Metal bonding interface interlocking texture laser etching manufacturing method based on machine vision

Abstract

The invention discloses a metal bonding interface interlocking texture laser etching manufacturing method based on machine vision. The metal bonding interface interlocking texture laser etching manufacturing method comprises the following steps that S10, a machining platform is built; s20, a laser generator is used for emitting a laser beam, and laser etching machining is conducted on the surface of the machined workpiece along a preset track; s30, a camera is used for shooting a surface texture image of the machined workpiece in real time; step S40, preprocessing the surface texture image; s50, performing etching area feature recognition on the preprocessed surface texture image, calibrating the edge position of an etching sunken area, and measuring the width of a sunken opening; step S60, judging whether the width of the sunken opening becomes small and gradually approaches to the diameter of the laser focus, if so, stopping next etching, and finishing processing; and if not, repeating the steps S20 to S60. According to the metal bonding interface interlocking texture laser etching manufacturing method based on machine vision, the accuracy, the intelligent degree and the production efficiency of feature structure machining can be effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of metal surface processing, and in particular to a laser etching manufacturing method for interlocking textures at a metal bonding interface based on machine vision. Background Art

[0002] The description in this section merely provides background information related to the disclosure of this specification and does not constitute prior art.

[0003] Metal bonding structure refers to a structure formed by bonding a metal material with the same or different materials. It has the advantages of light weight, high strength, and uniform stress distribution. It has been widely used in aerospace, automobile, rail transportation, shipbuilding, electronics, construction and other fields. The interlocking of the metal-polymer interface during the bonding process can greatly improve the mechanical anchoring effect of the interface and significantly improve the mechanical properties of the bonding interface.

[0004] Making a constricted inner cavity structure on the metal surface, that is, the width of the inner cavity opening is smaller than its middle width, is a key prerequisite for preparing the metal-polymer interlocking interface. One method that can improve the strength and fracture toughness of metal bonding structures is to use laser to etch textures in the area to be connected on the metal surface, which can not only increase the bonding area of ​​the metal, but also obtain an interlocking structure at the interface under specific laser parameters, thereby achieving the purpose of improving the metal bonding strength.

[0005] The interaction mechanism between laser and metal surface is complex. If the etching depth is insufficient, it is difficult to form a shrinking inner cavity structure. If the etching depth is too large, it is easy to form bonding pores at the bottom of the inner cavity and reduce the rigidity of the metal matrix. It is very important to accurately judge the moment when the inner locking structure appears and control the processing action in real time. Therefore, it is particularly important to use machine vision methods to realize online detection and control of metal surface texture prepared by laser etching.

[0006] It should be noted that the above introduction to the technical background is only for the convenience of providing a clear and complete description of the technical solutions of this specification and for the convenience of understanding by those skilled in the art. It cannot be considered that the above technical solutions are well known to those skilled in the art simply because they are described in the background technology section of this specification. Summary of the invention

[0007] In view of the shortcomings of the prior art, one purpose of this specification is to provide a machine vision-based laser etching manufacturing method for metal bonding interface interlocking texture, which can realize online detection of laser-processed metal workpiece surface texture and closed-loop control of the manufacturing process, and effectively improve the accuracy, intelligence and production efficiency of feature structure processing.

[0008] To achieve the above-mentioned purpose, the embodiment of this specification provides a laser etching manufacturing method of metal bonding interface interlocking texture based on machine vision, comprising the following steps:

[0009] Step S10: constructing a processing platform; the processing platform includes a laser generator, a camera, a visual inspection system function module, a laser controller and a control unit, the visual inspection system function module is electrically connected to the camera and the control unit respectively, and the laser controller is electrically connected to the laser generator and the control unit respectively;

[0010] Step S20: using the laser generator to emit a laser beam to perform laser etching on the surface of the workpiece along a preset trajectory;

[0011] Step S30: using the camera to capture a surface texture image of the workpiece being processed in real time;

[0012] Step S40: preprocessing the surface texture image;

[0013] Step S50: performing etching area feature recognition on the pre-processed surface texture image, calibrating the edge position of the etching recessed area, and measuring the width of the recessed opening;

[0014] Step S60: Determine whether the width of the recessed opening changes from large to small and gradually approaches the laser focus diameter. If so, stop the next etching and end the processing; if not, repeat steps S20 to S60.

[0015] As a preferred embodiment, in step S10, the processing platform also includes a robotic arm, which is electrically connected to the control unit; the camera is located on one side of the laser generator, and the camera and the laser generator are connected to the robotic arm via a connecting part.

[0016] As a preferred embodiment, in the step S20, the laser generator is adjusted using the robotic arm so that the laser emitted by the laser generator is vertically incident on the surface of the workpiece being processed and the laser emitted by the laser generator is focused on the surface of the workpiece being processed.

[0017] As a preferred embodiment, in step S20, the workpiece to be processed remains stationary, and the control unit controls the robot arm to drive the laser generator to move for laser etching processing; or, the laser generator remains stationary, and the workpiece to be processed moves for laser etching processing.

[0018] As a preferred implementation, the visual inspection system functional module includes a camera parameter module, an image acquisition module and a feature detection module; the camera parameter module is used to adjust the parameters of the camera, and the parameters include brightness, focal length, magnification, gain and color; the image acquisition module includes an image acquisition unit, an image storage unit and an image viewing unit; the feature detection module includes an image processing unit, a feature recognition unit and a feature width measurement unit.

[0019] As a preferred implementation, the laser generator includes a continuous laser, a nanosecond laser, a picosecond laser or a femtosecond laser.

[0020] As a preferred implementation manner, the material of the workpiece to be processed includes stainless steel, carbon steel, alloy steel, aluminum alloy, magnesium alloy, and titanium alloy.

[0021] As a preferred implementation, the laser etching process includes pit etching and groove etching.

[0022] As a preferred implementation, step S40 includes:

[0023] Performing grayscale processing on the surface texture image;

[0024] Using a median filtering method to perform denoising on the surface texture image after grayscale processing;

[0025] The threshold segmentation method is used to perform image segmentation on the surface texture image after denoising to separate the target features from the background.

[0026] As a preferred implementation, step S50 includes:

[0027] Perform texture edge detection;

[0028] Marking of connected domains;

[0029] The average opening diameter of ten locations within the selected area was measured as the recess opening width.

[0030] Beneficial effects:

[0031] The machine vision-based laser etching manufacturing method for interlocking textures of metal bonding interfaces provided in this embodiment can realize intelligent manufacturing of laser-processed metal workpiece surface textures by setting steps S10, S20, S30, S40, S50 and S60. By performing real-time image acquisition, processing, feature recognition and feature size measurement on the laser-etched metal surface, the laser etching preparation of the "shrinking"-shaped inner cavity on the metal surface is realized, the mechanical anchoring effect of the bonding interface is enhanced, and the interface strength and fracture toughness of the metal bonding component can be significantly improved. Compared with manual judgment of the feature structure, the feature structure detection by machine vision means (camera) can effectively avoid human errors and improve the processing accuracy. Furthermore, judging whether the shrinking structure occurs by the opening width of the laser-processed texture is more efficient and quicker than other judgment methods. This manufacturing method can realize the closed loop of laser-processed metal workpiece surface texture detection and control, improve the accuracy of feature structure processing, save productivity and improve production efficiency.

[0032] With reference to the following description and the accompanying drawings, the specific embodiments of the present invention are disclosed in detail, indicating the manner in which the principles of the present invention can be adopted. It should be understood that the embodiments of the present invention are not limited in scope thereby.

[0033] Features described and / or illustrated with respect to one embodiment may be used in the same or similar manner in one or more other embodiments, combined with features in other embodiments, or substituted for features in other embodiments.

[0034] It should be emphasized that the term “include / comprises” when used herein refers to the presence of features, integers, steps or components, but does not exclude the presence or addition of one or more other features, integers, steps or components. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without paying creative labor.

[0036] Figure 1 A flowchart of the steps of a laser etching manufacturing method for metal bonding interface interlocking texture based on machine vision provided in this embodiment;

[0037] Figure 2 A schematic diagram of the structure of a processing platform provided in this embodiment;

[0038] Figure 3This is a schematic diagram of the structure of a workpiece surface after laser processing in one embodiment of the present invention;

[0039] Figure 4 A surface texture image of a workpiece surface after laser processing in one example of the present embodiment;

[0040] Figure 5 for Figure 4 Corresponding graphs of protrusion, groove and opening width at different processing moments;

[0041] Figure 6 This is a graph showing the change of opening width with groove depth during laser processing of titanium alloy material;

[0042] Figure 7 This is a graph showing the change in opening width with groove depth during laser processing of carbon steel material.

[0043] Description of reference numerals:

[0044] 1. Robotic arm; 2. Laser controller; 3. Laser camera integrated system; 301. Laser generator; 302. Camera; 303. Connecting part; 4. Visual inspection system functional module; 5. Workpiece to be processed; 6. Control part; 7. Protrusion; 8. Groove; w, opening width. DETAILED DESCRIPTION

[0045] In order to enable those skilled in the art to better understand the technical solutions in the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings 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 should fall within the scope of protection of the present invention.

[0046] It should be noted that when an element is referred to as being "disposed on" another element, it may be directly on the other element or there may be another element centered thereon. When an element is considered to be "connected to" another element, it may be directly connected to the other element or there may be another element centered thereon at the same time. The terms "vertical", "horizontal", "left", "right" and similar expressions used herein are for illustrative purposes only and do not represent the only implementation method.

[0047] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art of the present invention. The terms used herein in the specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more related listed items.

[0048] See also Figure 1 The embodiment of the present application provides a laser etching manufacturing method for metal bonding interface interlocking texture based on machine vision, comprising the following steps:

[0049] Step S10: Building a processing platform.

[0050] Among them, Figure 2 As shown, the processing platform includes a laser generator 301, a camera 302, a visual inspection system functional module 4, a laser controller 2 and a control unit 6. The visual inspection system functional module 4 is electrically connected to the camera 302 and the control unit 6 respectively, and the laser controller 2 is electrically connected to the laser generator 301 and the control unit 6 respectively. The laser controller 2 is used to control the laser parameters of the laser generator 301. The laser generator 301 processes the surface of the workpiece 5 to be processed, and the camera 302 converts the surface texture light signal of the workpiece 5 to be processed into an electrical signal, thereby realizing the storage and display of the image.

[0051] Step S20: using the laser generator 301 to emit a laser beam to perform laser etching on the surface of the workpiece 5 along a preset trajectory.

[0052] Step S30: Use the camera 302 to take a real-time image of the surface texture of the workpiece 5. Figure 4 shown.

[0053] Step S40: pre-processing the surface texture image.

[0054] Step S50: perform etching area feature recognition on the pre-processed surface texture image, calibrate the edge position of the etching concave area, and measure the concave opening width w, such as Figure 3 and Figure 5 shown.

[0055] Step S60: Determine whether the recess opening width w changes from large to small and gradually approaches the laser focus diameter. If so, stop the next etching and end the processing; if not, repeat steps S20 to S60.

[0056] The laser etching manufacturing method for interlocking texture of metal bonding interface based on machine vision provided in this embodiment can realize intelligent manufacturing of laser-processed metal workpiece surface texture by setting steps S10, S20, S30, S40, S50 and S60. By performing real-time image acquisition, processing, feature recognition and feature size measurement on the laser-etched metal surface, the laser etching preparation of the "shrinking" shaped inner cavity on the metal surface is realized, the mechanical anchoring effect of the bonding interface is enhanced, and the interface strength and fracture toughness of the metal bonding component can be significantly improved. Compared with manual judgment of the feature structure, the feature structure detection by machine vision means (camera 302) can effectively avoid human errors and improve the processing accuracy. Furthermore, judging whether the shrinking structure occurs by the opening width w of the laser-processed texture is more efficient and quicker than other judgment methods. The manufacturing method can realize the closed loop of laser-processed metal workpiece surface texture detection and control, improve the accuracy of feature structure processing, save productivity and improve production efficiency.

[0057] In the present embodiment, in the step S10, the processing platform further comprises a robot arm 1, and the robot arm 1 is electrically connected to the control unit 6, so that the control unit 6 can control the movement of the robot arm 1. The camera 302 is located on one side of the laser generator 301, and the camera 302 and the laser generator 301 are connected to the robot arm 1 through a connection unit 303. Preferably, the robot arm 1 is connected to the laser camera integrated system 3 through the connection unit 303, and the laser camera integrated system 3 is provided with a camera 302 and a laser generator 301. The control unit 6 is connected to the robot arm 1, the laser controller 2, and the visual inspection system functional module 4, and controls the robot arm 1 and the laser controller 2 after online recognition of the embedded structure according to the features obtained by image recognition. The robot arm 1 can control the motion trajectory of the laser generator 301, and the laser controller 2 can control the laser parameters of the laser generator 301.

[0058] In the step S20 , the laser generator 301 is adjusted using the robot arm 1 so that the laser emitted by the laser generator 301 is vertically incident on the surface of the workpiece 5 , and the laser emitted by the laser generator 301 is focused on the surface of the workpiece 5 .

[0059] In this embodiment, in step S20, the workpiece 5 to be processed remains stationary, and the control unit 6 controls the robot arm 1 to drive the laser generator 301 to move for laser etching processing. In another embodiment, the robot arm 1 is not connected to the laser generator 301, but is connected to the workpiece 5 to be processed. During the laser processing, the laser generator 301 remains stationary, and the workpiece 5 to be processed is driven by the robot arm 1 to move for laser etching processing.

[0060] In this embodiment, the visual inspection system functional module 4 includes a camera parameter module, an image acquisition module and a feature detection module. The camera parameter module is used to adjust the parameters of the camera 302, and the parameters include brightness, focal length, magnification, gain and color. The image acquisition module includes an image acquisition unit, an image storage unit and an image viewing unit. The feature detection module includes an image processing unit, a feature recognition unit and a feature width measurement unit.

[0061] Specifically, the laser generator 301 includes a continuous laser, a nanosecond laser, a picosecond laser or a femtosecond laser. The material of the workpiece 5 includes stainless steel, carbon steel, alloy steel, aluminum alloy, magnesium alloy, titanium alloy. The laser etching process includes pit etching and groove etching.

[0062] In a specific embodiment, the above manufacturing method is used to prepare the interlocking texture of the bonding interface of the titanium alloy material, that is, when the material of the workpiece 5 to be processed is titanium alloy, a nanosecond laser is selected, and the camera 302 uses an industrial microscope camera. The image collected by the camera 302 is not compressed, so that a high-quality RGB image can be obtained. The camera 302 lens can be a normal lens or a telecentric lens. For metal workpieces with a small processing range, it is necessary to ensure a sufficient field of view and a larger magnification during observation, and a telecentric lens can be selected.

[0063] The workpiece 5 in this example is a titanium alloy plate. Experiments have verified that under certain laser parameters, a shrinking etched texture can be formed on the surface of the titanium alloy plate, and a shrinking inner cavity appears when the opening width w reaches a certain size. Therefore, it can be determined whether a shrinking inner cavity appears by observing the etched texture width.

[0064] In step S20, before laser metal surface texturing, the entire metal workpiece surface is first subjected to continuous laser etching to remove the workpiece surface layer, remove grease, rust, etc. on the material surface, and then the processing contour trajectory pattern (i.e., the preset trajectory) is designed and imported, and the laser parameters are set.

[0065] In step S40, the surface texture image is preprocessed to improve the image quality and the recognition rate of the surface texture features. Step S40 specifically includes:

[0066] Step S401: performing grayscale processing on the surface texture image.

[0067] Compared with color images, grayscale images take up less memory, run faster, and can increase visual contrast. Since the human eye is most sensitive to green and least sensitive to blue, the three vectors R, G, and B are comprehensively considered using the weighted average method based on importance and other indicators. The final grayscale after processing is g(i,j)=0.3R(i,j)+0.59G(i,j)+0.11B(i,j).

[0068] Step S402: using a median filtering method to perform denoising on the surface texture image after grayscale processing.

[0069] Sort all pixel sizes in descending order {x 1 ,x 2 ,…,x n}, get the median of the sequence:

[0070]

[0071] The middle value y is used as the new grayscale value of the target pixel.

[0072] Step S403: using a threshold segmentation method to perform image segmentation on the surface texture image after denoising, so as to separate the target features from the background.

[0073] Specifically, the pixels are divided into different subsets according to the grayscale level. Each subset corresponds to a different area in the image. According to the pixel values ​​of different subsets, a suitable threshold is selected for the image to achieve the segmentation of the target object and the background. This example uses the region growing method for threshold segmentation, that is, first a seed point is selected in the target area as the starting point of growth, and then the pixels in the seed point area are compared, and the pixels that meet the growth rules are divided into the area. This iteration is carried out until all the pixels in the image with similar attributes to the target object belong to one region.

[0074] In this embodiment, step S50 includes:

[0075] Step S501: Perform texture edge detection.

[0076] Specifically, the edge is located at the junction of the target object and the background, which is the area with the most drastic grayscale changes in the image. Gradient-based edge detection is used to extract the edge contour of the concave area. More specifically, the canny operator with advantages such as good edge detection effect and positioning accuracy is used for edge detection.

[0077] Step S502: marking connected domains.

[0078] Specifically, due to the influence of metal splashing during laser processing, there will occasionally be some foreign matter sticking to the edge of the collected image. In this case, the texture contour obtained by edge detection will have some independent pixel areas. The width-first search algorithm is used to input the image after edge detection, and the width-first search algorithm is used to traverse the entire image. First, all connected domains in the image are marked, and then the largest connected domain is found in the marked connected domains for output.

[0079] Step S503: measuring the average opening diameters of ten locations within the selected area as the recess opening width w.

[0080] Specifically, the average opening diameter d of ten locations in the selected area is measured using the horizontal multi-line method in the software system. Figure 6 As shown, when the average opening diameter d decreases to about 55 mm and the opening width w tends to be stable and no longer decreases significantly, it is determined that a shrinkage-like structure appears and the next processing is stopped, otherwise the processing continues.

[0081] In another specific embodiment, the above manufacturing method is used to prepare the interlocking texture of the bonding interface of carbon steel material, that is, when the material of the workpiece 5 to be processed is carbon steel, a nanosecond laser is selected. The operation steps are the same as those in the previous embodiment (preparing the interlocking texture of the bonding interface of titanium alloy material). Figure 7 As shown, when the average opening diameter d decreases to about 60 mm and the opening width w tends to be stable and no longer decreases significantly, it is determined that a shrinkage-like structure appears and the next processing is stopped, otherwise the processing continues.

[0082] In this embodiment, the bonding surface of the workpiece 5 includes but is not limited to secondary bonding, co-curing bonding, metal-thermoplastic polymer laser welding, metal-thermoplastic polymer ultrasonic welding, metal-thermoplastic polymer induction welding, metal-prepreg molding, etc., which involve the bonding of metal and polymer. The thermoplastic polymer includes a single thermoplastic polymer, a blended thermoplastic polymer, a fiber-reinforced thermoplastic polymer, a particle-reinforced thermoplastic polymer, etc.

[0083] exist Figure 5 In the figure, the adhesive is present only to demonstrate the effect, in order to make the protrusions 7 and the grooves 8 more obvious. In the surface texture image of the processed workpiece 5 taken by the actual camera 302, there is no adhesive.

[0084] It should be noted that, in the description of this specification, the terms "first", "second", etc. are only used for descriptive purposes and to distinguish similar objects. There is no order of precedence between the two, and they cannot be understood as indicating or implying relative importance. In addition, in the description of this specification, unless otherwise specified, the meaning of "plurality" is two or more.

[0085] Any numerical value cited herein includes all values ​​of lower and upper values ​​that increase by one unit from the lower limit to the upper limit, and there is at least a two-unit interval between any lower value and any higher value. For example, if the value of the quantity of a component or a process variable (such as temperature, pressure, time, etc.) is stated to be from 1 to 90, preferably from 20 to 80, and more preferably from 30 to 70, the purpose is to illustrate that values ​​such as 15 to 85, 22 to 68, 43 to 51, 30 to 32 are also explicitly listed in the specification. For values ​​less than 1, one unit is appropriately considered to be 0.0001, 0.001, 0.01, 0.1. These are merely examples that are intended to be clearly expressed, and it can be considered that all possible combinations of numerical values ​​listed between the lowest value and the highest value are clearly stated in the specification in a similar manner.

[0086] Unless otherwise specified, all ranges include the endpoints and all numbers between the endpoints. "About" or "approximately" used with a range applies to both endpoints of the range. Thus, "about 20 to 30" is intended to cover "about 20 to about 30", including at least the specified endpoints.

[0087] All articles and references disclosed, including patent applications and publications, are incorporated herein by reference for all purposes. The term "consisting essentially of..." to describe a combination should include the identified elements, ingredients, parts or steps and other elements, ingredients, parts or steps that do not substantially affect the basic novel characteristics of the combination. The use of the terms "comprising" or "including" to describe a combination of elements, ingredients, parts or steps herein also contemplates embodiments that consist essentially of these elements, ingredients, parts or steps. By using the term "may", it is intended to indicate that any attribute described that "may" include is optional.

[0088] Multiple elements, ingredients, parts or steps can be provided by a single integrated element, ingredient, part or step. Alternatively, a single integrated element, ingredient, part or step can be divided into separate multiple elements, ingredients, parts or steps. The disclosure "one" or "an" used to describe an element, ingredient, part or step is not intended to exclude other elements, ingredients, parts or steps.

[0089] It should be understood that the above description is for illustration and not for limitation. Many embodiments and many applications beyond the examples provided will be apparent to those skilled in the art upon reading the above description. Therefore, the scope of the present teachings should not be determined with reference to the above description, but should be determined with reference to the appended claims and the full scope of equivalents possessed by such claims. For the purpose of comprehensiveness, all articles and references, including disclosures of patent applications and publications, are incorporated herein by reference. The omission of any aspect of the subject matter disclosed herein in the preceding claims is not intended to be a waiver of the subject matter, nor should it be considered that the inventors did not consider the subject matter to be part of the disclosed inventive subject matter.

Claims

1. A laser etching manufacturing method for metal bonding interface interlocking texture based on machine vision, characterized in that: The following steps are involved: Step S10: constructing a processing platform; the processing platform includes a laser generator, a camera, a visual inspection system function module, a laser controller and a control unit, the visual inspection system function module is electrically connected to the camera and the control unit respectively, and the laser controller is electrically connected to the laser generator and the control unit respectively; Step S20: using the laser generator to emit a laser beam to perform laser etching on the surface of the workpiece along a preset trajectory; Step S30: using the camera to capture a surface texture image of the workpiece being processed in real time; Step S40: preprocessing the surface texture image; Step S50: performing etching area feature recognition on the pre-processed surface texture image, calibrating the edge position of the etching recessed area, and measuring the width of the recessed opening; Step S60: Determine whether the width of the recessed opening changes from large to small and gradually approaches the laser focus diameter. If so, stop the next etching and end the processing; if not, repeat steps S20 to S60.

2. The method for laser etching of metal bonding interface interlocking texture based on machine vision according to claim 1, characterized in that: In the step S10, the processing platform further includes a robot arm, and the robot arm is electrically connected to the control unit; the camera is located on one side of the laser generator, and the camera and the laser generator are connected to the robot arm via a connecting part.

3. The method for laser etching of metal bonding interface interlocking texture based on machine vision according to claim 2, characterized in that: In the step S20, the laser generator is adjusted using the robot arm so that the laser emitted by the laser generator is vertically incident on the surface of the workpiece being processed, and the laser emitted by the laser generator is focused on the surface of the workpiece being processed.

4. The method for laser etching of metal bonding interface interlocking texture based on machine vision according to claim 2, characterized in that: In the step S20, the workpiece to be processed remains stationary, and the control unit controls the robot arm to drive the laser generator to move for laser etching processing; or, the laser generator remains stationary, and the workpiece to be processed moves for laser etching processing.

5. The laser etching manufacturing method for metal bonding interface interlocking texture based on machine vision according to claim 1 is characterized in that: The functional modules of the visual inspection system include a camera parameter module, an image acquisition module and a feature detection module; the camera parameter module is used to adjust the parameters of the camera, and the parameters include brightness, focal length, magnification, gain and color; the image acquisition module includes an image acquisition unit, an image storage unit and an image viewing unit; the feature detection module includes an image processing unit, a feature recognition unit and a feature width measurement unit.

6. The laser etching manufacturing method for metal bonding interface interlocking texture based on machine vision according to claim 1 is characterized in that: The laser generator includes a continuous laser, a nanosecond laser, a picosecond laser or a femtosecond laser.

7. The method for laser etching of metal bonding interface interlocking texture based on machine vision according to claim 6, characterized in that: The materials of the workpieces to be processed include stainless steel, carbon steel, alloy steel, aluminum alloy, magnesium alloy, and titanium alloy.

8. The method for laser etching of metal bonding interface interlocking texture based on machine vision according to claim 6, characterized in that: The laser etching process includes pit etching and groove etching.

9. The laser etching manufacturing method for metal bonding interface interlocking texture based on machine vision according to claim 1 is characterized in that: The step S40 comprises: Performing grayscale processing on the surface texture image; Using a median filtering method to perform denoising on the surface texture image after grayscale processing; The threshold segmentation method is used to perform image segmentation on the surface texture image after denoising to separate the target features from the background.

10. The method for laser etching of metal bonding interface interlocking texture based on machine vision according to claim 1, characterized in that: The step S50 comprises: Perform texture edge detection; Marking of connected domains; The average opening diameter of ten locations within the selected area was measured as the recess opening width.

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