strategy, which includes

[0026] Obtaining the use environment parameters, ambient temperature parameters, and ambient humidity parameters of the rod, wherein the use environment parameters are used to represent the use environment of the rod, including full tunnel use, partial elevated use, and full elevated use.

[0027] The size of the environmental corrosion coefficient is adjusted according to the use environment parameters, the ambient temperature parameters and the ambient humidity parameters. The formula of the environmental factor calculation strategy is specifically as follows:

[0028] ,

[0029] in Indicates basic environment parameter items, Indicates the ambient temperature parameter item, Represents the ambient humidity parameter item.

[0030] Furthermore, the cleaning planning module is configured with a basic frequency correction strategy, including

[0031] Obtain historical cleaning data for the same model of rod, including the number of cleanings, cleaning parameters, and rod surface cleanliness. If the overlap of the areas to be cleaned during multiple cleanings is greater than the preset cleaning overlap threshold, increase the basic pulse frequency of the corresponding cleaning sub-area.

[0032] Furthermore, the cleaning planning module is configured with a basic speed correction strategy, including

[0033] Obtain historical cleaning data for the same model of rod, including the number of cleanings, cleaning parameters, and rod surface cleanliness. If the overlap of abnormal areas during multiple cleanings is greater than a preset abnormal overlap threshold, increase the basic scanning speed of the corresponding cleaning sub-area.

[0034] Beneficial effects of the present invention:

[0035] Through the collaborative work of the visual recognition module, processing module, and cleaning planning module, the system can intelligently adjust the cleaning parameters according to the specific conditions of the rod, achieving efficient and accurate paint stripping and cleaning. The use of laser cleaning technology avoids the use of chemical solvents and dust pollution generated by mechanical grinding, reducing harm to the environment. At the same time, by optimizing the cleaning parameters, the energy consumption of the laser is reduced, achieving the goal of environmental protection and energy saving. The cleaning database records a large amount of historical cleaning data. Through the analysis and mining of this data, the system can continuously optimize the cleaning parameters and strategies to improve the cleaning effect and efficiency. As the use time increases, the cleaning performance of the system will continue to improve. The over-cleaning adjustment strategy and the basic frequency and speed correction strategy can avoid excessive cleaning and damage to the rod surface, protect the original material and performance of the rod, and extend the service life of the rod. The environmental factor calculation strategy fully considers the influence of the rod's use environment and environmental parameters on the cleaning effect, enabling the system to maintain good cleaning performance under different environmental conditions. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 The present invention is a schematic diagram of the system architecture of a rail transit vehicle pole paint stripping laser cleaning system. DETAILED DESCRIPTION

[0037] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0038] It should be noted that when a component is referred to as being "fixed to" another component, it may be directly on the other component or there may be a central component. When a component is considered to be "connected to" another component, it may be directly connected to the other component or there may be a central component. When a component is considered to be "disposed on" another component, it may be directly disposed on the other component or there may be a central component. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only.

[0039] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one skilled in the art to which this invention pertains. The terms used in this specification of the present invention are for the purpose of describing specific embodiments only and are not intended to limit the present invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0040] like Figure 1 As shown, in this embodiment, a complete set of maintenance and cleaning solutions are configured for the rods. The intelligent maintenance system for bogie rods mainly consists of main process modules such as automatic laser stripping of rods, automatic press-fitting of rod joints, and robot-assisted handling. Various rod joints and press-fitting positioning fixtures can be identified by a visual system. The use of laser stripping equipment replaces the traditional paint stripping method using paint strippers. The automatic press-fitting module for rod joints can realize the automatic disassembly and press-fitting operations of rod joints of different models. The robot-assisted handling module uses a handling robot to realize the handling of rods between the paint stripping station, the flaw detection station, and the press-fitting station. The intelligent maintenance system for bogie rods adopts a mechatronic design and realizes a human-machine collaborative operation mode through protective measures such as safety gratings, making rod maintenance operations more orderly and efficient. This application mainly improves paint stripping and cleaning. A rail transit vehicle rod stripping laser cleaning system in this embodiment is equipped with a laser cleaning device, which includes a laser, a robot drive mechanism for driving the laser movement, and a flue gas treatment mechanism.

[0041] The rail transit vehicle rod paint stripping laser cleaning system includes

[0042] A visual recognition module, wherein the visual recognition module is used to identify the rod model;

[0043] An image acquisition module, the image acquisition module is used to acquire a cleaning image of the rod member to define as cleaning image information;

[0044] An information input module, wherein the information input module is used to input pole member information, wherein the pole member information includes a working vehicle and pole member parameters;

[0045] A cleaning database, wherein the cleaning database records the pole model, working vehicle, quantity and historical cleaning data corresponding to each working vehicle;

[0046] A processing module, wherein the processing module calls corresponding historical cleaning data based on the rod model and rod information, and generates cleaning parameters to the laser according to the parameter pre-adjustment strategy to perform preliminary cleaning on the rod;

[0047] A cleaning planning module, after the initial cleaning is completed, regenerates the cleaning execution parameters according to the cleaning degree of the rod to control the laser cleaning device to repeatedly clean until the surface cleanliness of the rod meets the preset cleaning requirements, and records the number of cleanings, cleaning parameters and the surface cleanliness of the rod as historical cleaning data in the cleaning database.

[0048] Through the collaborative work of the visual recognition module and the image acquisition module, the system can automatically identify the rod model and establish a digital cleaning file; the historical data accumulation of the cleaning database realizes the intelligent iterative optimization of cleaning parameters; the hierarchical control strategy of the processing module and the cleaning planning module enables the system to have autonomous decision-making capabilities, which can improve the cleaning efficiency by 30%-50% compared with traditional manual cleaning, while ensuring the cleanliness consistency of more than 98%.

[0049] Furthermore, the parameter pre-adjustment strategy includes

[0050] ,

[0051] ,

[0052] ,

[0053] Where T represents the time span from the last cleaning to the present. represents the preset member foundation power, represents the rod aging correction power, Indicates the duration of the inflection point of the aging rate, They represent the growth coefficient, E represents the environmental corrosion coefficient, V represents the laser's execution scanning speed, and F represents the laser's execution pulse frequency. Indicates the basic scanning speed of the laser, represents the basic pulse frequency of the laser, Indicates the enhancement factor from the last cleaning to the current time span.

[0054] The parameter adjustment strategy primarily considers the correlation between surface paint and rust conditions for rods of the same operating environment and model. The parameter adjustment strategy considers the effect of the time span from the last cleaning to the current cleaning on the paint layer and sets the aging rate inflection point duration. This is because, for example, if the aging rate inflection point duration is set to 12 months, the impact of the environment from 0-12 months on the paint layer may be different from that of more than 12 months. and This can be obtained through experiments. For example, for rod samples with different time intervals such as 6 / 12 / 24 months, the paint thickness, adhesion and hardness are measured, and the best value is determined through orthogonal experiments. and .

[0055] Furthermore, the cleaning planning module is configured with a cleanliness judgment strategy, which includes

[0056] The image acquisition module obtains the surface image of the rod after preliminary cleaning to define it as preliminary cleaning image information, obtains the cleaned surface of the rod in the preliminary cleaning image information to define it as the cleaning area, divides the cleaning area into several cleaning sub-areas, calculates the RGB color value of each cleaning sub-area to define it as the regional color value, compares the regional color value with the preset reference color value, and generates an uncleaned signal if the difference is greater than the preset difference threshold, and executes the preset repeated cleaning strategy.

[0057] Furthermore, the repeated cleaning strategy includes obtaining a cleaning sub-area corresponding to a difference greater than a preset difference threshold and defining it as an area to be cleaned, re-planning several pending cleaning paths based on the position of the area to be cleaned, selecting the shortest pending cleaning path as the re-cleaning path to the robot drive mechanism, and repeatedly cleaning until the difference between the color value of each cleaning sub-area and the preset reference color value meets the preset difference threshold.

[0058] Furthermore, the cleaning planning module is configured with an over-cleaning adjustment strategy, including

[0059] If multiple cleaning sub-areas are still defined as areas to be cleaned after continuous cleaning, they are defined as abnormal areas, and the abnormal color value changes of each abnormal area in each cleaning are determined.

[0060] If the color value of each abnormal area gradually increases with the increase in the number of cleaning times, it is determined to be over-cleaned and the cleaning pulse speed of the abnormal area is increased.

[0061] Furthermore, the cleaning planning module is configured with an environmental factor calculation strategy, which includes

[0062] Obtaining the use environment parameters, ambient temperature parameters, and ambient humidity parameters of the rod, wherein the use environment parameters are used to represent the use environment of the rod, including full tunnel use, partial elevated use, and full elevated use.

[0063] The size of the environmental corrosion coefficient is adjusted according to the use environment parameters, the ambient temperature parameters and the ambient humidity parameters. The formula of the environmental factor calculation strategy is specifically as follows:

[0064] ,

[0065] in Indicates basic environment parameter items, Indicates the ambient temperature parameter item, Represents the ambient humidity parameter item.

[0066] Furthermore, the cleaning planning module is configured with a basic frequency correction strategy, including

[0067] Obtain historical cleaning data for the same model of rod, including the number of cleanings, cleaning parameters, and rod surface cleanliness. If the overlap of the areas to be cleaned during multiple cleanings is greater than the preset cleaning overlap threshold, increase the basic pulse frequency of the corresponding cleaning sub-area.

[0068] Furthermore, the cleaning planning module is configured with a basic speed correction strategy, including

[0069] Obtain historical cleaning data for the same model of rod, including the number of cleanings, cleaning parameters, and rod surface cleanliness. If the overlap of abnormal areas during multiple cleanings is greater than a preset abnormal overlap threshold, increase the basic scanning speed of the corresponding cleaning sub-area.

[0070] The above are merely preferred embodiments of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions based on the principles of the present invention are within the scope of protection of the present invention. It should be noted that improvements and modifications that do not depart from the principles of the present invention are within the scope of protection of the present invention.

Claims

1. A rail transit vehicle rod paint stripping laser cleaning system, characterized by: A laser cleaning device is provided, which includes a laser, a robot driving mechanism for driving the laser to move, and a fume treatment mechanism. The rail transit vehicle rod paint stripping laser cleaning system includes A visual recognition module, wherein the visual recognition module is used to identify the rod model; An image acquisition module, the image acquisition module is used to acquire a cleaning image of the rod member to define as cleaning image information; An information input module, wherein the information input module is used to input pole member information, wherein the pole member information includes a working vehicle and pole member parameters; A cleaning database, wherein the cleaning database records the pole model, working vehicle, quantity and historical cleaning data corresponding to each working vehicle; A processing module, wherein the processing module calls corresponding historical cleaning data based on the rod model and rod information, and generates cleaning parameters to the laser according to the parameter pre-adjustment strategy to perform preliminary cleaning on the rod; a cleaning planning module, which regenerates cleaning execution parameters based on the degree of rod cleaning after the initial cleaning is completed to control the laser cleaning device to repeatedly clean the rod until the rod surface cleanliness meets the preset cleaning requirements, and records the number of cleanings, cleaning parameters, and rod surface cleanliness as historical cleaning data in the cleaning database; The parameter pre-adjustment strategy includes ， ， ， Where T represents the time span from the last cleaning to the present. represents the preset member foundation power, represents the rod aging correction power, Indicates the duration of the inflection point of the aging rate, They represent the growth coefficient, E represents the environmental corrosion coefficient, V represents the laser's execution scanning speed, and F represents the laser's execution pulse frequency. Indicates the basic scanning speed of the laser, represents the basic pulse frequency of the laser, Indicates the enhancement factor from the last cleaning to the current time span.

2. The rail transit vehicle rod paint stripping laser cleaning system according to claim 1 is characterized in that: The cleaning planning module is configured with a cleaning degree judgment strategy, and the cleaning degree judgment strategy includes The image acquisition module obtains the surface image of the rod after preliminary cleaning to define it as preliminary cleaning image information, obtains the cleaned surface of the rod in the preliminary cleaning image information to define it as the cleaning area, divides the cleaning area into several cleaning sub-areas, calculates the RGB color value of each cleaning sub-area to define it as the regional color value, compares the regional color value with the preset reference color value, and generates an uncleaned signal if the difference is greater than the preset difference threshold, and executes the preset repeated cleaning strategy.

3. The rail transit vehicle rod paint stripping laser cleaning system according to claim 2, characterized in that: The repeated cleaning strategy includes obtaining a cleaning sub-area corresponding to a difference greater than a preset difference threshold and defining it as an area to be cleaned, replanning several pending cleaning paths based on the position of the area to be cleaned, selecting the shortest pending cleaning path as the re-cleaning path to the robot drive mechanism, and repeatedly cleaning until the difference between the color value of each cleaning sub-area and the preset reference color value meets the preset difference threshold.

4. The rail transit vehicle rod paint stripping laser cleaning system according to claim 3 is characterized in that: The cleaning planning module is configured with an over-cleaning adjustment strategy, including If multiple cleaning sub-areas are still defined as areas to be cleaned after continuous cleaning, they are defined as abnormal areas. The abnormal color value changes of each abnormal area in each cleaning are determined. If the color value of each abnormal area gradually increases with the increase in the number of cleaning times, it is determined to be over-cleaned and the cleaning pulse speed of the abnormal area is increased.

5. The rail transit vehicle rod paint stripping laser cleaning system according to claim 3 is characterized by: The cleaning planning module is configured with an environmental factor calculation strategy, which includes Obtaining the use environment parameters, ambient temperature parameters, and ambient humidity parameters of the rod, wherein the use environment parameters are used to represent the use environment of the rod, including full tunnel use, partial elevated use, and full elevated use. The size of the environmental corrosion coefficient is adjusted according to the use environment parameters, the ambient temperature parameters and the ambient humidity parameters. The formula of the environmental factor calculation strategy is specifically as follows: ， in Indicates basic environment parameter items, Indicates the ambient temperature parameter item, Indicates the ambient humidity parameter item.

6. The rail transit vehicle rod paint stripping laser cleaning system according to claim 3, characterized in that: The cleaning planning module is configured with a basic frequency correction strategy, including Obtain historical cleaning data for the same model of rod, including the number of cleanings, cleaning parameters, and rod surface cleanliness. If the overlap of the areas to be cleaned during multiple cleanings is greater than the preset cleaning overlap threshold, increase the basic pulse frequency of the corresponding cleaning sub-area.

7. The rail transit vehicle rod paint stripping laser cleaning system according to claim 4, characterized in that: The cleaning planning module is configured with a basic speed correction strategy, including Obtain historical cleaning data for the same model of rod, including the number of cleanings, cleaning parameters, and rod surface cleanliness. If the overlap of abnormal areas during multiple cleanings is greater than a preset abnormal overlap threshold, increase the basic scanning speed of the corresponding cleaning sub-area.

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