Aluminum cap sorting monitoring system and method based on visual inspection

Abstract

The invention relates to the technical field of aluminum cap sorting, and discloses an aluminum cap sorting monitoring system and method based on visual inspection, and the system comprises an acquisition processing module which is configured to carry out the feature extraction of an image data set, and obtains a surface image feature set of a to-be-sorted aluminum cap; the comparison module is configured to generate defect labels of the to-be-sorted aluminum caps and calculate the overlap ratio of the to-be-sorted aluminum caps and the defect templates; the detection module is configured to compare the size feature set with a standard template in a standard object database and determine the quality grade of the to-be-sorted aluminum cover according to a comparison result; the calibration module is configured to judge whether to calibrate the quality grade of the to-be-sorted aluminum cover or not based on the analysis result; and calculating an environment influence coefficient according to the operation environment data, calibrating the quality grade according to the environment influence coefficient, and obtaining a final quality grade. According to the aluminum cap sorting device, efficient and accurate sorting of aluminum caps can be achieved, and the sorting efficiency and accuracy are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of aluminum cap sorting, and in particular to an aluminum cap sorting monitoring system and method based on visual detection. Background Art

[0002] As packaging quality becomes increasingly stringent in the pharmaceutical and food industries, aluminum caps, as crucial packaging components, have a direct impact on product sealing and safety. Traditional aluminum cap sorting methods rely primarily on manual inspection, which is inefficient and susceptible to human error, leading to unstable and unreliable sorting results.

[0003] Therefore, it is necessary to design an aluminum cover sorting and monitoring system and method based on visual inspection to solve the problems existing in the current technology. Summary of the Invention

[0004] In view of this, the present invention proposes an aluminum cap sorting and monitoring system and method based on visual inspection, aiming to achieve efficient and accurate sorting of aluminum caps through automated and intelligent means.

[0005] In one aspect, the present invention provides an aluminum cap sorting and monitoring system based on visual inspection, comprising:

[0006] The acquisition and processing module is configured to determine the aluminum caps to be sorted, collect a plurality of image data of the aluminum caps to be sorted within a preset time period using a visual inspection device, and form an image data set; perform feature extraction on the image data set to obtain a surface image feature set of the aluminum caps to be sorted; wherein the surface image feature set is composed of surface feature values, texture feature values, and reflective feature values;

[0007] a comparison module configured to compare the surface image feature set with a defect template in a standard object database, and determine whether the aluminum cover to be sorted has defects based on the comparison result; if so, generate a defect label for the aluminum cover to be sorted, and calculate the degree of overlap between the aluminum cover to be sorted and the defect template;

[0008] a detection module configured to determine whether the aluminum caps to be sorted are qualified based on the overlap; if so, obtain a set of size features of the aluminum caps to be sorted based on the image data set, compare the set of size features with a standard template in the standard object database, and determine a quality grade of the aluminum caps to be sorted based on the comparison result;

[0009] The calibration module is configured to collect the operating environment data of the visual inspection equipment, analyze the operating environment data, and determine whether to calibrate the quality grade of the aluminum cover to be sorted based on the analysis result; if so, calculate the environmental impact coefficient according to the operating environment data, calibrate the quality grade according to the environmental impact coefficient, and obtain the final quality grade.

[0010] Furthermore, when the acquisition and processing module extracts features from the image data set to obtain a surface image feature set of the aluminum caps to be sorted, the process includes:

[0011] Preprocessing the image data set, wherein the preprocessing includes denoising and contrast enhancement;

[0012] Using an image recognition algorithm to extract feature points from the preprocessed image data set to obtain contour features and color features of the surface of the aluminum cover to be sorted;

[0013] Based on the outline features and color features, image processing technology is used to calculate the surface feature values, texture feature values and reflection feature values of the aluminum covers to be sorted.

[0014] Furthermore, the comparison module compares the surface image feature set with the defect template in the standard object database, and determines whether the aluminum cover to be sorted has defects according to the comparison result, including:

[0015] Calculating the difference between each eigenvalue in the surface image feature set and the corresponding eigenvalue in the defect template one by one, and recording the difference as the eigenvalue difference;

[0016] When there is a characteristic value difference greater than or equal to the corresponding characteristic value difference threshold, it is determined that the aluminum cover to be sorted has defects;

[0017] Otherwise, it is determined that the aluminum cover to be sorted has no defects.

[0018] Furthermore, when the comparison module generates the defect label of the aluminum cover to be sorted and calculates the overlap between the aluminum cover to be sorted and the defect template, it includes:

[0019] The defect label includes the defect type and defect location;

[0020] The overlap degree is obtained by the following formula:

[0021]

[0022] Where R represents the overlap; n represents the total number of features; ωi represents the weight of the i-th feature; F1i represents the value of the image of the aluminum cover to be sorted on the i-th feature; F2i represents the value of the defect template on the i-th feature; Similarity(F1i,F2i) represents the similarity measure of the i-th feature.

[0023] Furthermore, when the detection module judges whether the aluminum cover to be sorted is qualified according to the overlap, it includes:

[0024] Setting a coincidence threshold, comparing the coincidence with the coincidence threshold, and judging whether the aluminum cover to be sorted is qualified according to the comparison result;

[0025] When the overlap degree is greater than or equal to the overlap degree threshold, it is determined that the aluminum cover to be sorted is unqualified;

[0026] When the overlap degree is less than the overlap degree threshold, it is determined that the aluminum cover to be sorted is qualified.

[0027] Furthermore, the detection module compares the size feature set with the standard template in the standard object database, and determines the quality grade of the aluminum cover to be sorted according to the comparison result, including:

[0028] The size feature set consists of the thickness, diameter and edge flatness of the aluminum cap to be sorted;

[0029] The standard template consists of a thickness standard value, a diameter standard value and an edge flatness standard value;

[0030] Calculating the deviation between each feature value in the size feature set and the corresponding feature value in the standard template one by one, and recording the deviation as the size deviation value;

[0031] According to the size deviation value, a weighted average method is used to calculate the comprehensive deviation value of the aluminum cover to be sorted;

[0032] Comparing the comprehensive deviation value with the first comprehensive deviation value and the second comprehensive deviation value, and determining the quality grade of the aluminum cap to be sorted according to the comparison result; wherein the first comprehensive deviation value is smaller than the second comprehensive deviation value;

[0033] When the comprehensive deviation value is less than or equal to the first comprehensive deviation value, it is determined that the quality grade of the aluminum cover to be sorted is level one;

[0034] When the comprehensive deviation value is greater than the first comprehensive deviation value and less than or equal to the second comprehensive deviation value, it is determined that the quality grade of the aluminum cover to be sorted is level 2;

[0035] When the comprehensive deviation value is greater than the second comprehensive deviation value, it is determined that the quality grade of the aluminum cover to be sorted is grade three.

[0036] Furthermore, when the calibration module determines whether to calibrate the quality grade of the aluminum cap to be sorted based on the analysis result, it includes:

[0037] Determining an environmental characteristic value corresponding to the operating environment data, and determining a corresponding environmental characteristic threshold;

[0038] If all the environmental characteristic values are within the corresponding environmental characteristic thresholds, it is determined that the quality grade of the aluminum cover to be sorted is not calibrated;

[0039] If one or more environmental characteristic values are outside the corresponding environmental characteristic thresholds, it is determined that the quality level of the aluminum cover to be sorted is to be calibrated.

[0040] Furthermore, when the calibration module calculates the environmental impact coefficient according to the operating environment data, it includes:

[0041] Determine the environmental standard value corresponding to each environmental characteristic value;

[0042] Extract all environmental characteristic values that are greater than the environmental standard value, and calculate the deviation value between each environmental characteristic value and the corresponding environmental standard value;

[0043] Determine all deviation values, and generate a first deviation value set based on all deviation values that are less than or equal to a preset deviation value;

[0044] generating a second deviation value set according to all deviation values greater than a preset deviation value;

[0045] Calculating a first average deviation value of the first deviation value set;

[0046] Calculating a second average deviation value of the second deviation value set;

[0047] An environmental impact coefficient is calculated based on the first average deviation value and the second average deviation value.

[0048] Furthermore, the calibration module calibrates the quality level according to the environmental impact coefficient to obtain the final quality level, including:

[0049] comparing the environmental impact coefficient with a first environmental impact coefficient and a second environmental impact coefficient, and calibrating the quality level according to the comparison result; wherein the first environmental impact coefficient is smaller than the second environmental impact coefficient;

[0050] When the environmental impact coefficient is less than or equal to the first environmental impact coefficient, it is determined that the quality level does not need to be adjusted, that is, the final quality level;

[0051] When the environmental impact coefficient is greater than the first environmental impact coefficient and less than or equal to the second environmental impact coefficient, the quality grade is lowered by one level to be the final quality grade;

[0052] When the environmental impact coefficient is greater than the second environmental impact coefficient, the quality level is lowered by two levels to be the final quality level.

[0053] Compared with the prior art, the present invention has the following advantages: the aluminum cover sorting and monitoring system based on visual inspection provided by the present invention can achieve efficient and accurate sorting of aluminum covers, improving sorting efficiency and accuracy. The acquisition and processing module extracts features from the image data of the aluminum covers to be sorted, and a surface image feature set of the aluminum covers can be obtained. Then, the comparison module compares the features with the defect templates in the standard object database to determine whether the aluminum covers have defects. The aluminum covers are judged to be qualified based on the degree of overlap, and the inspection module further compares the dimensional features of qualified aluminum covers to determine their quality grade. The calibration module can also calibrate the quality grade of the aluminum covers based on the operating environment data of the visual inspection equipment to ensure the accuracy and reliability of the sorting results.

[0054] In another aspect, the present invention also proposes a method for sorting and monitoring aluminum caps based on visual inspection, comprising the following steps:

[0055] S100: Determine aluminum caps to be sorted, collect a plurality of image data of the aluminum caps to be sorted within a preset time period using a visual inspection device, and form an image dataset; perform feature extraction on the image dataset to obtain a surface image feature set of the aluminum caps to be sorted; wherein the surface image feature set comprises surface feature values, texture feature values, and reflective feature values;

[0056] S200: comparing the surface image feature set with a defect template in a standard object database, and determining whether the aluminum cover to be sorted has a defect based on the comparison result; if so, generating a defect label for the aluminum cover to be sorted, and calculating the degree of overlap between the aluminum cover to be sorted and the defect template;

[0057] S300: Determine whether the aluminum cap to be sorted is qualified based on the overlap; if so, obtain a size feature set of the aluminum cap to be sorted based on the image dataset, compare the size feature set with a standard template in the standard object database, and determine the quality grade of the aluminum cap to be sorted based on the comparison result;

[0058] S400: Collect the operating environment data of the visual inspection equipment, and analyze the operating environment data, and determine whether to calibrate the quality grade of the aluminum cover to be sorted based on the analysis result; if so, calculate the environmental impact coefficient according to the operating environment data, calibrate the quality grade according to the environmental impact coefficient, and obtain the final quality grade.

[0059] It is understandable that the above-mentioned aluminum cover sorting and monitoring system and method based on visual inspection have the same beneficial effects, which will not be described in detail here. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Various other advantages and benefits will become apparent to those skilled in the art upon reading the detailed description of the preferred embodiment below. The accompanying drawings are for illustration purposes only and are not to be considered as limiting the present invention. The same reference symbols are used throughout the drawings to represent the same components. In the drawings:

[0061] Figure 1 A structural block diagram of an aluminum cap sorting and monitoring system based on visual inspection provided by an embodiment of the present invention;

[0062] Figure 2 This is a flow chart of the aluminum cover sorting and monitoring method based on visual inspection provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0063] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present disclosure are shown in the accompanying drawings, it should be understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to enable a more thorough understanding of the present disclosure and to fully convey the scope of the present disclosure to those skilled in the art. It should be noted that, unless there is a conflict, the embodiments of the present disclosure and the features in the embodiments can be combined with each other. The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

[0064] See Figure 1 As shown, in some embodiments of the present application, this embodiment provides an aluminum cap sorting and monitoring system based on visual inspection, comprising:

[0065] The acquisition and processing module is configured to determine the aluminum caps to be sorted, collect a plurality of image data of the aluminum caps to be sorted within a preset time period using a visual inspection device, and form an image data set; perform feature extraction on the image data set to obtain a surface image feature set of the aluminum caps to be sorted; wherein the surface image feature set is composed of surface feature values, texture feature values, and reflective feature values;

[0066] a comparison module configured to compare the surface image feature set with a defect template in a standard object database, and determine whether the aluminum cover to be sorted has defects based on the comparison result; if so, generate a defect label for the aluminum cover to be sorted, and calculate the degree of overlap between the aluminum cover to be sorted and the defect template;

[0067] a detection module configured to determine whether the aluminum caps to be sorted are qualified based on the overlap; if so, obtain a set of size features of the aluminum caps to be sorted based on the image data set, compare the set of size features with a standard template in the standard object database, and determine a quality grade of the aluminum caps to be sorted based on the comparison result;

[0068] The calibration module is configured to collect the operating environment data of the visual inspection equipment, analyze the operating environment data, and determine whether to calibrate the quality grade of the aluminum cover to be sorted based on the analysis result; if so, calculate the environmental impact coefficient according to the operating environment data, calibrate the quality grade according to the environmental impact coefficient, and obtain the final quality grade.

[0069] It is understood that the visual inspection-based aluminum cap sorting and monitoring system provided in this embodiment can achieve efficient and accurate sorting of aluminum caps, improving sorting efficiency and accuracy. The acquisition and processing module extracts features from the image data of the aluminum caps to be sorted, obtaining a set of surface image features of the aluminum caps. The comparison module then compares these features with defect templates in a standard object database to determine whether the aluminum caps are defective. The degree of overlap determines whether the aluminum caps are qualified, and the inspection module further compares the dimensional features of qualified aluminum caps to determine their quality grade. The calibration module can also calibrate the quality grade of the aluminum caps based on the operating environment data of the visual inspection equipment, ensuring the accuracy and reliability of the sorting results.

[0070] Specifically, when the acquisition and processing module extracts features from the image data set to obtain the surface image feature set of the aluminum caps to be sorted, it includes:

[0071] Preprocessing the image data set, wherein the preprocessing includes denoising and contrast enhancement;

[0072] Using an image recognition algorithm to extract feature points from the preprocessed image data set to obtain contour features and color features of the surface of the aluminum cover to be sorted;

[0073] Based on the outline features and color features, image processing technology is used to calculate the surface feature values, texture feature values and reflection feature values of the aluminum covers to be sorted.

[0074] In this embodiment, the surface characteristic value refers to the quantitative value of the physical properties of the aluminum cover surface, such as the degree of unevenness, scratches, and wear; the texture characteristic value refers to the quantitative value of the characteristics of the aluminum cover surface pattern, complexity, regularity, etc.; the reflective characteristic value reflects the quantitative value of the optical properties of the aluminum cover surface, such as glossiness and reflective ability.

[0075] In this embodiment, an advanced image filtering algorithm is first used to remove image noise and enhance image contrast, making the surface features of the aluminum cover clearer. Next, edge detection and contour extraction techniques are used to accurately identify the contour features of the aluminum cover's surface, which facilitates subsequent eigenvalue calculations. Simultaneously, color space conversion and color analysis techniques are used to extract the color features of the aluminum cover's surface, which is crucial for determining whether the aluminum cover has color anomalies or contamination. Based on the obtained contour and color features, feature matching and image analysis algorithms are used to calculate the surface eigenvalues, texture eigenvalues, and reflective eigenvalues of the aluminum cover. These eigenvalues not only reflect the physical and optical properties of the aluminum cover's surface but also provide key information for subsequent defect detection and quality grade determination.

[0076] Specifically, the comparison module compares the surface image feature set with the defect template in the standard object database, and determines whether the aluminum cover to be sorted has defects based on the comparison result, including:

[0077] Calculating the difference between each eigenvalue in the surface image feature set and the corresponding eigenvalue in the defect template one by one, and recording the difference as the eigenvalue difference;

[0078] When there is a characteristic value difference greater than or equal to the corresponding characteristic value difference threshold, it is determined that the aluminum cover to be sorted has defects;

[0079] Otherwise, it is determined that the aluminum cover to be sorted has no defects.

[0080] It can be understood that the calculation of the eigenvalue difference is based on the similarity or difference between the aluminum cover to be sorted and the defect template in each feature dimension. By setting a reasonable eigenvalue difference threshold, sensitive and accurate detection of aluminum cover defects can be achieved. When a certain eigenvalue difference exceeds the threshold, it means that there is a significant difference between the aluminum cover to be sorted and the defect template in this feature dimension, thereby determining that the aluminum cover has a defect. This defect detection method based on eigenvalue comparison not only improves the accuracy of detection, but also greatly shortens the detection time and realizes the rapid identification of aluminum cover defects. At the same time, the system provided in this embodiment can also generate corresponding defect labels according to the specific type and degree of the defect, which facilitates subsequent processing and classification.

[0081] Specifically, when the comparison module generates the defect label of the aluminum cover to be sorted and calculates the overlap between the aluminum cover to be sorted and the defect template, it includes:

[0082] The defect label includes the defect type and defect location;

[0083] The overlap degree is obtained by the following formula:

[0084]

[0085] Where R represents the overlap; n represents the total number of features; ωi represents the weight of the i-th feature; F1i represents the value of the image of the aluminum cover to be sorted on the i-th feature; F2i represents the value of the defect template on the i-th feature; Similarity(F1i,F2i) represents the similarity measure of the i-th feature.

[0086] In this embodiment, the similarity measurement adopts the cosine similarity calculation method, which can measure the directional consistency of the aluminum cover image to be sorted and the defect template in each feature dimension, thereby accurately reflecting the similarity between them.

[0087] It's understandable that generating defect labels is crucial for identifying and classifying aluminum cap defects. Detailed documentation of defect type and location not only provides valuable information for subsequent quality control and process improvement, but also facilitates accurate traceability of aluminum caps. Furthermore, calculating the degree of overlap is a crucial metric for measuring the degree of similarity between the aluminum cap being sorted and the defect template. By comprehensively considering the weights of various features and measuring similarity, an objective and accurate degree of overlap can be derived, providing strong support for determining the quality of aluminum caps.

[0088] Specifically, when the detection module determines whether the aluminum cover to be sorted is qualified according to the overlap, it includes:

[0089] Setting a coincidence threshold, comparing the coincidence with the coincidence threshold, and judging whether the aluminum cover to be sorted is qualified according to the comparison result;

[0090] When the overlap degree is greater than or equal to the overlap degree threshold, it is determined that the aluminum cover to be sorted is unqualified;

[0091] When the overlap degree is less than the overlap degree threshold, it is determined that the aluminum cover to be sorted is qualified.

[0092] It is understandable that the setting of the overlap threshold is based on a comprehensive consideration of the tolerance for aluminum cover defects. Through a large number of experiments and data analysis, a reasonable overlap threshold is determined to ensure the accuracy and reliability of the sorting results. When the overlap of the aluminum cover to be sorted exceeds the threshold, it means that it is highly similar to the defect template and there may be obvious defects, so it is judged as unqualified. On the contrary, when the overlap is lower than the threshold, it is considered that the difference between the aluminum cover to be sorted and the defect template is large, it can be judged as qualified, and the subsequent quality grade determination will continue. This overlap-based qualification determination method not only improves the accuracy of sorting, but also enhances the adaptability and flexibility of the system, and can cope with multiple types and degrees of aluminum cover defects.

[0093] Specifically, the detection module compares the size feature set with the standard template in the standard object database, and determines the quality grade of the aluminum cover to be sorted according to the comparison result, including:

[0094] The size feature set consists of the thickness, diameter and edge flatness of the aluminum cap to be sorted;

[0095] The standard template consists of a thickness standard value, a diameter standard value and an edge flatness standard value;

[0096] Calculating the deviation between each feature value in the size feature set and the corresponding feature value in the standard template one by one, and recording the deviation as the size deviation value;

[0097] According to the size deviation value, a weighted average method is used to calculate the comprehensive deviation value of the aluminum cover to be sorted;

[0098] Comparing the comprehensive deviation value with the first comprehensive deviation value and the second comprehensive deviation value, and determining the quality grade of the aluminum cap to be sorted according to the comparison result; wherein the first comprehensive deviation value is smaller than the second comprehensive deviation value;

[0099] When the comprehensive deviation value is less than or equal to the first comprehensive deviation value, it is determined that the quality grade of the aluminum cover to be sorted is level one;

[0100] When the comprehensive deviation value is greater than the first comprehensive deviation value and less than or equal to the second comprehensive deviation value, it is determined that the quality grade of the aluminum cover to be sorted is level 2;

[0101] When the comprehensive deviation value is greater than the second comprehensive deviation value, it is determined that the quality grade of the aluminum cover to be sorted is grade three.

[0102] In this embodiment, the levels are level 3, level 2, and level 1 from low to high, where level 3 indicates that the aluminum cover has a large size deviation and relatively low quality; level 2 indicates that the aluminum cover has a moderate size deviation and medium quality; and level 1 indicates that the aluminum cover has the smallest size deviation and the highest quality.

[0103] It's clear that this comprehensive deviation-based quality grading method objectively and accurately reflects the actual quality of aluminum caps, providing an important basis for subsequent quality control and usage. Furthermore, by setting different comprehensive deviation thresholds, flexible sorting of aluminum caps with varying quality requirements can be achieved, improving the system's applicability and practicality.

[0104] Specifically, when the calibration module determines whether to calibrate the quality grade of the aluminum cover to be sorted based on the analysis result, it includes:

[0105] Determining an environmental characteristic value corresponding to the operating environment data, and determining a corresponding environmental characteristic threshold;

[0106] If all the environmental characteristic values are within the corresponding environmental characteristic thresholds, it is determined that the quality grade of the aluminum cover to be sorted is not calibrated;

[0107] If one or more environmental characteristic values are outside the corresponding environmental characteristic thresholds, it is determined that the quality level of the aluminum cover to be sorted is to be calibrated.

[0108] In this embodiment, the operating environment data includes temperature, humidity, and light intensity.

[0109] It is understandable that the operating environment data of the visual inspection equipment has an important impact on the determination of the quality grade of the aluminum cover. Changes in environmental factors such as temperature, humidity and light intensity may cause errors in the image acquisition and processing process, thereby affecting the final sorting results. Therefore, by real-time monitoring and analysis of the operating environment data through the calibration module, these errors can be discovered and corrected in a timely manner to ensure the accuracy and reliability of the sorting results. When all environmental characteristic values are within the corresponding environmental characteristic thresholds, it is considered that the current environment has little impact on the quality grade of the aluminum cover, and the quality grade does not need to be calibrated. However, when there are one or more environmental characteristic values that exceed the corresponding environmental characteristic thresholds, it means that the current environment may have a significant impact on the determination of the quality grade of the aluminum cover, and the quality grade needs to be calibrated.

[0110] Specifically, when the calibration module calculates the environmental impact coefficient according to the operating environment data, it includes:

[0111] Determine the environmental standard value corresponding to each environmental characteristic value;

[0112] Extract all environmental characteristic values that are greater than the environmental standard value, and calculate the deviation value between each environmental characteristic value and the corresponding environmental standard value;

[0113] Determine all deviation values, and generate a first deviation value set based on all deviation values that are less than or equal to a preset deviation value;

[0114] generating a second deviation value set according to all deviation values greater than a preset deviation value;

[0115] Calculating a first average deviation value of the first deviation value set;

[0116] Calculating a second average deviation value of the second deviation value set;

[0117] An environmental impact coefficient is calculated based on the first average deviation value and the second average deviation value.

[0118] In this embodiment, the environmental impact coefficient is calculated by taking a weighted average of the first average deviation value and the second average deviation value.

[0119] As you can understand, the calculation of the environmental impact coefficient fully considers the degree to which different environmental characteristic values influence the determination of the aluminum cap quality grade. By calculating the first and second mean deviation values separately, the fluctuations of environmental factors can be more accurately measured. The first mean deviation reflects the average contribution of characteristic values with small deviations from the environmental standard to the overall environmental impact, while the second mean deviation reflects the significant impact of characteristic values with large deviations. Through weighted average calculation, the environmental impact coefficient comprehensively reflects these factors, providing a scientific basis for quality grade calibration. A large environmental impact coefficient indicates that the current environment has a significant impact on the aluminum cap quality grade, requiring larger calibration adjustments. A small environmental impact coefficient indicates that the environmental impact is less significant, and the calibration adjustment can be reduced accordingly. This environmental impact coefficient-based calibration method not only improves calibration accuracy but also enhances the system's adaptability and robustness, enabling it to meet the needs of aluminum cap sorting in diverse environments.

[0120] Specifically, the calibration module calibrates the quality level according to the environmental impact coefficient to obtain the final quality level, including:

[0121] comparing the environmental impact coefficient with a first environmental impact coefficient and a second environmental impact coefficient, and calibrating the quality level according to the comparison result; wherein the first environmental impact coefficient is smaller than the second environmental impact coefficient;

[0122] When the environmental impact coefficient is less than or equal to the first environmental impact coefficient, it is determined that the quality level does not need to be adjusted, that is, the final quality level;

[0123] When the environmental impact coefficient is greater than the first environmental impact coefficient and less than or equal to the second environmental impact coefficient, the quality grade is lowered by one level to be the final quality grade;

[0124] When the environmental impact coefficient is greater than the second environmental impact coefficient, the quality level is lowered by two levels to be the final quality level.

[0125] It's understandable that when the quality grade is Level 3, there's no need to adjust it downward, and the lowest final quality grade is Level 3. When the environmental impact coefficient is low—less than or equal to the first environmental impact coefficient—it indicates that the current environment has little impact on the aluminum cap's quality grade. Therefore, no adjustment is required, and the current quality grade is used directly as the final quality grade. This approach ensures the accuracy of the sorting results, avoids unnecessary calibration, and improves work efficiency. However, when the environmental impact coefficient exceeds the first environmental impact coefficient but is less than or equal to the second environmental impact coefficient, it means that the current environmental impact on the aluminum cap's quality grade is beginning to become apparent, but has not yet reached a critical level. In this case, to ensure the reliability of the sorting results, the system will adjust the quality grade downward by one level, setting it as the final quality grade. This approach not only accounts for the impact of environmental factors but also ensures the rationality of the sorting results. Finally, when the environmental impact coefficient exceeds the second environmental impact coefficient, it indicates that the current environmental impact on the aluminum cap's quality grade is very significant, seriously interfering with the accuracy of the sorting results. In this case, the system will adjust the quality grade downward by two levels, setting it as the final quality grade. This major adjustment is intended to ensure relatively accurate sorting results even in harsh environments, thereby improving the robustness and practicality of the system.

[0126] See Figure 2 As shown, in some embodiments of the present application, this embodiment provides an aluminum cover sorting and monitoring method based on visual inspection, comprising the following steps:

[0127] S100: Determine aluminum caps to be sorted, collect a plurality of image data of the aluminum caps to be sorted within a preset time period using a visual inspection device, and form an image dataset; perform feature extraction on the image dataset to obtain a surface image feature set of the aluminum caps to be sorted; wherein the surface image feature set comprises surface feature values, texture feature values, and reflective feature values;

[0128] S200: comparing the surface image feature set with a defect template in a standard object database, and determining whether the aluminum cover to be sorted has a defect based on the comparison result; if so, generating a defect label for the aluminum cover to be sorted, and calculating the degree of overlap between the aluminum cover to be sorted and the defect template;

[0129] S300: Determine whether the aluminum cap to be sorted is qualified based on the overlap; if so, obtain a size feature set of the aluminum cap to be sorted based on the image dataset, compare the size feature set with a standard template in the standard object database, and determine the quality grade of the aluminum cap to be sorted based on the comparison result;

[0130] S400: Collect the operating environment data of the visual inspection equipment, and analyze the operating environment data, and determine whether to calibrate the quality grade of the aluminum cover to be sorted based on the analysis result; if so, calculate the environmental impact coefficient according to the operating environment data, calibrate the quality grade according to the environmental impact coefficient, and obtain the final quality grade.

[0131] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or a combination of software and hardware embodiments. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0132] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems) and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0133] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0134] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0135] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the scope of protection of the claims of the present invention.

Claims

1. An aluminum cap sorting and monitoring system based on visual inspection, characterized in that: include: The acquisition and processing module is configured to determine the aluminum caps to be sorted, collect a plurality of image data of the aluminum caps to be sorted within a preset time period using a visual inspection device, and form an image data set; perform feature extraction on the image data set to obtain a surface image feature set of the aluminum caps to be sorted; wherein the surface image feature set is composed of surface feature values, texture feature values, and reflective feature values; a comparison module configured to compare the surface image feature set with a defect template in a standard object database, and determine whether the aluminum cover to be sorted has defects based on the comparison result; if so, generate a defect label for the aluminum cover to be sorted, and calculate the degree of overlap between the aluminum cover to be sorted and the defect template; a detection module configured to determine whether the aluminum caps to be sorted are qualified based on the overlap; if so, obtain a set of size features of the aluminum caps to be sorted based on the image data set, compare the set of size features with a standard template in the standard object database, and determine a quality grade of the aluminum caps to be sorted based on the comparison result; The calibration module is configured to collect the operating environment data of the visual inspection equipment, analyze the operating environment data, and determine whether to calibrate the quality grade of the aluminum cover to be sorted based on the analysis result; if so, calculate the environmental impact coefficient according to the operating environment data, calibrate the quality grade according to the environmental impact coefficient, and obtain the final quality grade.

2. The aluminum cap sorting and monitoring system based on visual inspection according to claim 1 is characterized in that: The acquisition and processing module extracts features from the image data set to obtain a surface image feature set of the aluminum caps to be sorted, including: Preprocessing the image data set, wherein the preprocessing includes denoising and contrast enhancement; Using an image recognition algorithm to extract feature points from the preprocessed image data set to obtain contour features and color features of the surface of the aluminum cover to be sorted; Based on the outline features and color features, image processing technology is used to calculate the surface feature values, texture feature values and reflection feature values of the aluminum covers to be sorted.

3. The aluminum cap sorting and monitoring system based on visual inspection according to claim 2 is characterized in that: The comparison module compares the surface image feature set with the defect template in the standard object database, and determines whether the aluminum cover to be sorted has defects based on the comparison result, including: Calculating the difference between each eigenvalue in the surface image feature set and the corresponding eigenvalue in the defect template one by one, and recording it as the eigenvalue difference; When there is a characteristic value difference greater than or equal to the corresponding characteristic value difference threshold, it is determined that the aluminum cover to be sorted has defects; Otherwise, it is determined that the aluminum cover to be sorted has no defects.

4. The aluminum cap sorting and monitoring system based on visual inspection according to claim 3 is characterized in that: When the comparison module generates the defect label of the aluminum cover to be sorted and calculates the overlap between the aluminum cover to be sorted and the defect template, it includes: The defect label includes the defect type and defect location; The overlap degree is obtained by the following formula: Where R represents the overlap; n represents the total number of features; ωi represents the weight of the i-th feature; F1i represents the value of the image of the aluminum cover to be sorted on the i-th feature; F2i represents the value of the defect template on the i-th feature; Similarity(F1i,F2i) represents the similarity measure of the i-th feature.

5. The aluminum cap sorting and monitoring system based on visual inspection according to claim 4 is characterized in that: When the detection module determines whether the aluminum cover to be sorted is qualified according to the overlap, it includes: Setting a coincidence threshold, comparing the coincidence with the coincidence threshold, and judging whether the aluminum cover to be sorted is qualified according to the comparison result; When the overlap degree is greater than or equal to the overlap degree threshold, it is determined that the aluminum cover to be sorted is unqualified; When the overlap degree is less than the overlap degree threshold, it is determined that the aluminum cover to be sorted is qualified.

6. The aluminum cap sorting and monitoring system based on visual inspection according to claim 5, characterized in that: The detection module compares the size feature set with the standard template in the standard object database, and determines the quality grade of the aluminum cover to be sorted according to the comparison result, including: The size feature set consists of the thickness, diameter and edge flatness of the aluminum cap to be sorted; The standard template consists of a thickness standard value, a diameter standard value and an edge flatness standard value; Calculating the deviation between each feature value in the size feature set and the corresponding feature value in the standard template one by one, and recording the deviation as the size deviation value; According to the size deviation value, a weighted average method is used to calculate the comprehensive deviation value of the aluminum cover to be sorted; Comparing the comprehensive deviation value with the first comprehensive deviation value and the second comprehensive deviation value, and determining the quality grade of the aluminum cap to be sorted according to the comparison result; wherein the first comprehensive deviation value is smaller than the second comprehensive deviation value; When the comprehensive deviation value is less than or equal to the first comprehensive deviation value, it is determined that the quality grade of the aluminum cover to be sorted is level one; When the comprehensive deviation value is greater than the first comprehensive deviation value and less than or equal to the second comprehensive deviation value, it is determined that the quality grade of the aluminum cover to be sorted is level 2; When the comprehensive deviation value is greater than the second comprehensive deviation value, it is determined that the quality grade of the aluminum cover to be sorted is grade three.

7. The aluminum cap sorting and monitoring system based on visual inspection according to claim 6, characterized in that: When the calibration module determines whether to calibrate the quality grade of the aluminum cover to be sorted based on the analysis result, it includes: Determining an environmental characteristic value corresponding to the operating environment data, and determining a corresponding environmental characteristic threshold; If all the environmental characteristic values are within the corresponding environmental characteristic thresholds, it is determined that the quality grade of the aluminum cover to be sorted is not calibrated; If one or more environmental characteristic values are outside the corresponding environmental characteristic thresholds, it is determined that the quality level of the aluminum cover to be sorted is to be calibrated.

8. The aluminum cap sorting and monitoring system based on visual inspection according to claim 1, characterized in that: When the calibration module calculates the environmental impact coefficient according to the operating environment data, it includes: Determine the environmental standard value corresponding to each environmental characteristic value; Extract all environmental characteristic values that are greater than the environmental standard value, and calculate the deviation value between each environmental characteristic value and the corresponding environmental standard value; Determine all deviation values, and generate a first deviation value set based on all deviation values that are less than or equal to a preset deviation value; generating a second deviation value set according to all deviation values greater than a preset deviation value; Calculating a first average deviation value of the first deviation value set; Calculating a second average deviation value of the second deviation value set; An environmental impact coefficient is calculated based on the first average deviation value and the second average deviation value.

9. The aluminum cap sorting and monitoring system based on visual inspection according to claim 8, characterized in that: The calibration module calibrates the quality level according to the environmental impact coefficient to obtain a final quality level, including: comparing the environmental impact coefficient with a first environmental impact coefficient and a second environmental impact coefficient, and calibrating the quality level according to the comparison result; wherein the first environmental impact coefficient is smaller than the second environmental impact coefficient; When the environmental impact coefficient is less than or equal to the first environmental impact coefficient, it is determined that the quality level does not need to be adjusted, that is, the final quality level; When the environmental impact coefficient is greater than the first environmental impact coefficient and less than or equal to the second environmental impact coefficient, the quality grade is lowered by one level to be the final quality grade; When the environmental impact coefficient is greater than the second environmental impact coefficient, the quality level is lowered by two levels to be the final quality level.

10. A method for sorting and monitoring aluminum caps based on visual inspection, applied to the aluminum cap sorting and monitoring system based on visual inspection according to any one of claims 1 to 9, characterized in that: include: Determine the aluminum caps to be sorted, collect a plurality of image data of the aluminum caps to be sorted within a preset time period using a visual inspection device, and form an image data set; Performing feature extraction on the image data set to obtain a surface image feature set of the aluminum cap to be sorted; wherein the surface image feature set consists of surface feature values, texture feature values, and reflective feature values; Compare the surface image feature set with the defect template in the standard object database, and determine whether the aluminum cover to be sorted has defects based on the comparison result; if so, generate a defect label for the aluminum cover to be sorted, and calculate the degree of overlap between the aluminum cover to be sorted and the defect template; Determine whether the aluminum cover to be sorted is qualified based on the overlap; if so, obtain a set of size features of the aluminum cover to be sorted based on the image data set, compare the set of size features with a standard template in the standard object database, and determine the quality grade of the aluminum cover to be sorted based on the comparison result; Collect the operating environment data of the visual inspection equipment, analyze the operating environment data, and determine whether to calibrate the quality grade of the aluminum cover to be sorted based on the analysis result; if so, calculate the environmental impact coefficient according to the operating environment data, calibrate the quality grade according to the environmental impact coefficient, and obtain the final quality grade.

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