Fireproof blanket automatic gluing process based on visual identification

Abstract

The invention relates to a fireproof blanket automatic gluing process based on visual identification, which comprises the following steps: performing visual scanning on a part overall frame and each gap state of a fireproof blanket by using Simo Vsion software to generate a point cloud picture, transmitting the scanned features to a computer terminal as a template, and for the deviation of the part overall, performing visual identification on the deviation of the part overall frame and the fireproof blanket; the whole coordinate of the part is compared with the coordinate of the template, the deviation is automatically compensated, a compiled automatic gluing program is uploaded to the PLC control device, the part is loaded into the shape frame tool, and the gluing can be carried out by directly calling the corresponding program. In short, the device has the advantages of being simple in structure, convenient to operate, high in installation efficiency, short in fireproof blanket bonding period and stable in bonding quality.

Description

Technical Field

[0001] The present invention belongs to the technical field of aeroengines, and particularly relates to an automatic gluing process for a fire blanket based on visual recognition. Background Art

[0002] The thrust reverser nacelle device is an important part of an aeroengine. The fireproof performance of the thrust reverser nacelle device is a decisive requirement for its installation. Its fireproof performance is directly affected by the bonding quality of the fire blanket. However, the current bonding difficulties of the fire blanket mainly lie in the following points: First, the installation and fixation method is mainly manual installation, and there are certain deviations in the installation positions of each part of the fire blanket. Its material is manually cut, resulting in inconsistent widths of the gaps in each area and uneven edges of the fire blanket. Second, the structure of the fire blanket itself is very complex, with large size, flexible and curved surface, so the conventional automatic gluing process is not applicable to it. Finally, the bonding process of the fire blanket of the thrust reverser nacelle device is all manual gluing. Although manual gluing can meet the gluing requirements on the complex surface of the fire blanket, it has the disadvantages of long bonding cycle, unstable bonding quality, poor appearance quality, and the glue used is harmful to the human body. Therefore, there is an urgent need for an automatic gluing process for a fire blanket based on visual recognition to solve the above existing problems. Summary of the Invention

[0003] In view of this, the present invention proposes an automatic gluing process for a fire blanket based on visual recognition, which is applied to the technical field of aeroengines and can solve the technical problems of low efficiency of existing manual installation, long bonding cycle of the fire blanket, and low bonding quality while ensuring the normal use of the brushless DC motor.

[0004] In order to achieve the above technical purpose, the specific technical solution adopted by the present invention is as follows:

[0005] An automatic gluing process for a fire blanket based on visual recognition includes the following steps:

[0006] S1. Use SimoVsion software for visual recognition to locate the positions of the part and the fire blanket, and identify the width, length and state of each gap of the fire blanket;

[0007] S2. Use a PLC control device to control the glue output and gluing trajectory of the gluing robot;

[0008] In step S1, use SimoVsion software to perform visual scanning on the overall frame of the part and the states of each gap of the fire blanket to generate a point cloud map. The scanned features are transmitted to the computer terminal as a template. For the offset of the overall part, the camera will compare the coordinates of the overall part with the coordinates of the template and automatically compensate for the deviation;

[0009] In step S2, the programmed automatic gluing procedure is uploaded to the PLC control device. The parts are loaded into the jig fixture, and the corresponding program can be directly called to perform gluing.

[0010] Furthermore, in step S2, according to the different states of the gap, manual debugging is carried out to determine the gluing posture, the glue output speed, and the running speed of the gluing robot.

[0011] Furthermore, in step S2, for the long and uneven edge gap, the muzzle is raised for gluing, the glue output speed is 3 g / s, and the running speed is 70%, to prevent the muzzle from scratching the fireproof blanket.

[0012] Furthermore, in step S2, for the gap at the connection between the edge of the fireproof blanket and the Hi-Lok bolt, re-gluing is carried out, and then manual smoothing is performed. The gluing robot outputs glue at the maximum glue output of 5 g / s and performs coating at a running speed of 70% to ensure the appearance quality and that the glue layer completely covers the Hi-Lok bolt.

[0013] Furthermore, in step S2, the gluing robot outputs glue at the maximum glue output of 5 g / s and performs coating at a running speed of 70%. After manual smoothing, the glue layer completely covers the Hi-Lok bolt without any glue missing or leaking areas.

[0014] Furthermore, in step S2, for gluing at the buckle position, a capping fixture is used to fix the shape of the corresponding buckle when the gluing is completed.

[0015] Furthermore, in step S2, during the gluing process of the buckle, the gluing robot outputs glue at a rate of 3.5 g / s, pauses for 1.2 s at a fixed point for glue output, and the capping time is the time when the glue surface is slightly cured and not sticky after gluing.

[0016] Furthermore, in step S2, for the large-sized and uneven-width gap, the glue output parameters of gaps with different widths are collected as templates. The width is identified by the vision recognition system, and the glue output is automatically changed through the PLC control device for gluing.

[0017] Furthermore, in step S2, the vision recognition system automatically skips the gaps that cannot be filled with the maximum glue output of 5 g / s, and manual glue filling is carried out later. For the raised transition area generated at one end of the gap where the glue output is changed and manually re-coated, no further treatment is required.

[0018] Furthermore, the jig fixture includes a base and a fixed clamp provided on the base. Two support columns are provided above the base. The parts are placed vertically on the base, and the bottom of the parts is fixed by the fixed clamp. The two support columns are respectively located on both sides of the parts, and fasteners for squeezing from the side of the parts are respectively provided on the two support columns, so as to fix the upper part of the parts through the support columns and the fasteners.

[0019] Adopting the above technical solution, the present invention can also bring the following beneficial effects:

[0020] 1. The present invention mentions an automatic glue - applying process for fire - proof blankets based on visual recognition, which can automatically recognize gaps that are long and irregular in width, and can automatically recognize parts with complex surfaces and curved surface structures, filling the gap in the automatic bonding process of fire - proof blankets and solving the problems of long bonding cycle and low bonding quality of fire - proof blankets.

[0021] 2. The present invention mentions an automatic glue - applying process for fire - proof blankets based on visual recognition. It uses Simo Vsion software for visual recognition, locates the positions of parts and fire - proof blankets, and recognizes the width and length states of each gap of the fire - proof blanket. It uses a PLC control device to control the glue output and glue - applying trajectory of the glue - applying robot. The structure is simple and the operation is convenient, suitable for large - scale promotion. Automatic glue - applying only requires remote operation by the operator, and employees do not need to directly contact the glue, which is beneficial to the occupational health of employees and promotes the extended application of related technologies. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can be obtained based on these drawings.

[0023] Figure 1 It is a schematic structural diagram of a part in a specific embodiment of the present invention;

[0024] Figure 2 It is a schematic structural diagram of a jig tooling in a specific embodiment of the present invention;

[0025] Figure 3 It is a schematic structural diagram of a cap tooling in a specific embodiment of the present invention;

[0026] 1. Part; 2. Jig tooling; 3. Cap tooling; 21. Base; 22. Fixed fixture; 23. Support column; 24. Fastener. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0027] The embodiments of the present invention will be described in detail below with reference to the drawings.

[0028] The following describes the embodiments of the present invention through specific examples. Those skilled in the art can easily understand the other advantages and effects of the present invention from the content disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all embodiments. The present invention can also be implemented or applied through other different specific embodiments. Various details in this specification can also be modified or changed based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that, without conflict, the following embodiments and the features in the embodiments can be combined with each other. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative work belong to the scope of protection of the present invention.

[0029] It should be noted that the following describes various aspects of the embodiments within the scope of the appended claims. It should be apparent that the aspects described herein can be embodied in a wide variety of forms, and any specific structure and / or function described herein is merely illustrative. Based on the present invention, those skilled in the art should understand that one aspect described herein can be implemented independently of any other aspect, and two or more of these aspects can be combined in various ways. For example, any number of aspects described herein can be used to implement a device and / or practice a method. Additionally, this device and / or method can be implemented using other structures and / or functions in addition to one or more of the aspects described herein.

[0030] It should also be noted that the drawings provided in the following embodiments only illustrate the basic concept of the present invention schematically. The drawings only show the components related to the present invention, rather than being drawn according to the number, shape, and size of the components in actual implementation. The type, quantity, and ratio of each component in actual implementation can be arbitrarily changed, and the component layout type may also be more complex.

[0031] In addition, in the following description, specific details are provided to facilitate a thorough understanding of the examples. However, those skilled in the art will understand that the described aspects can be practiced without these specific details.

[0032] In one embodiment of the present invention, as Figure 1 , an automatic glue coating process for a fire blanket based on visual recognition includes the following steps:

[0033] S1. Use Simo Vsion software to perform visual scanning on the overall frame of part 1 and the gap states of the fire blanket to generate a point cloud map. The scanned features are transmitted to the computer terminal as a template. For the overall offset of part 1, the camera will compare the coordinates of the overall part 1 with the coordinates of the template and automatically compensate for the deviation;

[0034] S2. Upload the automatically programmed glue application program to the PLC control device, load part 1 into the jig tooling 2, and directly call the corresponding program to apply glue.

[0035] The jig tooling 2 includes a base 21 and a fixed fixture 22 provided on the base 21. There are two support columns 23 arranged above the base 21. Part 1 is placed vertically on the base 21, and the bottom of part 1 is fixed by the fixed fixture 22. The two support columns 23 are respectively located on both sides of part 1, and fasteners 24 for extruding from the side of part 1 are respectively provided on the two support columns 23, so as to fix the upper part of part 1 through the support columns 23 and the fasteners 24. The specific structures of the fixed fixture 22 and the fasteners 24 adopt existing components and will not be introduced in detail here.

[0036] According to the different states of the gap, manually debug to determine the glue application posture, the glue output speed, and the running speed of the glue application robot. For the long and uneven edge gap, raise the muzzle to apply glue, with a glue output speed of 3 g / s and a running speed of 70%, to prevent the muzzle from scratching the fireproof blanket.

[0037] For the gap at the connection between the edge of the fireproof blanket and the Hi-Lok bolt, reapply glue and then manually smooth it. The glue application robot applies glue with a maximum glue output of 5 g / s and a running speed of 70% for coating, ensuring the appearance quality and that the glue layer completely covers the Hi-Lok bolt. The glue application robot applies glue with a maximum glue output of 5 g / s and a running speed of 70% for coating. After manual smoothing, the glue layer completely covers the Hi-Lok bolt without any glue shortage or leakage area.

[0038] For applying glue to the buckle position, use the cap tooling 3 to fix the shape of the corresponding buckle when the glue application is completed. During the glue application process of the buckle, the glue application robot applies glue with a glue output of 3.5 g / s, pauses at a fixed point for 1.2 s to apply glue, and the capping time is the time when the glue surface is slightly cured and not sticky after the glue application.

[0039] For large-sized and uneven-width gaps, collect the glue application parameters of gaps with different widths as templates, use the vision recognition system to identify their widths, and automatically change the glue output through the PLC control device to apply glue. The vision recognition system automatically skips the gaps that cannot be filled with a maximum glue output of 5 g / s, and then manually fill the glue at the back. For the raised transition area generated at one end of the gap where the glue output is changed and manually filled, no further treatment is required.

[0040] In summary, the present invention has the advantages of simple structure, convenient operation, high installation efficiency, short bonding cycle of the fireproof blanket, and stable bonding quality.

[0041] The above are only specific embodiments of the present invention, but the protection scope of the present invention is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed by the present invention should be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.

Claims

1. An automatic glue - coating process for fire - proof blankets based on visual recognition, characterized in that, The steps are as follows: S1. Use SimoVsion software for visual recognition to locate the positions of the part (1) and the fireproof blanket, and identify the width, length, and state of each gap of the fireproof blanket; S2. Use a PLC control device to control the glue output and glue application trajectory of the glue - applying robot; In step S1, use SimoVsion software to perform visual scanning on the overall frame of the part (1) and the states of each gap of the fireproof blanket to generate a point - cloud map. The scanned features are transmitted to the computer terminal as a template. For the overall offset of the part (1), the camera will compare the overall coordinates of the part (1) with the coordinates of the template and automatically compensate for the deviation; In step S2, upload the programmed automatic glue - applying program to the PLC control device, load the part (1) into the jig tooling (2), and directly call the corresponding program to perform glue application; 2. The automatic glue coating process of a fire blanket based on visual recognition according to claim 1, characterized in that: In step S2, according to the different states of the gaps, perform manual debugging to determine the glue - applying posture, glue output speed, and running speed of the glue - applying robot; 3. The automatic glue coating process for a fire blanket based on visual recognition according to claim 2, characterized in that: In step S2, for the long and uneven edge gaps, raise the muzzle of the gun for glue application, with a glue output speed of 3 g / s and a running speed of 70%, to prevent the muzzle from scratching the fireproof blanket; 4. The automatic gluing process of a fire blanket based on visual recognition according to claim 3, characterized in that: In step S2, for the gap at the connection between the edge of the fireproof blanket and the Hi - Lock bolt, perform re - glue application, and then manually level it. The glue - applying robot applies glue with a maximum glue output of 5 g / s and a running speed of 70% for coating to ensure the appearance quality and that the glue layer completely covers the Hi - Lock bolt; 5. The automatic gluing process of a fire blanket based on visual recognition according to claim 4, characterized in that: In step S2, the glue - applying robot applies glue with a maximum glue output of 5 g / s and a running speed of 70% for coating. After manual leveling, the glue layer completely covers the Hi - Lock bolt without any glue - missing or glue - leaking areas; 6. The automatic gluing process of a fire blanket based on visual recognition according to claim 1, characterized in that: In step S2, for glue application at the buckle position, use a capping tooling (3) to fix the outer shape of the corresponding buckle when the glue application is completed; 7. The automatic glue - coating process of a fire - proof blanket based on visual recognition according to claim 6, wherein: In step S2, during the glue - applying process for the buckle, the glue - applying robot uses a glue output of 3.5 g / s, pauses at the fixed point for 1.2 s for glue output. The capping time is the time when the glue surface is slightly cured and not sticky after glue application; 8. The automatic glue coating process of a fire blanket based on visual recognition according to claim 1, characterized in that: In step S2, for large - sized and uneven - width gaps, collect the glue - output parameters of gaps with different widths as a template, use the visual recognition system to identify their widths, and automatically change the glue output through the PLC control device for glue application; 9. The automatic glue coating process of a fire blanket based on visual recognition according to claim 8, wherein: In step S2, the visual recognition system automatically skips the gaps that cannot be filled with a maximum glue output of 5 g / s, and then performs manual glue patching. For the raised transition area generated at one end of the gap where the glue output is changed and manually re - coated, no further treatment is required.

10. The automatic glue coating process for a fire blanket based on visual recognition according to claim 9, wherein: In the step S2, the frame tooling (2) includes a base (21) and a fixing fixture (22) arranged on the base (21). Above the base (21), two support columns (23) are provided. The part (1) is placed vertically on the base (21), and the bottom of the part (1) is fixed by the fixing fixture (22). The two support columns (23) are respectively located on both sides of the part (1), and fasteners (24) for squeezing from the side of the part (1) are respectively arranged on the two support columns (23), so as to fix the upper part of the part (1) through the support columns (23) and the fasteners (24).

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