Recognition system for laser engraving of vehicle codes through mechanical arm

Abstract

The invention discloses an identification system for a vehicle code engraved by mechanical arm laser, and relates to the technical field of vehicle code identification, the identification system comprises a code identification module, an anti-bending strength interpretation module and a material improvement module, the code identification module is used for collecting internal structure data of an etched material by using an image scanning technology; the anti-bending strength interpretation module is used for processing the image data to judge the quality of an etched area, and the material improvement module is used for adjusting the content of rare earth elements of the material. The code identification module comprises an ultrasonic transmitting unit, an ultrasonic receiving unit, a dead pixel identification module, a structure fitting module, a data acquisition module, a material display module and an etching area identification module, the ultrasonic transmitting unit is used for penetrating an etching material through ultrasonic waves, and the ultrasonic receiving unit is electrically connected with the dead pixel identification module. The method has the characteristic of real-time variation.

Description

Technical Field

[0001] The invention relates to the technical field of vehicle code recognition, and in particular to a vehicle code recognition system using a robotic arm laser to engrave a vehicle code. Background Art

[0002] Robotic arm laser engraving technology uses a high-precision robotic arm to guide the laser beam and automatically complete the permanent marking of the vehicle code at the specified position of the vehicle. The mark is called a laser etched code. This technology has the advantages of high automation, high engraving accuracy, high efficiency, and long-lasting marking. It can be widely used in scenes such as automobiles, parts, and frames to achieve traceability and anti-counterfeiting of vehicle information and improve vehicle production and management efficiency.

[0003] When laser etching is performed on a car, there are defects such as bad spots and impurities inside the etched material, which may cause abnormal melting or vaporization in the local area during the laser etching process, forming bad spots. The existing technology can refine the grains and reduce the inclusions inside the material by adding trace amounts of rare earth elements, but too much rare earth elements will change the melting point and fluidity of the material, resulting in lower material strength, increased costs, and difficulty in control. Therefore, it is necessary to design a recognition system for a robotic arm laser engraved vehicle code that changes in real time. Summary of the invention

[0004] The purpose of the present invention is to provide a vehicle code recognition system for laser engraving by a robotic arm to solve the problems raised in the above background technology.

[0005] In order to solve the above technical problems, the present invention provides the following technical solutions: a robotic arm laser engraved vehicle code recognition system, comprising a code recognition module, a bending strength interpretation module, and a material improvement module. The code recognition module is used to collect internal structure data of the etched material using image scanning technology, the bending strength interpretation module is used to process image data to determine the quality of the etching area, and the material improvement module is used to adjust the rare earth element content of the material.

[0006] According to the above technical solution, the code recognition module includes an ultrasonic transmitting unit, an ultrasonic receiving unit, a bad point recognition module, a structure fitting module, a data acquisition module, a material display module, and an etching area recognition module. The ultrasonic transmitting unit is used to penetrate the etching material with ultrasonic waves, the ultrasonic receiving unit is electrically connected to the bad point recognition module, the material display module is electrically connected to the structure fitting module, and the etching area recognition module is electrically connected to the structure fitting module; the ultrasonic receiving unit is used to detect the reflection and scattering of ultrasonic waves and obtain the image information inside the material, the bad point recognition module is used to determine whether there are bad points in the material by the attenuation degree of ultrasonic waves, the data acquisition module is used to input the material composition by means of data acquisition, the material display module is used to display the acquired material composition, the structure fitting module is used to obtain a material composition model based on the acquired material composition and the overall material composition ratio, and the etching area recognition module is used to identify the etching area on the material structure;

[0007] The bending strength interpretation module includes a bad point counting module, a bending strength analysis module, a material composition storage library, and an etching judgment module. The bad point counting module is electrically connected to the bad point identification module, the material composition storage library is electrically connected to the material display module, the bending strength analysis module is electrically connected to the material composition storage library, and the etching judgment module is electrically connected to both the bad point counting module and the bending strength analysis module; the bad point counting module is used to count the number of bad points judged to exist in the etching code, the bending strength analysis module is used to analyze the bending strength of the etching area near the material, the material composition storage library is used to store standard material composition models for analysis and comparison with actual usage, and the etching judgment module is used to comprehensively analyze the etching quality of the image code based on the number of bad points in the etching code and the bending strength of the etching area;

[0008] The material improvement module includes a composition adjustment calculation module, a composition modification module, and a practical verification module. The composition adjustment calculation module is used to re-improve the rare earth content suitable for this material, the composition modification module is used to modify the material parameters on the material composition model of the material, and the practical verification module is used to determine whether the improved material can be etched and used normally.

[0009] According to the above technical solution, the working method of the system includes:

[0010] S1. After the etching of the material is completed, the material composition is acquired by using the data acquisition module to obtain a standard material composition model;

[0011] S2. After the material is put into use, the material is scanned by using an ultrasonic transmitting unit, the number of bad code points in the material area is counted, and the material is acquired again by using a data acquisition module to obtain the overall composition ratio of the material after use;

[0012] S3, comprehensively judging the quality of the etching area according to the number of bad spots and the bending strength of the etching area;

[0013] S4. Improve the rare earth content of the material and apply the improved parameters to the material composition model to confirm that the improved material can be etched and used normally.

[0014] According to the above technical solution, in S3, the specific method for identifying the bending strength of the etching area is:

[0015] S3-1, bend the scanned standard material composition model along the material area until the bent material composition model reaches a level that cannot be used normally, which is recorded as 100% deformation, that is, the worst quality. The model of the bending strength of the etching area is the limit state, and the standard material composition model is 0% deformation, that is, the best quality;

[0016] S3-2. By collecting the rare earth content of two different materials and the bending strength of the etched area scanned after the material is put into use, the bending strength of the etched area material is between 0-100%, and the functional relationship between the rare earth content of the material and the vehicle code scanned after the material is put into use is obtained. The formula is:

[0017]

[0018] Among them, Q x Q is the rare earth content in the rare earth component content of the etched area of ​​the material during the first scan, y is the rare earth content of the rare earth component content in the etched area of ​​the material during the second scan, A% is the bending strength of the etched area of ​​the material during the first scan, and B% is the bending strength of the etched area of ​​the material during the second scan, and finally k is obtained;

[0019] S3-3. After the functional relationship is obtained, the rare earth content Q0 corresponding to 100% deformation, that is, when the model of the bending strength of the etching area is in the limit state, is obtained. This value is the maximum rare earth content allowed by the rare earth component content in the etching area.

[0020] According to the above technical solution, in S3, the comprehensive identification method is: under the premise of ensuring that the rare earth component content in the etching area is less than Q0, the number of bad spots scanned after the material is put into use is counted multiple times, and the quality of the etching area is judged according to the number of bad spots. The fewer the number of bad spots, the better the quality of the etching area. Since the number of bad spots and the rare earth component content in the etching area are not in a linear positive correlation, the quality of the etching area with the corresponding rare earth component content in the etching area is the best when the number of bad spots decreases fastest with the change of the rare earth component content in the etching area.

[0021] According to the above technical solution, in S4, the specific method for improving the rare earth content of the material is: directly reduce the rare earth content during the first improvement, calculate the improved rare earth content during subsequent improvements, record the number of bad spots in the material after the last improvement, and compare it with the number of bad spots in the material after the second to last improvement. If it tends to decrease, do not change the improved rare earth content; if it tends to increase, correct the improved rare earth content according to the increase ratio.

[0022] According to the above technical solution, in S4, the rare earth content Q is improved n The calculation formula is:

[0023] When V n ≤V n-1 When n =Q n-1 ;

[0024] When V n >V n-1 hour,

[0025] Where Q n-1 is the improved rare earth content obtained after the penultimate improvement, V n is the number of bad pixels measured during the last improvement, V n-1 is the number of bad pixels measured during the penultimate improvement, k is the weight parameter of the number of bad pixels when improving the rare earth content calculation, p is the weight parameter of the changing trend of the number of bad pixels when improving the rare earth content calculation, and n is the number of improvements.

[0026] According to the above technical solution, in S4, the specific method of applying the improved parameters to the material composition model is: designing a new rare earth content in the etching area according to the optimized theoretical value of the rare earth content, updating the material model and performing simulation tests to determine whether the improved etching area affects the normal operation of the material. If it does not affect the normal operation, continue to perform stress analysis on the etching area by applying external force and load to ensure that the improved parameters can be applied.

[0027] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: the present invention, by performing a bending resistance test and ultrasonic scanning on the material, conducts a comprehensive analysis on the number of bad spots in the material area and the bending resistance of the material, and obtains the optimal rare earth component content in the etching area, and repeatedly collects parameters and continuously improves them when the material is used multiple times, so that the improved rare earth component content in the etching area can continuously adapt to the small-scale structural optimization of the material itself. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0029] Figure 1 It is a schematic diagram of the overall module structure of the present invention. DETAILED DESCRIPTION

[0030] 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.

[0031] See also Figure 1 The present invention provides a technical solution: a recognition system for vehicle codes engraved by a robot laser, comprising a code recognition module, a bending strength interpretation module, and a material improvement module. The code recognition module is used to collect internal structure data of the etched material using image scanning technology, the bending strength interpretation module is used to process image data to determine the quality of the etching area, and the material improvement module is used to adjust the rare earth element content of the material;

[0032] The code recognition module includes an ultrasonic transmitting unit, an ultrasonic receiving unit, a bad point recognition module, a structure fitting module, a data acquisition module, a material display module, and an etching area recognition module. The ultrasonic transmitting unit is used to use ultrasonic waves to penetrate the etching material. The ultrasonic receiving unit is electrically connected to the bad point recognition module, the material display module is electrically connected to the structure fitting module, and the etching area recognition module is electrically connected to the structure fitting module; the ultrasonic receiving unit is used to detect the reflection and scattering of ultrasonic waves and obtain the image information inside the material. The bad point recognition module is used to determine whether there are bad points in the material by the attenuation degree of ultrasonic waves. The data acquisition module is used to input the material composition by means of data acquisition. The material display module is used to display the acquired material composition. The structure fitting module is used to obtain a material composition model based on the proportion of the overall material composition acquired. The etching area recognition module is used to identify the etching area on the material structure.

[0033] The bending strength interpretation module includes a bad point counting module, a bending strength analysis module, a material composition storage library, and an etching judgment module. The bad point counting module is electrically connected to the bad point identification module, the material composition storage library is electrically connected to the material display module, the bending strength analysis module is electrically connected to the material composition storage library, and the etching judgment module is electrically connected to the bad point counting module and the bending strength analysis module. The bad point counting module is used to count the number of bad points judged to exist in the etching code, the bending strength analysis module is used to analyze the bending strength of the etching area near the material, the material composition storage library is used to store standard material composition models for analysis and comparison with actual usage, and the etching judgment module is used to comprehensively analyze the etching quality of the image code based on the number of bad points in the etching code and the bending strength of the etching area.

[0034] The material improvement module includes a composition adjustment calculation module, a composition modification module, and a practice verification module. The composition adjustment calculation module is used to re-improve the rare earth content suitable for this material. The composition modification module is used to modify the material parameters on the material composition model of the material. The practice verification module is used to determine whether the improved material can be etched and used normally.

[0035] The system's working methods include:

[0036] S1. After the etching of the material is completed, the material composition is acquired by using the data acquisition module to obtain a standard material composition model;

[0037] S2. After the material is put into use, the material is scanned by using an ultrasonic transmitting unit, the number of bad code points in the material area is counted, and the material is acquired again by using a data acquisition module to obtain the overall composition ratio of the material after use;

[0038] S3, comprehensively judging the quality of the etching area according to the number of bad spots and the bending strength of the etching area;

[0039] S4. Improve the rare earth content of the material and apply the improved parameters to the material composition model to confirm that the improved material can be etched and used normally;

[0040] In S3, the specific method for identifying the bending strength of the etching area is:

[0041] S3-1, bend the scanned standard material composition model along the material area until the bent material composition model reaches a level that cannot be used normally, which is recorded as 100% deformation, that is, the worst quality. The model of the bending strength of the etching area is the limit state, and the standard material composition model is 0% deformation, that is, the best quality;

[0042] S3-2. By collecting the rare earth content of two different materials and the bending strength of the etched area scanned after the material is put into use, the bending strength of the etched area material is between 0-100%, and the functional relationship between the rare earth content of the material and the vehicle code scanned after the material is put into use is obtained. The formula is:

[0043]

[0044] Among them, Q x Q is the rare earth content in the rare earth component content of the etched area of ​​the material during the first scan, y is the rare earth content of the rare earth component content in the etched area of ​​the material during the second scan, A% is the bending strength of the etched area of ​​the material during the first scan, and B% is the bending strength of the etched area of ​​the material during the second scan, and finally k is obtained;

[0045] S3-3. After the functional relationship is obtained, the rare earth content Q0 corresponding to 100% deformation, that is, when the model of the bending strength of the etching area is in the limit state, is obtained. This value is the maximum rare earth content allowed by the rare earth component content in the etching area;

[0046] In S3, the comprehensive identification method is: under the premise of ensuring that the rare earth content of the etching area is less than Q0, the number of bad points scanned after the material is put into use is counted multiple times, and the quality of the etching area is judged according to the number of bad points. The fewer the number of bad points, the better the quality of the etching area. Since the number of bad points and the rare earth content of the etching area are not linearly positively correlated, the etching area with the best rare earth content quality is when the number of bad points decreases fastest with the change of the rare earth content of the etching area;

[0047] In S4, the specific method for improving the rare earth content of the material is: directly reducing the rare earth content during the first improvement, calculating the improved rare earth content during subsequent improvements, recording the number of bad spots in the material after the last improvement, and comparing it with the number of bad spots in the material after the penultimate improvement. If it tends to decrease, the improved rare earth content is not changed; if it tends to increase, the improved rare earth content is corrected according to the increase ratio;

[0048] In S4, the rare earth content Q is improved n The calculation formula is:

[0049] When V n ≤V n-1 When n =Q n-1 ;

[0050] When V n >V n-1 hour,

[0051] Where Q n-1 is the improved rare earth content obtained after the penultimate improvement, V n is the number of bad pixels measured during the last improvement, V n-1 is the number of bad pixels measured during the penultimate improvement, k is the weight parameter of the number of bad pixels when improving the rare earth content calculation, p is the weight parameter of the change trend of the number of bad pixels when improving the rare earth content calculation, and n is the number of improvements;

[0052] In S4, the specific method of applying the improved parameters to the material composition model is: designing a new rare earth content in the etching area according to the optimized theoretical value of the rare earth content, updating the material model and performing simulation tests to determine whether the improved etching area affects the normal operation of the material. If it does not affect the normal operation, continue to perform stress analysis on the etching area by applying external force and load to ensure that the improved parameters can be applied.

[0053] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0054] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A vehicle code recognition system for a robotic arm laser engraving, characterized by: It includes a code recognition module, a bending strength interpretation module, and a material improvement module. The code recognition module is used to collect internal structure data of the etched material using image scanning technology. The bending strength interpretation module is used to process image data to determine the quality of the etching area. The material improvement module is used to adjust the rare earth element content of the material.

2. A vehicle code recognition system for a robotic arm laser engraving according to claim 1, characterized in that: The code recognition module includes an ultrasonic transmitting unit, an ultrasonic receiving unit, a bad point recognition module, a structure fitting module, a data acquisition module, a material display module, and an etching area recognition module. The ultrasonic transmitting unit is used to penetrate the etching material with ultrasonic waves. The ultrasonic receiving unit is electrically connected to the bad point recognition module, the material display module is electrically connected to the structure fitting module, and the etching area recognition module is electrically connected to the structure fitting module; the ultrasonic receiving unit is used to detect the reflection and scattering of ultrasonic waves and obtain the image information inside the material. The bad point recognition module is used to determine whether there are bad points in the material by the attenuation degree of ultrasonic waves. The data acquisition module is used to input the material composition by means of data acquisition, the material display module is used to display the acquired material composition, the structure fitting module is used to obtain a material composition model based on the proportion of the overall material composition acquired, and the etching area recognition module is used to identify the etching area on the material structure; The bending strength interpretation module includes a bad point counting module, a bending strength analysis module, a material composition storage library, and an etching judgment module. The bad point counting module is electrically connected to the bad point identification module, the material composition storage library is electrically connected to the material display module, the bending strength analysis module is electrically connected to the material composition storage library, and the etching judgment module is electrically connected to both the bad point counting module and the bending strength analysis module; the bad point counting module is used to count the number of bad points judged to exist in the etching code, the bending strength analysis module is used to analyze the bending strength of the etching area near the material, the material composition storage library is used to store standard material composition models for analysis and comparison with actual usage, and the etching judgment module is used to comprehensively analyze the etching quality of the image code based on the number of bad points in the etching code and the bending strength of the etching area; The material improvement module includes a composition adjustment calculation module, a composition modification module, and a practical verification module. The composition adjustment calculation module is used to re-improve the rare earth content suitable for this material, the composition modification module is used to modify the material parameters on the material composition model of the material, and the practical verification module is used to determine whether the improved material can be etched and used normally.

3. The vehicle code recognition system for a robotic arm laser engraving according to claim 2 is characterized by: The system's working methods include: S1. After the etching of the material is completed, the material composition is acquired by using the data acquisition module to obtain a standard material composition model; S2. After the material is put into use, the material is scanned by using an ultrasonic transmitting unit, the number of bad code points in the material area is counted, and the material is acquired again by using a data acquisition module to obtain the overall composition ratio of the material after use; S3, comprehensively judging the quality of the etching area according to the number of bad spots and the bending strength of the etching area; S4. Improve the rare earth content of the material and apply the improved parameters to the material composition model to confirm that the improved material can be etched and used normally.

4. A vehicle code recognition system for a robotic arm laser engraving according to claim 3, characterized in that: In S3, the specific method for identifying the bending strength of the etching area is: S3-1, bend the scanned standard material composition model along the material area until the bent material composition model reaches a level that cannot be used normally, which is recorded as 100% deformation, that is, the worst quality. The model of the bending strength of the etching area is the limit state, and the standard material composition model is 0% deformation, that is, the best quality; S3-2. By collecting the rare earth content of two different materials and the bending strength of the etched area scanned after the material is put into use, the bending strength of the etched area material is between 0-100%, and the functional relationship between the rare earth content of the material and the vehicle code scanned after the material is put into use is obtained. The formula is: Among them, Q x Q is the rare earth content in the rare earth component content of the etched area of ​​the material during the first scan, y is the rare earth content of the rare earth component content in the etched area of ​​the material during the second scan, A% is the bending strength of the etched area of ​​the material during the first scan, and B% is the bending strength of the etched area of ​​the material during the second scan, and finally k is obtained; S3-3. After the functional relationship is obtained, the rare earth content Q0 corresponding to 100% deformation, that is, when the model of the bending strength of the etching area is in the limit state, is obtained. This value is the maximum rare earth content allowed by the rare earth component content in the etching area.

5. The vehicle code recognition system for a robotic arm laser engraving according to claim 4 is characterized by: In S3, the comprehensive identification method is: under the premise of ensuring that the rare earth component content in the etching area is less than Q0, the number of bad spots scanned after the material is put into use is counted multiple times, and the quality of the etching area is judged according to the number of bad spots. The fewer the number of bad spots, the better the quality of the etching area. Since the number of bad spots and the rare earth component content in the etching area are not in a linear positive correlation, the rare earth component content in the etching area corresponding to the etching area has the best quality when the number of bad spots decreases fastest with the change of the rare earth component content in the etching area.

6. A vehicle code recognition system for laser engraving with a robotic arm according to claim 5, characterized in that: In S4, the specific method for improving the rare earth content of the material is: directly reduce the rare earth content during the first improvement, calculate the improved rare earth content during subsequent improvements, record the number of bad spots in the material after the last improvement, and compare it with the number of bad spots in the material after the second to last improvement. If it tends to decrease, do not change the improved rare earth content; if it tends to increase, correct the improved rare earth content according to the increase ratio.

7. A vehicle code recognition system for a robotic arm laser engraving according to claim 6, characterized in that: In the S4, the rare earth content Q is improved n The calculation formula is: When V n ≤V n-1 When n =Q n-1 ; When V n >V n-1 hour, Where Q n-1 is the improved rare earth content obtained after the penultimate improvement, V n is the number of bad pixels measured during the last improvement, V n-1 is the number of bad pixels measured during the penultimate improvement, k is the weight parameter of the number of bad pixels when improving the rare earth content calculation, p is the weight parameter of the changing trend of the number of bad pixels when improving the rare earth content calculation, and n is the number of improvements.

8. The vehicle code recognition system for laser marking by a robotic arm according to claim 7, characterized in that: In S4, the specific method of applying the improved parameters to the material composition model is: designing a new rare earth content in the etching area according to the optimized theoretical value of the rare earth content, updating the material model and performing simulation tests to determine whether the improved etching area affects the normal operation of the material. If it does not affect the normal operation, continue to perform stress analysis on the etching area by applying external force and load to ensure that the improved parameters can be applied.

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