A large-size aluminum alloy surface polishing control method and system

Abstract

The present invention discloses a surface polishing control method and system for large-size aluminum alloy parts, and relates to the technical field of metal surface polishing control, comprising: matching surface point cloud images in a surface point cloud image library with environmental information in an environmental information library one by one, obtaining registration point cloud coordinate information corresponding to environmental impact point cloud data, determining size information of the aluminum alloy parts to be polished, obtaining polishing influence parameters matching a surface texture feature set of each image of a region to be polished based on the size information of the aluminum alloy parts to be polished, determining preset polishing information according to the polishing influence parameters and the surface texture feature set of each image of the region to be polished, and realizing precise control of the surface polishing of large-size aluminum alloy parts, so that the polishing system can obtain standard polishing information and polish the large-size aluminum alloy parts when there are parts with complex geometric shapes or large curvature changes in the large-size aluminum alloy parts.

Description

Technical Field

[0001] The invention relates to the technical field of metal surface polishing control, and in particular to a surface polishing control method and system for a large-size aluminum alloy part. Background Art

[0002] As the performance requirements for aluminum alloy parts increase, the requirements for their processing accuracy and surface quality are becoming more and more stringent. Among them, polishing, as the last process in the manufacture of aluminum alloy parts, directly determines the final surface accuracy and surface quality of aluminum alloy parts. The control method and system for surface polishing of large-size aluminum alloy parts are mainly used in high-precision fields such as aerospace and automotive industries to ensure that their surface quality meets high requirements. Through precise process parameter settings, advanced polishing equipment, and real-time monitoring and feedback systems, the polishing pressure, speed, and polishing agent use are effectively controlled to ensure the overall surface finish and uniformity and avoid surface damage and deformation. This system can improve production efficiency and product quality and meet the high-end application needs of complex aluminum alloy parts.

[0003] The existing surface polishing control method for large-size aluminum alloy parts is difficult to obtain standard polishing information based on the collected information because the polishing surface of large-size aluminum alloy parts is large and there may be parts with complex geometric shapes or large curvature changes. At the same time, when the polishing system is collecting information, the surrounding environment of the large-size aluminum alloy parts will affect it, which will not only affect the polishing effect, but also increase the polishing cost and reduce the efficiency. Therefore, it is necessary to provide a surface polishing control method and system for large-size aluminum alloy parts to solve the above-mentioned problems. Summary of the invention

[0004] In order to solve the above-mentioned technical problems, a surface polishing control method and system for large-size aluminum alloy parts are provided. The technical solution solves the existing surface polishing control method for large-size aluminum alloy parts proposed in the above-mentioned background technology. Since the polishing surface of large-size aluminum alloy parts is large and there may be parts with complex geometric shapes or large curvature changes, it is difficult to obtain standard polishing information based on the collected information. At the same time, when the polishing system is collecting information, the surrounding environment of the large-size aluminum alloy parts will affect it, which will not only affect the polishing effect, but also increase the polishing cost and reduce the efficiency.

[0005] In order to achieve the above purpose, the technical solution adopted by the present invention is:

[0006] A method for controlling the surface polishing of a large-size aluminum alloy part, comprising:

[0007] Step 1: Collect the initial surface image of the aluminum alloy part to be cleaned, establish an initial surface image library, and determine the cleaning information of each aluminum alloy part to be cleaned, clean the surface of each aluminum alloy part to be cleaned, and obtain the aluminum alloy part to be polished, wherein the cleaning information includes the cleaning agent usage parameters and the cleaning water pressure parameters;

[0008] Step 2: determining the polishing requirement information of the aluminum alloy surface based on the aluminum alloy to be polished, and obtaining the polishing requirement information and polishing tool type information of the aluminum alloy surface to be polished, wherein the polishing requirement information includes the aluminum alloy surface quality index and the polishing film quality index, and the polishing tool type information includes the polishing tool type information and the polishing tool size information;

[0009] Step 3: obtaining an original image of each aluminum alloy part to be polished, and dividing the original image into regions based on the polishing tool type information, obtaining an image of the region to be polished, and establishing an image library of the region to be polished;

[0010] Among them, the method for establishing the image library of the area to be polished is:

[0011] Based on the polishing tool type information, determine the polishing tool size information and the polishing tool quantity information;

[0012] A square blank window is set with the size of the largest polishing tool as the maximum size of the area division, and the area division window is constructed;

[0013] Performing region division on each original image of the aluminum alloy part to be polished based on the region division window to obtain a region image to be polished;

[0014] Obtaining the acquisition time sequence of the images of the area to be polished, and sorting the images of the area to be polished according to the acquisition time sequence to obtain an image library of the area to be polished;

[0015] Step 4: Acquire surface texture feature information of the aluminum alloy surface corresponding to each image of the area to be polished in the image library of the area to be polished, and establish a surface texture feature set for each image of the area to be polished;

[0016] Step 5: Obtain polishing influencing parameters that match the surface texture feature set of each image of the area to be polished, and determine preset polishing information corresponding to each image of the area to be polished based on the surface texture feature set of each image of the area to be polished, wherein the preset polishing information includes preset polishing tool usage parameters, preset polishing speed, preset polishing time, and preset polishing pressure;

[0017] Step 6: Based on the image of each area to be polished and the original image of the aluminum alloy part to be polished, determine the polishing position information, and polish the aluminum alloy part to be polished based on the preset polishing information and the polishing tool type information to obtain the initially polished aluminum alloy part;

[0018] Step 7: real-time acquisition of real-time images of the primary polished aluminum alloy part, and acquisition of adjacent area images of the polished area and the unpolished area, extraction of surface adjacent texture features, and establishment of a surface adjacent texture feature set;

[0019] Step eight, based on the surface adjacent texture feature set and the corresponding polishing influencing parameters, determine the adjacent area polishing information corresponding to each area to be polished image, and polish the surface position of the primary polishing aluminum alloy part corresponding to the adjacent area image.

[0020] In an optional embodiment, determining the cleaning information of each aluminum alloy part to be cleaned, cleaning the surface of each aluminum alloy part to be cleaned, and obtaining the aluminum alloy part to be polished specifically includes:

[0021] Traversing all the initial surface images in the initial surface image library, extracting the initial surface images collected from the same aluminum alloy part to be cleaned, and obtaining a corresponding initial surface image set;

[0022] Acquiring an acquisition sequence when acquiring an initial surface image of the aluminum alloy part to be cleaned;

[0023] Performing image stitching on the initial surface images in the initial surface image set according to the acquisition sequence to obtain an initial surface stitching image;

[0024] Setting first preset parameters, and constructing a first cutting template according to the first preset parameters;

[0025] Crop the initial surface stitching image according to the first cropping template to obtain an initial cropped image;

[0026] Perform image processing on each initial cropped image, obtain the pollution degree index of each initial cropped image, and establish a pollution degree index matrix;

[0027] Based on the contamination degree index matrix, contamination characteristic information of the aluminum alloy part to be cleaned in the initial surface image is obtained, and the aluminum alloy part to be cleaned is cleaned.

[0028] In an optional embodiment, determining the polishing requirement information of the aluminum alloy part surface based on the aluminum alloy part to be polished, and obtaining the polishing requirement information and polishing tool type information of the aluminum alloy surface to be polished specifically includes:

[0029] Placing the aluminum alloy part to be polished in a fixture, collecting high-definition surface images of all to-be-polished surfaces of the aluminum alloy part to be polished, and images of adjacent structures of the aluminum alloy part to be polished close to the to-be-polished surfaces, and establishing a surface high-definition image library and an adjacent structure image library;

[0030] Performing image preprocessing on the surface high-definition images and the adjacent structure images in the surface high-definition image library and the adjacent structure image library to obtain the surface high-definition standard image library and the adjacent structure standard image library;

[0031] Divide the images in the surface high-definition standard image library to obtain the surface high-definition segmented images;

[0032] Perform grayscale processing on each surface high-definition segmented image to obtain a surface segmented grayscale image library, and determine the average smoothness index of the aluminum alloy part to be polished;

[0033] A low-pass filter is used to filter each surface high-definition segmented image to obtain the average roughness index of the aluminum alloy part to be polished;

[0034] Taking the average of the smoothness average index and the roughness average index as the surface quality parameter of the aluminum alloy part to be polished;

[0035] The surface polishing requirement information and polishing tool type information of aluminum alloy parts are determined based on surface quality parameters and adjacent structure image library.

[0036] In an optional embodiment, the step of acquiring the surface texture feature information of the aluminum alloy surface corresponding to each image of the area to be polished in the image library of the area to be polished and establishing a surface texture feature set of each image of the area to be polished specifically includes:

[0037] Performing image standardization processing on each image of the area to be polished in the image library of the area to be polished to obtain a standard image of the area to be polished;

[0038] Based on the gray level co-occurrence matrix, the co-occurrence matrix of the gray level pairs of pixels in the standard image of each area to be polished is obtained, and the contrast parameter, energy index, correlation parameter and uniformity index measuring the gray level pairs are extracted;

[0039] The contrast parameter, energy index, correlation parameter and uniformity index of the standard image of each area to be polished are recorded respectively to obtain surface texture feature information, and a surface texture feature set of each image of the area to be polished is established.

[0040] In an optional embodiment, the step of obtaining a polishing influencing parameter that matches a surface texture feature set of each image of the area to be polished, and determining preset polishing information corresponding to each image of the area to be polished based on the surface texture feature set of each image of the area to be polished, specifically includes:

[0041] The aluminum alloy workpiece to be polished is placed horizontally on the polishing pad, and surface point cloud images of the aluminum alloy workpiece to be polished at different angles are acquired by using a three-dimensional scanner to establish a surface point cloud image library;

[0042] Obtain environmental information of surface point cloud images at different angles and establish an environmental information database;

[0043] Match the surface point cloud images in the surface point cloud image library with the environmental information in the environmental information library one by one to obtain an environmental impact point cloud database;

[0044] Acquire registration point cloud coordinate information corresponding to the environmental impact point cloud data;

[0045] Determine the size information of the aluminum alloy part to be polished, wherein the size information includes the overall size, weight, wall thickness, parallelism and verticality of the aluminum alloy part to be polished;

[0046] Obtaining polishing influencing parameters matching a surface texture feature set of each to-be-polished area image based on size information of the to-be-polished aluminum alloy part;

[0047] The preset polishing information is determined according to the polishing influencing parameters and the surface texture feature set of each to-be-polished area image.

[0048] In an optional embodiment, the real-time acquisition of a real-time image of the primary polished aluminum alloy part, and obtaining adjacent area images of the polished area and the unpolished area, extracting surface adjacent texture features, and establishing a surface adjacent texture feature set specifically include:

[0049] Based on the regional segmentation technology, the real-time image of the primary polished aluminum alloy part is segmented to obtain the polished area image and the unpolished area image;

[0050] Based on the polished area image and the unpolished area image, the adjacent area images of the polished area and the unpolished area in the real-time image are segmented to obtain adjacent area images;

[0051] Texture analysis is performed on adjacent region images to extract surface adjacent texture features and establish a surface adjacent texture feature set.

[0052] In an optional embodiment, the step of determining the polishing information of the adjacent region corresponding to each image of the region to be polished based on the surface adjacent texture feature set and the polishing influencing parameters corresponding thereto, and polishing the surface position of the primary polished aluminum alloy part corresponding to the adjacent region image, specifically includes:

[0053] Obtaining a polished area image of a polished aluminum alloy part, and obtaining its corresponding historical surface texture feature set and historical polishing influencing parameters;

[0054] Obtaining historical polishing information corresponding to the polishing area image of the polished aluminum alloy part;

[0055] Integrate the historical surface texture feature set, historical polishing influencing parameters and historical polishing information to obtain integrated data;

[0056] Extracting correlation data from the integrated data, and inputting the correlation data into the mechanical model for training to obtain a polishing information prediction model;

[0057] Inputting the surface adjacent texture feature set of each to-be-polished area image and the corresponding polishing influencing parameters into the polishing information prediction model to obtain the adjacent area polishing information;

[0058] The surface position of the primary polished aluminum alloy part corresponding to the adjacent area image is polished based on the adjacent area polishing information.

[0059] Furthermore, a large-size aluminum alloy surface polishing control system is proposed, which is used to implement any of the above control methods, including:

[0060] A main control module, the main control module is used to determine the surface polishing requirement information of the aluminum alloy part based on the aluminum alloy part to be polished, and obtain the polishing requirement information and polishing tool type information of the aluminum alloy surface to be polished, obtain the surface texture feature information of the aluminum alloy surface corresponding to each area to be polished image in the area to be polished image library, obtain the polishing influence parameter matching the surface texture feature set of each area to be polished image, determine the preset polishing information corresponding to each area to be polished image based on the surface texture feature set of each area to be polished image, determine the polishing position information based on each area to be polished image and the original image of the aluminum alloy part to be polished, determine the adjacent area polishing information corresponding to each area to be polished image based on the surface adjacent texture feature set and the corresponding polishing influence parameter, determine the cleaning information of each aluminum alloy part to be cleaned, clean the surface of each aluminum alloy part to be cleaned, obtain the aluminum alloy part to be polished, polish the aluminum alloy part to be polished based on the preset polishing information and the polishing tool type information, obtain the initially polished aluminum alloy part, and polish the surface position of the initially polished aluminum alloy part corresponding to the adjacent area image;

[0061] An acquisition module, wherein the acquisition module is used to acquire an initial surface image of the aluminum alloy part to be cleaned, establish an initial surface image library, obtain an original image of each aluminum alloy part to be polished, acquire a real-time image of the aluminum alloy part being initially polished in real time, and acquire adjacent area images of the polished area and the unpolished area, extract surface adjacent texture features, and establish a surface adjacent texture feature set;

[0062] A transmission module, which is used to connect the main control module, the acquisition module and the display module, and transmit the data exchanged between the modules;

[0063] The display module is used to display the processing results of the main control module, the data collected by the collection module, and the information transmitted and received by the transmission module.

[0064] In an optional embodiment, the main control module includes:

[0065] A data acquisition unit, the data acquisition unit is used to determine the surface polishing requirement information of the aluminum alloy part based on the aluminum alloy part to be polished, and obtain the polishing requirement information and polishing tool type information of the aluminum alloy surface to be polished, obtain the surface texture feature information of the aluminum alloy surface corresponding to each image of the area to be polished in the image library of the area to be polished, and obtain the polishing influencing parameters matching the surface texture feature set of each image of the area to be polished;

[0066] A data processing unit, the data processing unit is used to determine the preset polishing information corresponding to each image of the area to be polished based on the surface texture feature set of each image of the area to be polished, determine the polishing position information based on each image of the area to be polished and the original image of the aluminum alloy part to be polished, and determine the polishing information of the adjacent area corresponding to each image of the area to be polished based on the surface adjacent texture feature set and the polishing influence parameters corresponding thereto;

[0067] A control unit is used to determine the cleaning information of each aluminum alloy part to be cleaned, clean the surface of each aluminum alloy part to be cleaned, obtain the aluminum alloy part to be polished, polish the aluminum alloy part to be polished based on preset polishing information and polishing tool type information, obtain the initially polished aluminum alloy part, and polish the surface position of the initially polished aluminum alloy part corresponding to the adjacent area image.

[0068] In an optional embodiment, the acquisition module includes:

[0069] A first acquisition unit, wherein the first acquisition unit is used to acquire an initial surface image of the aluminum alloy part to be cleaned, establish an initial surface image library, and obtain an original image of each aluminum alloy part to be polished;

[0070] The second acquisition unit is used to acquire real-time images of the primary polished aluminum alloy part, obtain adjacent area images of the polished area and the unpolished area, extract surface adjacent texture features, and establish a surface adjacent texture feature set.

[0071] Compared with the prior art, the present invention has the following beneficial effects:

[0072] The present invention proposes a surface polishing control method and system for large-size aluminum alloy parts. The method comprises the following steps: placing the aluminum alloy part to be polished horizontally on a polishing pad, using a three-dimensional scanner to obtain surface point cloud images of the aluminum alloy part to be polished at different angles, establishing a surface point cloud image library, obtaining environmental information of the surface point cloud images at different angles, establishing an environmental information library, matching the surface point cloud images in the surface point cloud image library with the environmental information in the environmental information library one by one, obtaining an environmental impact point cloud database, obtaining registration point cloud coordinate information corresponding to the environmental impact point cloud data, determining the size information of the aluminum alloy part to be polished, obtaining polishing influence parameters matching the surface texture feature set of each image of the area to be polished based on the size information of the aluminum alloy part to be polished, determining preset polishing information based on the polishing influence parameters and the surface texture feature set of each image of the area to be polished, realizing precise control of the surface polishing of the large-size aluminum alloy part, enabling the polishing system to obtain standard polishing information when there are parts of the large-size aluminum alloy part with complex geometric shapes or large curvature changes, and polishing the large-size aluminum alloy part. Meanwhile, the polishing influence parameters can also prevent the polishing system from being affected by the surrounding environment when collecting information and performing polishing, thereby improving the polishing effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] Figure 1 This is a flow chart of a surface polishing control method for a large-size aluminum alloy part proposed by the present invention;

[0074] Figure 2 This is a flow chart for obtaining the aluminum alloy part to be polished in the present invention;

[0075] Figure 3 A flowchart for obtaining polishing requirement information and polishing tool type information in the present invention;

[0076] Figure 4 This is a system framework diagram of a large-size aluminum alloy part surface polishing control system proposed in the present invention. DETAILED DESCRIPTION

[0077] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art may think of other obvious variations.

[0078] Reference Figure 1 - Figure 4 As shown, a surface polishing control method for a large-size aluminum alloy part comprises:

[0079] Step 1: Collect the initial surface image of the aluminum alloy part to be cleaned, establish an initial surface image library, and determine the cleaning information of each aluminum alloy part to be cleaned, clean the surface of each aluminum alloy part to be cleaned, and obtain the aluminum alloy part to be polished, wherein the cleaning information includes the cleaning agent usage parameters and the cleaning water pressure parameters;

[0080] Step 2: determining the surface polishing requirement information of the aluminum alloy part based on the aluminum alloy part to be polished, and obtaining the polishing requirement information and polishing tool type information of the aluminum alloy surface to be polished, wherein the polishing requirement information includes the aluminum alloy surface quality index and the polishing film quality index, and the polishing tool type information includes the polishing tool type information and the polishing tool size information;

[0081] Step 3: obtaining an original image of each aluminum alloy part to be polished, and dividing the original image into regions based on the polishing tool type information, obtaining an image of the region to be polished, and establishing an image library of the region to be polished;

[0082] Among them, the method for establishing the image library of the area to be polished is:

[0083] Based on the polishing tool type information, determine the polishing tool size information and the polishing tool quantity information;

[0084] A square blank window is set with the size of the largest polishing tool as the maximum size of the area division, and the area division window is constructed;

[0085] Performing region division on each original image of the aluminum alloy part to be polished based on the region division window to obtain a region image to be polished;

[0086] Obtaining the acquisition time sequence of the images of the area to be polished, and sorting the images of the area to be polished according to the acquisition time sequence to obtain an image library of the area to be polished;

[0087] Step 4: Acquire surface texture feature information of the aluminum alloy surface corresponding to each image of the area to be polished in the image library of the area to be polished, and establish a surface texture feature set for each image of the area to be polished;

[0088] Step 5: Obtain polishing influencing parameters that match the surface texture feature set of each image of the area to be polished, and determine preset polishing information corresponding to each image of the area to be polished based on the surface texture feature set of each image of the area to be polished, wherein the preset polishing information includes preset polishing tool usage parameters, preset polishing speed, preset polishing time, and preset polishing pressure;

[0089] Step 6: Based on the image of each area to be polished and the original image of the aluminum alloy part to be polished, determine the polishing position information, and polish the aluminum alloy part to be polished based on the preset polishing information and the polishing tool type information to obtain the initially polished aluminum alloy part;

[0090] Step 7: real-time acquisition of real-time images of the primary polished aluminum alloy part, and acquisition of adjacent area images of the polished area and the unpolished area, extraction of surface adjacent texture features, and establishment of a surface adjacent texture feature set;

[0091] Step eight, based on the surface adjacent texture feature set and the corresponding polishing influencing parameters, determine the adjacent area polishing information corresponding to each to-be-polished area image, and polish the surface position of the primary polishing aluminum alloy part corresponding to the adjacent area image.

[0092] Further, the cleaning information of each aluminum alloy part to be cleaned is determined, and the surface of each aluminum alloy part to be cleaned is cleaned to obtain the aluminum alloy part to be polished, which specifically includes:

[0093] Traversing all the initial surface images in the initial surface image library, extracting the initial surface images collected from the same aluminum alloy part to be cleaned, and obtaining a corresponding initial surface image set;

[0094] Acquiring an acquisition sequence when acquiring an initial surface image of the aluminum alloy part to be cleaned;

[0095] Performing image stitching on the initial surface images in the initial surface image set according to the acquisition sequence to obtain an initial surface stitching image;

[0096] Setting first preset parameters, and constructing a first cutting template according to the first preset parameters;

[0097] Crop the initial surface stitching image according to the first cropping template to obtain an initial cropped image;

[0098] Perform image processing on each initial cropped image, obtain the pollution degree index of each initial cropped image, and establish a pollution degree index matrix;

[0099] Based on the contamination degree index matrix, contamination characteristic information of the aluminum alloy part to be cleaned in the initial surface image is obtained, and the aluminum alloy part to be cleaned is cleaned.

[0100] Specifically, an acquisition sequence is obtained when acquiring the initial surface image of the aluminum alloy part to be cleaned. The acquisition sequence is the acquisition order when the acquisition module acquires the initial surface image of the aluminum alloy part to be cleaned. For example, the large-sized aluminum alloy part is a rectangular structure. During acquisition, if a high-resolution image needs to be acquired, it is difficult for the acquisition device to ensure that the texture features of the surface of the large-sized aluminum alloy part are presented in the image when acquiring the overall image of the large-sized aluminum alloy part. The first preset parameter is determined by the size of the initial surface spliced ​​image and the size of the initial surface image in the initial surface image set. For example, if the size value of the initial surface image is a*b, the value of the first preset parameter is 1.2a*1.2*b. At the same time, if the first cropping template constructed by the first preset parameter cannot satisfy the value of the first preset parameter of 1.2a*1.2*b during cropping, the remaining initial surface spliced ​​image is equally divided at a random size to obtain a number of initial cropped images. The pollution degree index matrix is ​​used to represent the pollution degree of different areas on the surface of the aluminum alloy part to be cleaned. The cleaning information is determined according to the pollution degree. The cleaning information includes detergent usage parameters and cleaning water pressure parameters.

[0101] The specific steps of performing image stitching on the initial surface images in the initial surface image set according to the acquisition sequence to obtain the initial surface stitching image are as follows:

[0102] S100, extracting feature points from each initial surface image, and matching these feature points to find out the corresponding relationship between them;

[0103] S101, estimating the perspective transformation (such as affine transformation or perspective transformation) between each pair of adjacent initial surface images by matching the found feature points, so as to align them to the same coordinate system;

[0104] S102, registering all the initial surface images according to the estimated transformation parameters, that is, adjusting their positions and angles so that there is no obvious overlap or gap between them after splicing;

[0105] S103, finally, performing image fusion processing to obtain an initial surface splicing image after splicing;

[0106] The relevant calculation formula for the pollution degree index is: ; In the formula, For the The percentage of polluted area in the initial surface image, For the The pollution pixel density of the initial surface image, For the The pollution color value of the initial surface image, For the The pollution degree index of the initial surface image, For the The number of pixels in the contaminated area of ​​the initial surface image, For the The total number of image pixels of the initial surface image, For the The area of ​​the contaminated region of the initial surface image, For the The initial surface image The color value of the polluted pixel, For the The initial surface image The total color value of all adjacent polluted pixels of a polluted pixel, For the The initial surface image The total number of all adjacent polluted pixels of a polluted pixel, , and are all weight coefficients.

[0107] It can be understood that image processing is performed on each initial cropped image separately to obtain the pollution degree index of each initial cropped image, and a pollution degree index matrix is ​​established. Specifically, image processing is performed on each initial cropped image, including denoising, contrast enhancement, smoothing, etc., and image segmentation is performed on the initial cropped image after image processing to separate the polluted area and the clean area in the initial cropped image. The boundary of the segmented polluted area is extracted to obtain the accurate boundary information of the polluted area. For each detected polluted area, the number of pixels surrounding the area is calculated as the area of ​​the polluted area, and the pollution color value is the grayscale value of the pixel.

[0108] Further, based on the aluminum alloy part to be polished, the polishing requirement information of the aluminum alloy part surface is determined, and the polishing requirement information and polishing tool type information of the aluminum alloy part to be polished are obtained, specifically including:

[0109] Placing the aluminum alloy part to be polished in a fixture, collecting high-definition surface images of all to-be-polished surfaces of the aluminum alloy part to be polished, and images of adjacent structures of the aluminum alloy part to be polished close to the to-be-polished surfaces, and establishing a surface high-definition image library and an adjacent structure image library;

[0110] Performing image preprocessing on the surface high-definition images and the adjacent structure images in the surface high-definition image library and the adjacent structure image library to obtain the surface high-definition standard image library and the adjacent structure standard image library;

[0111] Divide the images in the surface high-definition standard image library to obtain the surface high-definition segmented images;

[0112] Perform grayscale processing on each surface high-definition segmented image to obtain a surface segmented grayscale image library, and determine the average smoothness index of the aluminum alloy part to be polished;

[0113] A low-pass filter is used to filter each surface high-definition segmented image to obtain the average roughness index of the aluminum alloy part to be polished;

[0114] Taking the average of the smoothness average index and the roughness average index as the surface quality parameter of the aluminum alloy part to be polished;

[0115] The surface polishing requirement information and polishing tool type information of aluminum alloy parts are determined based on surface quality parameters and adjacent structure image library.

[0116] Specifically, the adjacent structure image is used to describe the structural image of the periphery of the polishing surface of the aluminum alloy part to be polished. The adjacent structure image takes into account that when the polishing surface of the aluminum alloy part to be polished is polished, its surrounding structure will have a certain impact on the polishing. According to the adjacent structure image, a suitable polishing tool type can be selected.

[0117] It can be understood that grayscale processing is performed on each surface high-definition segmented image to obtain a surface segmentation grayscale image library, and the average smoothness index of the aluminum alloy part to be polished is determined. Each surface high-definition segmented image is filtered using a low-pass filter to obtain the average roughness index of the aluminum alloy part to be polished. The average smoothness index is used to reflect the smoothness and reflective performance of the aluminum alloy part surface. The higher the average smoothness index, the smoother and brighter the surface. The average roughness index is used to reflect the microscopic undulations on the surface of the aluminum alloy part, and is used to reflect the height change of the surface of the aluminum alloy surface and quantify the roughness of the surface. The lower the value of the average roughness index, the flatter and smoother the surface. For different average smoothness indexes and average roughness indexes, the surface polishing demand information and polishing tool type information of the aluminum alloy part can be determined, that is, the best polishing quality that can be achieved on the surface of the aluminum alloy part can be determined, and the type of polishing tool selected to achieve the polishing quality can be determined;

[0118] The calculation formula of the average smoothness index is: ; In the formula, is the average smoothness index, and They are The width and height of the high-definition segmentation image of the surface, is the total number of surface high-resolution segmented images, is the grayscale image of the surface high-definition segmentation image, is the pixel coordinate;

[0119] The relevant calculation formula for the roughness average index is: ; In the formula, is the pixel value after filtering, and are the width and height of the filter, is the pixel value of the original grayscale image of the surface high-definition segmentation image, is the convolution kernel of the low-pass filter, is the gradient magnitude calculated for each pixel at position ( (x, y) ), is the average roughness index.

[0120] Further, the surface texture feature information of the aluminum alloy surface corresponding to each image of the area to be polished in the image library of the area to be polished is obtained, and a surface texture feature set of each image of the area to be polished is established, which specifically includes:

[0121] Performing image standardization processing on each image of the area to be polished in the image library of the area to be polished to obtain a standard image of the area to be polished;

[0122] Based on the gray level co-occurrence matrix, the co-occurrence matrix of the gray level pairs of pixels in the standard image of each area to be polished is obtained, and the contrast parameter, energy index, correlation parameter and uniformity index measuring the gray level pairs are extracted;

[0123] The contrast parameter, energy index, correlation parameter and uniformity index of the standard image of each area to be polished are recorded respectively to obtain surface texture feature information, and a surface texture feature set of each image of the area to be polished is established.

[0124] Further, obtaining the polishing influencing parameters matching the surface texture feature set of each image of the area to be polished, and determining the preset polishing information corresponding to each image of the area to be polished based on the surface texture feature set of each image of the area to be polished, specifically including:

[0125] The aluminum alloy workpiece to be polished is placed horizontally on the polishing pad, and surface point cloud images of the aluminum alloy workpiece to be polished at different angles are acquired by using a three-dimensional scanner to establish a surface point cloud image library;

[0126] Obtain environmental information of surface point cloud images at different angles and establish an environmental information database;

[0127] Match the surface point cloud images in the surface point cloud image library with the environmental information in the environmental information library one by one to obtain an environmental impact point cloud database;

[0128] Obtaining registration point cloud coordinate information corresponding to the environmental impact point cloud data;

[0129] Determine the size information of the aluminum alloy part to be polished, the size information includes the overall size, weight, wall thickness, parallelism and verticality of the aluminum alloy part to be polished;

[0130] Obtaining polishing influencing parameters matching a surface texture feature set of each to-be-polished area image based on size information of the to-be-polished aluminum alloy part;

[0131] The preset polishing information is determined according to the polishing influencing parameters and the surface texture feature set of each to-be-polished area image.

[0132] Specifically, surface point cloud images are a data representation method used to describe the surface shape of a three-dimensional object. It consists of a large number of discrete points, each of which has spatial coordinate information ( The points are arranged according to their position on the surface of the object;

[0133] It can be understood that the environmental information of the surface point cloud images at different angles is obtained, and the environmental information library is established. The environmental information in the surface point cloud images at different angles is other surrounding environmental information in the point cloud data except the surface points of the object, including background point cloud parameters, ambient lighting parameters, normal direction and noise point coordinates;

[0134] Among them, the relevant calculation formula for polishing influencing parameters is: ; In the formula, For the The registered point cloud coordinates, For the The background point cloud parameters corresponding to the registration point cloud coordinates, For the The ambient lighting parameters corresponding to the registered point cloud coordinates, For the The normal direction corresponding to the coordinates of the registered point cloud is For the The coordinates of the noise points corresponding to the registered point cloud coordinates, For the The average vector of all points in the neighborhood corresponding to the coordinates of the registered point cloud, For the The environmental impact parameters corresponding to the registered point cloud coordinates, for The registered point cloud coordinates correspond to the total polishing influence parameters, , , and is the weight coefficient of background point cloud parameters, ambient lighting parameters, normal direction and noise point coordinates, is the total number of registered point cloud coordinates, is a constant term;

[0135] Understandably, is the coordinate value of the registration point cloud on the three-dimensional coordinates. It is the background point cloud parameter on the three-dimensional coordinates. The polishing influence parameter is used to quantify the influence of the surrounding environment on the collected surface point cloud images when the polishing system collects surface point cloud images of large-size aluminum alloy parts at different angles during polishing, as well as some errors when the surface point cloud images collected at multiple angles are overlapped. For example, the point clouds collected at different angles may not completely match the position, angle or rotation, resulting in incomplete overlap of the corresponding points of the point cloud. Changes in environmental conditions such as lighting and reflectivity may cause inconsistent quality of collected data at different angles, affecting the overlapping results. The size information of the aluminum alloy parts to be polished is determined by the environmental influence point cloud data and the registration point cloud coordinate information, and the polishing influence parameters are further obtained, so that the polishing system is not easily affected by the structure, surface curvature, surrounding environment, etc. of large-size aluminum alloy parts during collection and polishing.

[0136] Furthermore, real-time images of the primary polished aluminum alloy parts are collected in real time, and adjacent area images of the polished area and the unpolished area are obtained, surface adjacent texture features are extracted, and a surface adjacent texture feature set is established, which specifically includes:

[0137] Based on the regional segmentation technology, the real-time image of the primary polished aluminum alloy part is segmented to obtain the polished area image and the unpolished area image;

[0138] Based on the polished area image and the unpolished area image, the adjacent area images of the polished area and the unpolished area in the real-time image are segmented to obtain adjacent area images;

[0139] Texture analysis is performed on adjacent region images to extract surface adjacent texture features and establish a surface adjacent texture feature set.

[0140] Further, based on the surface adjacent texture feature set and the polishing influencing parameters corresponding thereto, the polishing information of the adjacent region corresponding to each image of the region to be polished is determined, and the surface position of the primary polishing aluminum alloy part corresponding to the adjacent region image is polished, specifically including:

[0141] Obtaining a polished area image of a polished aluminum alloy part, and obtaining its corresponding historical surface texture feature set and historical polishing influencing parameters;

[0142] Obtaining historical polishing information corresponding to the polishing area image of the polished aluminum alloy part;

[0143] Integrate the historical surface texture feature set, historical polishing influencing parameters and historical polishing information to obtain integrated data;

[0144] Extracting correlation data from the integrated data, and inputting the correlation data into the mechanical model for training to obtain a polishing information prediction model;

[0145] Inputting the surface adjacent texture feature set of each to-be-polished area image and the corresponding polishing influencing parameters into the polishing information prediction model to obtain the adjacent area polishing information;

[0146] The surface position of the primary polished aluminum alloy part corresponding to the adjacent area image is polished based on the adjacent area polishing information.

[0147] Specifically, texture analysis is performed on adjacent area images to extract surface adjacent texture features and establish a surface adjacent texture feature set. The adjacent area image is the area where the large-sized aluminum alloy part intersects with the unpolished area after the initial polishing, and the surface adjacent texture features are the texture features of the surface of the large-sized aluminum alloy part presented in the adjacent area image. By inputting the surface adjacent texture feature set into the polishing information prediction model to obtain the adjacent area polishing information, the polishing system can more easily control and process the polishing process of each area when polishing the surface of the large-sized aluminum alloy part, ensuring that the polished area is protected to prevent unnecessary polishing when polishing the adjacent area. There may be some unpolished areas at the junction of the two areas after polishing. The polishing system can collect images of the unpolished area to extract texture features and input them into the polishing information prediction model to obtain repair polishing information to perform local polishing on the unpolished area.

[0148] Furthermore, a large-size aluminum alloy surface polishing control system is proposed, which is used to implement any of the above control methods, including:

[0149] A main control module, the main control module is used to determine the surface polishing requirement information of the aluminum alloy part based on the aluminum alloy part to be polished, and obtain the polishing requirement information and polishing tool type information of the aluminum alloy surface to be polished, obtain the surface texture feature information of the aluminum alloy surface corresponding to each area to be polished image in the area to be polished image library, obtain the polishing influence parameter matching the surface texture feature set of each area to be polished image, determine the preset polishing information corresponding to each area to be polished image based on the surface texture feature set of each area to be polished image, determine the polishing position information based on each area to be polished image and the original image of the aluminum alloy part to be polished, determine the adjacent area polishing information corresponding to each area to be polished image based on the surface adjacent texture feature set and the corresponding polishing influence parameter, determine the cleaning information of each aluminum alloy part to be cleaned, clean the surface of each aluminum alloy part to be cleaned, obtain the aluminum alloy part to be polished, polish the aluminum alloy part to be polished based on the preset polishing information and the polishing tool type information, obtain the initially polished aluminum alloy part, and polish the surface position of the initially polished aluminum alloy part corresponding to the adjacent area image;

[0150] The acquisition module is used to acquire the initial surface image of the aluminum alloy part to be cleaned, establish an initial surface image library, obtain the original image of each aluminum alloy part to be polished, acquire the real-time image of the aluminum alloy part being polished for the first time in real time, and acquire the adjacent area images of the polished area and the unpolished area, extract the surface adjacent texture features, and establish the surface adjacent texture feature set;

[0151] Transmission module: the transmission module is used to connect the main control module, the acquisition module and the display module, and transmit the data exchanged between the modules;

[0152] Display module: The display module is used to display the processing results of the main control module, the data collected by the acquisition module, and the information transmitted and received by the transmission module.

[0153] Furthermore, the main control module includes:

[0154] A data acquisition unit, the data acquisition unit is used to determine the surface polishing requirement information of the aluminum alloy part based on the aluminum alloy part to be polished, and obtain the polishing requirement information and polishing tool type information of the aluminum alloy surface to be polished, obtain the surface texture feature information of the aluminum alloy surface corresponding to each image of the area to be polished in the image library of the area to be polished, and obtain the polishing influencing parameters matching the surface texture feature set of each image of the area to be polished;

[0155] A data processing unit, the data processing unit is used to determine the preset polishing information corresponding to each image of the area to be polished based on the surface texture feature set of each image of the area to be polished, determine the polishing position information based on each image of the area to be polished and the original image of the aluminum alloy part to be polished, and determine the polishing information of the adjacent area corresponding to each image of the area to be polished based on the surface adjacent texture feature set and the polishing influencing parameters corresponding thereto;

[0156] A control unit is used to determine the cleaning information of each aluminum alloy part to be cleaned, clean the surface of each aluminum alloy part to be cleaned, obtain the aluminum alloy part to be polished, polish the aluminum alloy part to be polished based on preset polishing information and polishing tool type information, obtain the initially polished aluminum alloy part, and polish the surface position of the initially polished aluminum alloy part corresponding to the adjacent area image.

[0157] Furthermore, the acquisition module includes:

[0158] A first acquisition unit, the first acquisition unit is used to acquire an initial surface image of the aluminum alloy part to be cleaned, establish an initial surface image library, and obtain an original image of each aluminum alloy part to be polished;

[0159] The second acquisition unit is used to acquire real-time images of the primary polished aluminum alloy part, obtain adjacent area images of the polished area and the unpolished area, extract surface adjacent texture features, and establish a surface adjacent texture feature set.

[0160] In summary, the advantages of the present invention are: through the average finish index and the average roughness index, the surface polishing requirement information and polishing tool type information of the aluminum alloy part can be determined, that is, the best polishing quality that can be achieved on the surface of the aluminum alloy part can be determined, and the type of polishing tool selected to achieve the polishing quality can be determined. According to the polishing influencing parameters and the surface texture feature set of each area to be polished, the preset polishing information is determined to achieve precise control of the surface polishing of large-sized aluminum alloy parts, so that the polishing system can obtain standard polishing information when there are parts with complex geometric shapes or large curvature changes in large-sized aluminum alloy parts, and polish the large-sized aluminum alloy parts. By inputting the surface adjacent texture feature set into the polishing information prediction model to obtain the polishing information of the adjacent area, the polishing system can more easily control and process the polishing process of each area when polishing the surface of the large-sized aluminum alloy part, ensuring that the polished area is protected to prevent unnecessary polishing when polishing the adjacent area. There may be a partially unpolished area at the junction of the two areas after polishing. The polishing system can collect images of the unpolished area to extract texture features and input them into the polishing information prediction model to obtain repair polishing information to perform local polishing on the unpolished area.

[0161] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. The present invention may be subject to various changes and improvements without departing from the spirit and scope of the present invention. These changes and improvements fall within the scope of the present invention. The scope of protection claimed by the present invention is defined by the attached claims and their equivalents.

Claims

1. A method for controlling the surface polishing of a large-size aluminum alloy part, characterized in that: include: Step 1: Collect the initial surface image of the aluminum alloy part to be cleaned, establish an initial surface image library, and determine the cleaning information of each aluminum alloy part to be cleaned, clean the surface of each aluminum alloy part to be cleaned, and obtain the aluminum alloy part to be polished, wherein the cleaning information includes the cleaning agent usage parameters and the cleaning water pressure parameters; Step 2: determining the polishing requirement information of the aluminum alloy surface based on the aluminum alloy to be polished, and obtaining the polishing requirement information and polishing tool type information of the aluminum alloy surface to be polished, wherein the polishing requirement information includes the aluminum alloy surface quality index and the polishing film quality index, and the polishing tool type information includes the polishing tool type information and the polishing tool size information; The step of determining the polishing requirement information of the aluminum alloy part surface based on the aluminum alloy part to be polished, and obtaining the polishing requirement information and polishing tool type information of the aluminum alloy surface to be polished, specifically includes: Placing the aluminum alloy part to be polished in a fixture, collecting high-definition surface images of all to-be-polished surfaces of the aluminum alloy part to be polished, and images of adjacent structures of the aluminum alloy part to be polished close to the to-be-polished surfaces, and establishing a surface high-definition image library and an adjacent structure image library; Performing image preprocessing on the surface high-definition images and the adjacent structure images in the surface high-definition image library and the adjacent structure image library to obtain the surface high-definition standard image library and the adjacent structure standard image library; Divide the images in the surface high-definition standard image library to obtain the surface high-definition segmented images; Perform grayscale processing on each surface high-definition segmented image to obtain a surface segmented grayscale image library, and determine the average smoothness index of the aluminum alloy part to be polished; A low-pass filter is used to filter each surface high-definition segmented image to obtain the average roughness index of the aluminum alloy part to be polished; Taking the average of the smoothness average index and the roughness average index as the surface quality parameter of the aluminum alloy part to be polished; Determine the surface polishing requirement information and polishing tool type information of the aluminum alloy part based on the surface quality parameters and the adjacent structure image library; Step 3: obtaining an original image of each aluminum alloy part to be polished, and dividing the original image into regions based on the polishing tool type information, obtaining an image of the region to be polished, and establishing an image library of the region to be polished; Among them, the method for establishing the image library of the area to be polished is: Based on the polishing tool type information, determine the polishing tool size information and the polishing tool quantity information; A square blank window is set with the size of the largest polishing tool as the maximum size of the area division, and the area division window is constructed; Performing region division on each original image of the aluminum alloy part to be polished based on the region division window to obtain a region image to be polished; Obtaining the acquisition time sequence of the images of the area to be polished, and sorting the images of the area to be polished according to the acquisition time sequence to obtain an image library of the area to be polished; Step 4: Acquire surface texture feature information of the aluminum alloy surface corresponding to each image of the area to be polished in the image library of the area to be polished, and establish a surface texture feature set for each image of the area to be polished; The step of obtaining the surface texture feature information of the aluminum alloy surface corresponding to each image of the area to be polished in the image library of the area to be polished and establishing a surface texture feature set of each image of the area to be polished specifically includes: Performing image standardization processing on each image of the area to be polished in the image library of the area to be polished to obtain a standard image of the area to be polished; Based on the gray level co-occurrence matrix, the co-occurrence matrix of the pixel gray level pairs in the standard image of each area to be polished is obtained, and the contrast parameter, energy index, correlation parameter and uniformity index measuring the gray level pairs are extracted; Record the contrast parameter, energy index, correlation parameter and uniformity index of each standard image of the area to be polished respectively, obtain surface texture feature information, and establish a surface texture feature set of each image of the area to be polished; Step 5: Obtain polishing influencing parameters that match the surface texture feature set of each image of the area to be polished, and determine preset polishing information corresponding to each image of the area to be polished based on the surface texture feature set of each image of the area to be polished, wherein the preset polishing information includes preset polishing tool usage parameters, preset polishing speed, preset polishing time, and preset polishing pressure; The step of obtaining the polishing influencing parameters matching the surface texture feature set of each image of the area to be polished, and determining the preset polishing information corresponding to each image of the area to be polished based on the surface texture feature set of each image of the area to be polished, specifically includes: The aluminum alloy workpiece to be polished is placed horizontally on the polishing pad, and surface point cloud images of the aluminum alloy workpiece to be polished at different angles are obtained by using a three-dimensional scanner to establish a surface point cloud image library; Obtain environmental information of surface point cloud images at different angles and establish an environmental information database; Match the surface point cloud images in the surface point cloud image library with the environmental information in the environmental information library one by one to obtain the environmental impact point cloud database; Acquire registration point cloud coordinate information corresponding to the environmental impact point cloud data; Determine the size information of the aluminum alloy part to be polished, wherein the size information includes the overall size, weight, wall thickness, parallelism and verticality of the aluminum alloy part to be polished; Obtaining polishing influencing parameters matching a surface texture feature set of each to-be-polished area image based on size information of the to-be-polished aluminum alloy part; Determine preset polishing information according to the polishing influencing parameters and the surface texture feature set of each to-be-polished area image; Step 6: Based on the image of each area to be polished and the original image of the aluminum alloy part to be polished, determine the polishing position information, and polish the aluminum alloy part to be polished based on the preset polishing information and the polishing tool type information to obtain the initially polished aluminum alloy part; Step 7: real-time acquisition of real-time images of the primary polished aluminum alloy part, and acquisition of adjacent area images of the polished area and the unpolished area, extraction of surface adjacent texture features, and establishment of a surface adjacent texture feature set; Step eight, based on the surface adjacent texture feature set and the corresponding polishing influencing parameters, determine the adjacent area polishing information corresponding to each to-be-polished area image, and polish the surface position of the primary polishing aluminum alloy part corresponding to the adjacent area image.

2. A large-size aluminum alloy surface polishing control method according to claim 1, characterized in that: The step of determining the cleaning information of each aluminum alloy part to be cleaned, cleaning the surface of each aluminum alloy part to be cleaned, and obtaining the aluminum alloy part to be polished specifically includes: Traversing all the initial surface images in the initial surface image library, extracting the initial surface images collected from the same aluminum alloy part to be cleaned, and obtaining a corresponding initial surface image set; Acquiring an acquisition sequence when acquiring an initial surface image of the aluminum alloy part to be cleaned; Performing image stitching on the initial surface images in the initial surface image set according to the acquisition sequence to obtain an initial surface stitching image; Setting first preset parameters, and constructing a first cutting template according to the first preset parameters; Crop the initial surface stitching image according to the first cropping template to obtain an initial cropped image; Perform image processing on each initial cropped image, obtain the pollution degree index of each initial cropped image, and establish a pollution degree index matrix; Based on the contamination degree index matrix, contamination characteristic information of the aluminum alloy part to be cleaned in the initial surface image is obtained, and the aluminum alloy part to be cleaned is cleaned.

3. The surface polishing control method of a large-size aluminum alloy part according to claim 1 is characterized in that: The real-time acquisition of the real-time image of the primary polished aluminum alloy part, and the acquisition of the adjacent area images of the polished area and the unpolished area, the extraction of the surface adjacent texture features, and the establishment of the surface adjacent texture feature set specifically include: Based on the regional segmentation technology, the real-time image of the primary polished aluminum alloy part is segmented to obtain the polished area image and the unpolished area image; Based on the polished area image and the unpolished area image, the adjacent area images of the polished area and the unpolished area in the real-time image are segmented to obtain adjacent area images; Texture analysis is performed on adjacent area images to extract surface adjacent texture features and establish a surface adjacent texture feature set.

4. The surface polishing control method of a large-size aluminum alloy part according to claim 1 is characterized in that: The method of determining the polishing information of the adjacent region corresponding to each image of the region to be polished based on the surface adjacent texture feature set and the polishing influencing parameters corresponding thereto, and polishing the surface position of the primary polished aluminum alloy part corresponding to the adjacent region image, specifically includes: Obtaining a polished area image of a polished aluminum alloy part, and obtaining its corresponding historical surface texture feature set and historical polishing influencing parameters; Obtaining historical polishing information corresponding to the polishing area image of the polished aluminum alloy part; Integrate the historical surface texture feature set, historical polishing influencing parameters and historical polishing information to obtain integrated data; Extracting correlation data from the integrated data, and inputting the correlation data into the mechanical model for training to obtain a polishing information prediction model; Inputting the surface adjacent texture feature set of each to-be-polished area image and the polishing influencing parameters corresponding thereto into the polishing information prediction model to obtain the adjacent area polishing information; The surface position of the primary polished aluminum alloy part corresponding to the adjacent area image is polished based on the adjacent area polishing information.

5. A large-size aluminum alloy surface polishing control system, used to implement the control method according to any one of claims 1 to 4, characterized in that: include: A main control module, the main control module is used to determine the surface polishing requirement information of the aluminum alloy part based on the aluminum alloy part to be polished, and obtain the polishing requirement information and polishing tool type information of the aluminum alloy surface to be polished, obtain the surface texture feature information of the aluminum alloy surface corresponding to each area to be polished image in the area to be polished image library, obtain the polishing influence parameter matching the surface texture feature set of each area to be polished image, determine the preset polishing information corresponding to each area to be polished image based on the surface texture feature set of each area to be polished image, determine the polishing position information based on each area to be polished image and the original image of the aluminum alloy part to be polished, determine the adjacent area polishing information corresponding to each area to be polished image based on the surface adjacent texture feature set and the corresponding polishing influence parameter, determine the cleaning information of each aluminum alloy part to be cleaned, clean the surface of each aluminum alloy part to be cleaned, obtain the aluminum alloy part to be polished, polish the aluminum alloy part to be polished based on the preset polishing information and the polishing tool type information, obtain the initially polished aluminum alloy part, and polish the surface position of the initially polished aluminum alloy part corresponding to the adjacent area image; An acquisition module, wherein the acquisition module is used to acquire an initial surface image of the aluminum alloy part to be cleaned, establish an initial surface image library, obtain an original image of each aluminum alloy part to be polished, acquire a real-time image of the aluminum alloy part being initially polished in real time, and acquire adjacent area images of the polished area and the unpolished area, extract surface adjacent texture features, and establish a surface adjacent texture feature set; A transmission module, which is used to connect the main control module, the acquisition module and the display module, and transmit the data exchanged between the modules; The display module is used to display the processing results of the main control module, the data collected by the collection module, and the information transmitted and received by the transmission module.

6. A large-size aluminum alloy surface polishing control system according to claim 5, characterized in that: The main control module comprises: A data acquisition unit, the data acquisition unit is used to determine the surface polishing requirement information of the aluminum alloy part based on the aluminum alloy part to be polished, and obtain the polishing requirement information and polishing tool type information of the aluminum alloy surface to be polished, obtain the surface texture feature information of the aluminum alloy surface corresponding to each image of the area to be polished in the image library of the area to be polished, and obtain the polishing influencing parameters matching the surface texture feature set of each image of the area to be polished; A data processing unit, the data processing unit is used to determine the preset polishing information corresponding to each image of the area to be polished based on the surface texture feature set of each image of the area to be polished, determine the polishing position information based on each image of the area to be polished and the original image of the aluminum alloy part to be polished, and determine the polishing information of the adjacent area corresponding to each image of the area to be polished based on the surface adjacent texture feature set and the polishing influence parameters corresponding thereto; A control unit is used to determine the cleaning information of each aluminum alloy part to be cleaned, clean the surface of each aluminum alloy part to be cleaned, obtain the aluminum alloy part to be polished, polish the aluminum alloy part to be polished based on preset polishing information and polishing tool type information, obtain the initially polished aluminum alloy part, and polish the surface position of the initially polished aluminum alloy part corresponding to the adjacent area image.

7. A large-size aluminum alloy surface polishing control system according to claim 5, characterized in that: The acquisition module comprises: A first acquisition unit, wherein the first acquisition unit is used to acquire an initial surface image of the aluminum alloy part to be cleaned, establish an initial surface image library, and obtain an original image of each aluminum alloy part to be polished; The second acquisition unit is used to acquire real-time images of the primary polished aluminum alloy part, obtain adjacent area images of the polished area and the unpolished area, extract surface adjacent texture features, and establish a surface adjacent texture feature set.

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