Electronic grating quality inspection and evaluation method based on digital twin model

Abstract

The present invention relates to the technical field of quality inspection and evaluation, and specifically discloses an electronic grating quality inspection and evaluation method based on a digital twin model, comprising: inputting physical scanning data of a quality inspection object into a digital electronic grating measurement system to obtain all partition detection results of the quality inspection object; aligning all partition detection results of the quality inspection object with a standard morphological twin model of the quality inspection object as a whole to obtain quality inspection and evaluation reference data for each partition detection result; comparing each partition detection result of the quality inspection object with the corresponding quality inspection and evaluation reference data to obtain a quality inspection and evaluation result of the quality inspection object; and effectively improving the accuracy, reliability and efficiency of quality inspection and ensuring the quality of the quality inspection object.

Description

Technical Field

[0001] The present invention relates to the technical field of quality inspection and evaluation, and in particular to an electronic grating quality inspection and evaluation method based on a digital twin model. Background Art

[0002] Digital twins, as a cutting-edge digital simulation technology, use digital means to accurately simulate physical devices, systems, or processes, creating a virtual model that fully corresponds to them. They have demonstrated tremendous potential and value in a variety of fields, including manufacturing, energy, aerospace, and urban planning. In the manufacturing sector, digital twins have been widely applied. They enable monitoring, evaluation, diagnosis, prediction, and optimization through virtual models that mirror physical entities, addressing the challenge of integrating digital and physical information in the manufacturing process. In particular, digital twins enable comprehensive and precise control of product quality, improving production efficiency and quality. Electronic gratings, as precision measuring equipment, play a vital role in manufacturing and quality inspection. Traditional quality inspection and evaluation methods for electronic gratings often rely on manual operation and empirical judgment, resulting in low accuracy and efficiency. However, digital twin-based quality inspection and evaluation methods for electronic gratings enable virtual simulation and real-time monitoring of electronic gratings, improving the accuracy and efficiency of quality inspection.

[0003] To improve the efficiency of electronic grating quality inspection methods, the appearance inspection data of the inspection object obtained by the electronic grating measurement system can be compared with its digital twin model in a standard form to identify and evaluate actual defects in the inspection object's appearance. However, how to accurately compare the appearance inspection data of the inspection object obtained by the electronic grating measurement system with its digital twin model in a standard form to ensure the accuracy of the compared quality inspection and evaluation data is a major difficulty in electronic grating quality inspection and evaluation methods based on digital twin models.

[0004] Therefore, the present invention proposes an electronic grating quality inspection and evaluation method based on a digital twin model. Summary of the Invention

[0005] The present invention provides an electronic grating quality inspection and evaluation method based on a digital twin model, which is used to obtain all partition detection results using an electronic grating, and can comprehensively and efficiently collect detection information of the quality inspection object to ensure the integrity of the data. By aligning the partition detection results with the standard form twin model as a whole, a local and accurate comparison between the appearance detection data of the quality inspection object obtained by the digital electronic grating measurement system and its digital twin model in the standard form is achieved, providing an accurate quality inspection and evaluation reference for each partition, thereby improving the scientific nature of the evaluation. It is helpful to discover subtle differences between the partition detection results and the standard, and to improve the accuracy of quality inspection. By comparing the partition detection results with the reference data, the quality inspection and evaluation results can be objectively and accurately obtained, reducing human errors. This can effectively improve the accuracy, reliability and efficiency of quality inspection, and ensure the quality of the quality inspection object.

[0006] The present invention provides an electronic grating quality inspection and evaluation method based on a digital twin model, comprising:

[0007] S1: Input the physical scan data of the inspection object into the digital electronic raster measurement system to obtain the inspection results of all partitions of the inspection object;

[0008] S2: Align all partition test results of the quality inspection object with the standard morphological twin model of the quality inspection object to obtain quality inspection evaluation reference data for each partition test result;

[0009] S3: Compare the detection result of each partition of the quality inspection object with the corresponding quality inspection evaluation reference data to obtain the quality inspection evaluation result of the quality inspection object.

[0010] Preferably, the electronic grating quality inspection and evaluation method based on the digital twin model includes: S1: inputting the physical scan data of the quality inspection object into the digital electronic grating measurement system to obtain all partition inspection results of the quality inspection object, including:

[0011] S101: partitioning the outer surface of the inspection object based on the surface material distribution of the inspection object to obtain the surface coverage area of ​​each material;

[0012] S102: determining the final value ranges of all surface partitions of the quality inspection object and all types of electronic grating parameters of each surface partition based on the shape of the surface coverage area of ​​each material and the material type;

[0013] S103: Inputting the physical scan data of the inspection object into a digital electronic grating measurement system set based on the final value range of all types of electronic grating parameters of each surface partition to obtain partition detection results of all surface partitions of the inspection object.

[0014] Preferably, in the electronic grating quality inspection and evaluation method based on the digital twin model, S102: based on the shape of the surface coverage area of ​​each material and the material type, determining the final value range of all surface partitions of the quality inspection object and all types of electronic grating parameters of each surface partition, including:

[0015] Based on the shape and material type of the surface coverage area of ​​each material, a preset electronic grating parameter value range table is retrieved to determine the value ranges of all types of electronic grating parameters of the surface coverage area of ​​each material;

[0016] Based on the value ranges of all types of electronic grating parameters of the surface coverage areas of all materials of the quality inspection object, the final value ranges of all types of electronic grating parameters of all surface partitions of the quality inspection object and each surface partition are determined.

[0017] Preferably, the electronic grating quality inspection and evaluation method based on the digital twin model determines the final value range of all types of electronic grating parameters of all surface partitions of the quality inspection object and each surface partition based on the value range of all types of electronic grating parameters of the surface coverage area of ​​all materials of the quality inspection object, including:

[0018] Calculating the merging operability between the surface coverage areas of each two materials of the quality inspection object based on the value ranges of all types of electronic grating parameters of the surface coverage areas of each two materials of the quality inspection object;

[0019] The surface coverage areas of all materials whose mergable operation degree is not less than the operation degree threshold are regarded as all mergable areas;

[0020] Determine all surface partitions of the inspection object based on all mergeable areas;

[0021] The value ranges of the same type of electronic grating parameters of the surface coverage area of ​​each material contained in each surface partition are intersected to obtain the final value range of each type of electronic grating parameter of each surface partition.

[0022] Preferably, the electronic grating quality inspection and evaluation method based on the digital twin model calculates the merging operability between the surface coverage areas of each two materials of the quality inspection object based on the value ranges of all types of electronic grating parameters of the surface coverage areas of each two materials of the quality inspection object, including:

[0023] Calculate the ratio of the interval length of the intersection between the value ranges of the same type of electronic grating parameters of the surface coverage areas of each two materials of the quality inspection object and the average value of the interval length of the value ranges of the same type of electronic grating parameters of the surface coverage areas of each two materials of the quality inspection object, and use it as the interval overlap of the value ranges of the corresponding type of electronic grating parameters of the surface coverage areas of each two materials of the quality inspection object;

[0024] The average value of the interval overlap of the value ranges of all types of electronic grating parameters of the surface coverage areas of each two materials of the quality inspection object is regarded as the merging operability between the surface coverage areas of each two materials of the quality inspection object.

[0025] Preferably, the electronic grating quality inspection and evaluation method based on the digital twin model determines all surface partitions of the inspection object based on all mergeable areas, including:

[0026] From all the mergable areas, select the mergable areas with more than one mergable operation degree between them and all other mergable areas, and use them as the first-tier merging areas;

[0027] Merge two mergable regions corresponding to the maximum mergable operation degree among all mergable operation degrees that are not less than the operation degree threshold between each first gradient merging region and all other mergable regions to obtain a first merging region;

[0028] determining whether, among all the mergable areas except all the mergable areas included in all the first merging areas, there is at least one group of mergable areas whose corresponding mergable operability is not less than the operability threshold; if so, merging the at least one group of mergable areas whose corresponding mergable operability is not less than the operability threshold to obtain a second merging area; otherwise, retaining the determination result;

[0029] All surface partitions of the quality inspection object are determined based on all the first merged regions and all the second merged regions.

[0030] Preferably, the electronic grating quality inspection and evaluation method based on the digital twin model determines all surface partitions of the quality inspection object based on all first merged areas and all second merged areas, including:

[0031] Calculating the merging operability between every two regions in all first merging regions and all second merging regions;

[0032] Determine whether there are two regions with a mergible operability not less than a threshold operability threshold among all the first merged regions and all the second merged regions; if so, merge the two regions with a mergible operability not less than the threshold operability threshold into a third merged region; otherwise, merge all the mergible regions contained in each first merged region into a single surface partition of the quality inspection object; and at the same time, merge all the mergible regions contained in each second merged region into a single surface partition of the quality inspection object;

[0033] Continue to calculate the mergible operation degree between each of the third merged areas until all the newly obtained merged areas do not contain at least one group of merged areas whose mergible operation degree is not less than the operation degree threshold. Then merge all the mergible areas contained in each of the latest merged areas as a single surface partition of the quality inspection object.

[0034] Preferably, the electronic grating quality inspection and evaluation method based on the digital twin model calculates the merging operability between each two areas in all first merging areas and all second merging areas, including:

[0035] The ratio of the interval length of the intersection between the value ranges of the same type of electronic grating parameters of all mergable areas contained in every two areas of all the first merged areas and all the second merged areas to the average value of the interval lengths of the value ranges of the same type of electronic grating parameters of the two corresponding areas is regarded as the interval overlap of the value ranges of the corresponding type of electronic grating parameters of the two corresponding areas;

[0036] The average value of the interval overlap of the value ranges of all types of electronic grating parameters of every two areas in all the first merging areas and all the second merging areas is regarded as the merging operability between every two areas in all the first merging areas and all the second merging areas.

[0037] Preferably, in the electronic grating quality inspection and evaluation method based on the digital twin model, S2: all partition inspection results of the quality inspection object are aligned with the standard morphological twin model of the quality inspection object to obtain quality inspection and evaluation reference data for each partition inspection result, including:

[0038] S201: Determine appearance morphology data of each surface partition of the quality inspection object based on the detection result of each partition of the quality inspection object;

[0039] S202: Based on the appearance morphological data of all surface partitions of the quality inspection object, all partition detection results of the quality inspection object are aligned with the standard morphological twin model of the quality inspection object, and the quality inspection evaluation reference data of each partition detection result is determined in the standard morphological twin model of the quality inspection object.

[0040] Preferably, the electronic grating quality inspection and evaluation method based on the digital twin model, S3: comparing the inspection result of each partition of the quality inspection object with the corresponding quality inspection and evaluation reference data to obtain the quality inspection and evaluation result of the quality inspection object, including:

[0041] S301: Compare the inspection result of each partition of the quality inspection object with the corresponding quality inspection evaluation reference data to obtain the quality inspection result of each surface partition of the quality inspection object;

[0042] S302: Summarize and integrate the quality inspection results of all surface partitions of the quality inspection object to obtain a quality inspection evaluation result of the quality inspection object.

[0043] The beneficial effects of the present invention compared to the prior art are as follows: by using electronic grating to obtain all partition detection results, the detection information of the quality inspection object can be collected comprehensively and efficiently, ensuring the integrity of the data. By aligning the partition detection results with the standard form twin model as a whole, a local and precise comparison between the appearance detection data of the quality inspection object obtained by the digital electronic grating measurement system and its digital twin model in the standard form is achieved, providing an accurate quality inspection evaluation reference for each partition and improving the scientific nature of the evaluation. It helps to discover subtle differences between the partition detection results and the standard, and improve the accuracy of quality inspection. Comparing the partition detection results with the reference data can objectively and accurately derive the quality inspection evaluation results and reduce human errors. This can effectively improve the accuracy, reliability and efficiency of quality inspection and ensure the quality of the quality inspection object.

[0044] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purpose and other advantages of the present invention can be achieved and obtained through the structures specifically pointed out in this application document.

[0045] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0047] Figure 1 This is a flow chart of an electronic grating quality inspection and evaluation method based on a digital twin model in an embodiment of the present invention;

[0048] Figure 2 This is a flowchart of a specific execution method of step S1 in an embodiment of the present invention;

[0049] Figure 3 This is a flowchart of a specific execution method of step S2 in an embodiment of the present invention;

[0050] Figure 4 4 is a flowchart of a specific execution method of step S3 in an embodiment of the present invention. DETAILED DESCRIPTION

[0051] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0052] Example 1:

[0053] The present invention provides an electronic grating quality inspection and evaluation method based on a digital twin model. Figure 1 ,include:

[0054] S1: Input the physical scan data of the inspection object into the digital electronic raster measurement system to obtain the inspection results of all partitions of the inspection object;

[0055] S2: Align all partition test results of the quality inspection object with the standard morphological twin model of the quality inspection object to obtain quality inspection evaluation reference data for each partition test result;

[0056] S3: Compare the detection result of each partition of the quality inspection object with the corresponding quality inspection evaluation reference data to obtain the quality inspection evaluation result of the quality inspection object.

[0057] In this embodiment, the digital electronic grating measurement system is a software measurement system that uses computer software to simulate the detection effect of a physical grating on the quality inspection object and utilizes the principle of electronic grating to obtain relevant information about the quality inspection object (such as shape, size, surface features, etc.).

[0058] In this embodiment, the quality inspection object refers to the article, component or product that needs to be inspected and evaluated for quality. It can be various physical objects, such as mechanical parts, electronic products, food, etc.

[0059] In this embodiment, the twin model of the standard form of the quality inspection object is a digital simulation and description of the quality inspection object in an ideal, standard state. This model contains various characteristics and parameters that the quality inspection object should have in its standard form, serving as a benchmark for comparison and evaluation of the actual quality inspection object.

[0060] In this embodiment, the quality inspection evaluation reference data of the partition detection results are determined in the standard morphological twin model of the quality inspection object. These data are used to provide the basis and standards for the evaluation of the detection results of each partition, such as the deviation range, qualification indicators, etc.

[0061] In this embodiment, the quality inspection evaluation result of the quality inspection object is obtained by comparing and analyzing the inspection results of each partition with the corresponding quality inspection evaluation reference data, and obtaining a final conclusion on whether the quality of the entire quality inspection object is qualified, what problems exist, and the severity of the problems.

[0062] The beneficial effects of the above technology are as follows: Step S1 uses the electronic grating to obtain all partition detection results, which can comprehensively and efficiently collect the detection information of the quality inspection object and ensure the integrity of the data. Step S2 realizes the local precise comparison between the appearance detection data of the quality inspection object obtained by the digital electronic grating measurement system and its digital twin model in the standard form by overall alignment of the partition detection results and the standard form twin model, providing an accurate quality inspection evaluation reference for each partition and improving the scientific nature of the evaluation. It helps to discover subtle differences between the partition detection results and the standard, and improve the accuracy of quality inspection. Step S3 compares the partition detection results with the reference data, which can objectively and accurately derive the quality inspection evaluation results and reduce human errors. This can effectively improve the accuracy, reliability and efficiency of quality inspection and ensure the quality of the quality inspection object.

[0063] Example 2:

[0064] On the basis of Example 1, the electronic grating quality inspection and evaluation method based on the digital twin model, S1: input the physical scanning data of the quality inspection object into the digital electronic grating measurement system, obtain all the partition detection results of the quality inspection object, refer to Figure 2 ,include:

[0065] S101: partitioning the outer surface of the inspection object based on the surface material distribution of the inspection object to obtain the surface coverage area of ​​each material;

[0066] S102: determining the final value ranges of all surface partitions of the quality inspection object and all types of electronic grating parameters of each surface partition based on the shape of the surface coverage area of ​​each material and the material type;

[0067] S103: Inputting the physical scan data of the inspection object into a digital electronic grating measurement system set based on the final value range of all types of electronic grating parameters of each surface partition to obtain partition detection results of all surface partitions of the inspection object.

[0068] In this embodiment, the surface material distribution of the inspection object refers to the distribution position and range of different materials on the outer surface of the inspection object. For example, a part may be made of metal and another part of plastic.

[0069] In this embodiment, the surface coverage area of ​​each material refers to the specific range occupied by each specific material on the surface of the inspection object, such as the area covered by the metal material in the above-mentioned part.

[0070] In this embodiment, the shape and material type of the surface coverage area include the outer contour (such as circle, square, etc.) and the material category (such as steel, aluminum, rubber, etc.) of each material coverage area.

[0071] In this embodiment, all surface partitions of the quality inspection object are multiple regions formed by dividing the complete outer surface of the quality inspection object according to certain rules.

[0072] In this embodiment, the final value range of all types of electronic grating parameters refers to the specific value range that can be set for various parameters of the electronic grating (such as wavelength, frequency, intensity, etc.) that are suitable for current detection requirements.

[0073] In this embodiment, the physical scanning data of the quality inspection object is input into a digital electronic grating measurement system that is set based on the final value range of all types of electronic grating parameters of each surface partition. Obtaining the partition detection results of all surface partitions of the quality inspection object means setting the grating setting parameters in the digital electronic grating measurement system based on the final value range of all types of electronic grating parameters of each surface partition, and then inputting the physical scanning data of the quality inspection object into the set digital electronic grating measurement system to simulate the detection results obtained when the quality inspection object is detected by a physical electronic grating under the same conditions, thereby obtaining the detection results of all surface partitions of the quality inspection object.

[0074] Physical grating detection has the following difficulties:

[0075] The cost of physical grating inspection is high: the existing quality inspection of automobile exterior parts requires the construction of a dedicated grating review room on a large site, using a dedicated light source with a specific arrangement density and angle, and the light source is a consumable item.

[0076] Physical grating inspection has great limitations: it relies on manual visual inspection by quality inspection engineers, and the inspection results are highly dependent on the quality inspection engineers' experience. Parts need to be inspected repeatedly, and multiple people need to review them at the same time. Because each person stands in a different position, the zebra pattern results seen will be different. The inspection process is time-consuming and incomplete.

[0077] Physical grating inspection is difficult to quantify: the physical inspection results are inspected visually, and the inspection results are difficult to output quantitatively. At the same time, the original design CAD data cannot display the design appearance effect in the same inspection method, and it is impossible to inspect and compare the design effect with the physical effect.

[0078] Therefore, a digital twin electronic grating physical inspection method applied to a digital electronic grating measurement system is introduced here, which includes:

[0079] Import the design CAD model and physical scan data, set the light source surface and electronic grating display density required to display the electronic grating, as well as the visual angle and detection point for detection according to the final value range of all types of electronic grating parameters of each surface partition, and then automatically display the current grating detection results;

[0080] Its method implements the specific functional modules required:

[0081] Data import function module: import original design CAD data model, support IGS, STP and other formats; scan mesh data import, support STL format import;

[0082] Grid data optimization processing module: grid segmentation, grid smoothing, grid optimization;

[0083] Grid alignment processing module: The scanned grid is automatically fitted to the existing CAD product model for best fit alignment;

[0084] Scan mesh and automatically generate surface module: convert mesh data into irregular surface with one click;

[0085] Hexahedron-based grating density setting module: According to the detection needs (i.e. the final value range of all types of electronic grating parameters in each surface partition), the direction and density of grating generation can be set in six directions: up and down, left and right, and front and back;

[0086] Grating library setting and management module: The grating library creates corresponding grating files according to different refraction directions and grating densities;

[0087] Standard detection viewing angle setting module: You can select orthogonal or perspective viewing angle and set the height, angle and distance of the display viewing angle, and store the set parameters as the corresponding detection template. You can save multiple detection templates at the same time;

[0088] Overall inspection module: Automatically generates inspection views based on the parameters set by the standard inspection view angle. The generated inspection views can be manually viewed one by one.

[0089] Specific point detection module: produces single-point detection views by specifying a specific position of the part;

[0090] Coordinate conversion module: set the body coordinates and stamping coordinates, and switch quickly;

[0091] Detection record module: During the automatic or manual detection process, the current detection view can be saved. During automatic detection, the detection record is automatically generated. During manual detection, the record can be saved manually and named.

[0092] Automatic test report generation module: Generate the final test result report with one click based on the test records, which can be saved as PPT or table output.

[0093] The beneficial effects of the above technology are as follows: Step S101 divides the surface into zones according to the distribution of surface materials, enabling targeted detection of different material areas and improving the professionalism of the detection. Step S102 determines the final value range of the electronic grating parameters, so that the detection parameters match the characteristics of the surface zones and ensure the accuracy of the detection. This helps to fully digitize the performance of the electronic grating measurement system and optimize the detection effect. Step S103 uses a specific parameter value range to obtain the partition detection results, which can improve the reliability and validity of the detection data. The overall solution realizes the refined detection of quality inspection objects and improves the quality and efficiency of quality inspection.

[0094] Example 3:

[0095] Based on Example 2, the electronic grating quality inspection and evaluation method based on the digital twin model, S102: Based on the shape of the surface coverage area of ​​each material and the material type, determine the final value range of all surface partitions of the quality inspection object and all types of electronic grating parameters of each surface partition, including:

[0096] Based on the shape and material type of the surface coverage area of ​​each material, a preset electronic grating parameter value range table is retrieved to determine the value ranges of all types of electronic grating parameters of the surface coverage area of ​​each material;

[0097] Based on the value ranges of all types of electronic grating parameters of the surface coverage areas of all materials of the quality inspection object, the final value ranges of all types of electronic grating parameters of all surface partitions of the quality inspection object and each surface partition are determined.

[0098] In this embodiment, the preset electronic grating parameter value range table "preset electronic grating parameter value range table" refers to a table or database that is set and stored in advance. This table contains the possible value ranges of various electronic grating parameters corresponding to surface coverage areas of different shapes and material types. For example, for a circular metal surface area, the applicable electronic grating wavelength may be specified to be 100-200 nanometers, the frequency to be 50-100 Hz, etc.; and for a square plastic surface area, the intensity of the electronic grating may be 20-30 watts, etc. This value range table is determined based on past detection experience, experimental data or theoretical calculations, and is used to quickly determine the appropriate electronic grating parameter range for different material and shape areas during the detection process.

[0099] The benefits of this technology include: By retrieving a parameter range table based on the material's shape and type, a preliminary range of applicable parameters can be quickly obtained, improving work efficiency. The final range is determined by comprehensively considering the parameter ranges across all material coverage areas, ensuring parameter integrity and coordination. This closely integrates electronic grating parameters with material characteristics and surface shape, improving detection accuracy and reliability. This helps optimize the detection performance of the electronic grating, fully utilizing its performance and obtaining more accurate test results. This lays a solid foundation for subsequently obtaining high-quality, zoned test results, thereby enhancing the quality and level of quality inspection work.

[0100] Example 4:

[0101] On the basis of Example 3, the electronic grating quality inspection and evaluation method based on the digital twin model determines the final value range of all types of electronic grating parameters of all surface partitions of the quality inspection object and all types of electronic grating parameters of each surface partition based on the value range of all types of electronic grating parameters of the surface coverage area of ​​all materials of the quality inspection object, including:

[0102] Calculating the merging operability between the surface coverage areas of each two materials of the quality inspection object based on the value ranges of all types of electronic grating parameters of the surface coverage areas of each two materials of the quality inspection object;

[0103] The surface coverage areas of all materials whose mergable operation degree is not less than the operation degree threshold are regarded as all mergable areas;

[0104] Determine all surface partitions of the inspection object based on all mergeable areas;

[0105] The value ranges of the same type of electronic grating parameters of the surface coverage area of ​​each material contained in each surface partition are intersected to obtain the final value range of each type of electronic grating parameter of each surface partition.

[0106] In this embodiment, the merging operability between the surface coverage areas of each two materials of the quality inspection object refers to a quantitative indicator that measures the degree or possibility of merging the surface coverage areas of any two different materials in the quality inspection object, taking into account the value ranges of all types of electronic grating parameters corresponding to each of them.

[0107] In this embodiment, the operability threshold is a pre-set critical value used to determine whether the merging operability is high enough, thereby determining whether the merging operation can be performed. If the merging operability reaches this threshold, it is considered that the surface coverage areas of the corresponding two materials can be merged; otherwise, it is considered that the merging cannot be performed.

[0108] The beneficial effects of the above technology are as follows: By calculating the degree of merging operability, the feasibility of merging surface coverage areas of different materials can be accurately assessed, improving the rationality of zoning. Mergeable areas can be identified, reducing the number of partitions, streamlining the quality inspection process, and improving work efficiency. Surface partitioning is determined based on mergable areas, ensuring that the partitioning better reflects the actual material distribution of the inspection object. The final value range is determined by intersecting the parameter value ranges of the same type of electronic grating, ensuring the accuracy and effectiveness of the parameters. This overall solution helps optimize the surface partitioning and parameter settings of the inspection object, improving the quality and effectiveness of quality inspection.

[0109] Example 5:

[0110] On the basis of Example 4, the electronic grating quality inspection and evaluation method based on the digital twin model calculates the merging operability between the surface coverage areas of each two materials of the quality inspection object based on the value ranges of all types of electronic grating parameters of the surface coverage areas of each two materials of the quality inspection object, including:

[0111] Calculate the ratio of the interval length of the intersection between the value ranges of the same type of electronic grating parameters of the surface coverage areas of each two materials of the quality inspection object and the average value of the interval length of the value ranges of the same type of electronic grating parameters of the surface coverage areas of each two materials of the quality inspection object, and use it as the interval overlap of the value ranges of the corresponding type of electronic grating parameters of the surface coverage areas of each two materials of the quality inspection object;

[0112] The average value of the interval overlap of the value ranges of all types of electronic grating parameters of the surface coverage areas of each two materials of the quality inspection object is regarded as the merging operability between the surface coverage areas of each two materials of the quality inspection object.

[0113] In this embodiment, the intersection interval length refers to the length of the common portion of the value ranges of the same type of electronic raster parameter for the surface coverage area of ​​each of the two materials under inspection. For example, if the electronic raster parameter value range of material A is 10-20 and that of material B is 15-25, then their intersection is 15-20, and the interval length of this intersection is 5.

[0114] The beneficial effects of the above technology are as follows: by calculating the interval overlap, the similarity between the electronic grating parameter value ranges of the surface coverage areas of two materials can be quantified, providing an accurate basis for merging judgments. Using the average value of the interval overlap as the merging operability degree, and comprehensively considering multiple parameter types, the merging judgment is more comprehensive and reliable. This helps to more scientifically determine the mergeable areas and improve the accuracy and rationality of the partitioning. It can more effectively integrate similar material areas, reduce unnecessary partitioning, and simplify the quality inspection process. It provides an important reference indicator for the subsequent determination of the surface partitioning and the final value range of the electronic grating parameters, improving the efficiency and quality of quality inspection.

[0115] Example 6:

[0116] On the basis of Example 4, the electronic grating quality inspection and evaluation method based on the digital twin model determines all surface partitions of the inspection object based on all mergeable areas, including:

[0117] From all the mergable areas, select the mergable areas with more than one mergable operation degree between them and all other mergable areas, and use them as the first-tier merging areas;

[0118] Merge two mergable regions corresponding to the maximum mergable operation degree among all mergable operation degrees that are not less than the operation degree threshold between each first gradient merging region and all other mergable regions to obtain a first merging region;

[0119] determining whether, among all the mergable areas except all the mergable areas included in all the first merging areas, there is at least one group of mergable areas whose corresponding mergable operability is not less than the operability threshold; if so, merging the at least one group of mergable areas whose corresponding mergable operability is not less than the operability threshold to obtain a second merging area; otherwise, retaining the determination result;

[0120] All surface partitions of the quality inspection object are determined based on all the first merged regions and all the second merged regions.

[0121] The benefits of these technologies include: First-tier mergeable regions are screened, prioritizing regions with high merging potential and improving merging efficiency. Merging is performed with the maximum possible degree of merging, ensuring both rationality and effectiveness. Multiple judgments and merges are performed, fully considering all merging-capable regions and optimizing the resulting partitioning. This helps more accurately determine the surface partitioning of inspection objects, improving both accuracy and scientificity. The overall solution effectively integrates merging-capable regions, achieving more rational surface partitioning and providing a sound foundation for subsequent quality inspection work.

[0122] Example 7:

[0123] On the basis of Example 6, the electronic grating quality inspection and evaluation method based on the digital twin model determines all surface partitions of the quality inspection object based on all first merged areas and all second merged areas, including:

[0124] Calculating the merging operability between every two regions in all first merging regions and all second merging regions;

[0125] Determine whether there are two regions with a mergible operability not less than a threshold operability threshold among all the first merged regions and all the second merged regions; if so, merge the two regions with a mergible operability not less than the threshold operability threshold into a third merged region; otherwise, merge all the mergible regions contained in each first merged region into a single surface partition of the quality inspection object; and at the same time, merge all the mergible regions contained in each second merged region into a single surface partition of the quality inspection object;

[0126] Continue to calculate the mergible operation degree between each of the third merged areas until all the newly obtained merged areas do not contain at least one group of merged areas whose mergible operation degree is not less than the operation degree threshold. Then merge all the mergible areas contained in each of the latest merged areas as a single surface partition of the quality inspection object.

[0127] In this embodiment, the merging operability between each two regions refers to a quantitative value of the degree or possibility of merging any two regions selected from all first merging regions and all second merging regions, obtained by a specific calculation method.

[0128] In this embodiment, calculating the degree of merging operability between any two third merging regions means combining already formed third merging regions in pairs again and calculating the degree of merging operability between them according to the same calculation rule.

[0129] The benefits of this technology include: Multiple calculations of the mergeability allow for a comprehensive and detailed assessment of the potential for merging between regions. Continuous merging judgments and operations maximize the integration of similar regions and optimize surface partitioning. This ensures that the final surface partitioning results fully account for all possible merging scenarios, improving the rationality and accuracy of the partitioning. This effectively reduces the number of partitions, making them simpler and clearer, facilitating subsequent quality inspection. Repeated merging until stable ensures the stability and reliability of the partitioning results, improving the quality of the surface partitioning of the inspection object.

[0130] Example 8:

[0131] On the basis of Example 7, the electronic grating quality inspection and evaluation method based on the digital twin model calculates the merging operability between each two areas in all first merging areas and all second merging areas, including:

[0132] The ratio of the interval length of the intersection between the value ranges of the same type of electronic grating parameters of all mergable areas contained in every two areas of all the first merged areas and all the second merged areas to the average value of the interval lengths of the value ranges of the same type of electronic grating parameters of the two corresponding areas is regarded as the interval overlap of the value ranges of the corresponding type of electronic grating parameters of the two corresponding areas;

[0133] The average value of the interval overlap of the value ranges of all types of electronic grating parameters of every two areas in all the first merging areas and all the second merging areas is regarded as the merging operability between every two areas in all the first merging areas and all the second merging areas.

[0134] The beneficial effects of the above technology are as follows: by calculating the interval overlap, the similarity of the electronic grating parameter value ranges between regions is accurately quantified, providing a precise basis for merging judgments. Using the average value of the interval overlap as the merging operability degree, and comprehensively considering multiple parameter types, merging judgments are more comprehensive and accurate. This helps to more scientifically and rationally determine the possibility of merging between regions, improving the reliability of merging decisions. It can more effectively identify and merge highly similar regions, optimizing the partition structure. This provides strong support for more accurate and efficient surface partitioning of quality inspection objects, improving the quality and effectiveness of partitioning.

[0135] Example 9:

[0136] On the basis of Example 1, the electronic grating quality inspection and evaluation method based on the digital twin model, S2: all the partition inspection results of the quality inspection object are aligned with the standard morphological twin model of the quality inspection object, and the quality inspection evaluation reference data of each partition inspection result is obtained. Figure 3 ,include:

[0137] S201: Determine appearance morphology data of each surface partition of the quality inspection object based on the detection result of each partition of the quality inspection object;

[0138] S202: Based on the appearance morphological data of all surface partitions of the quality inspection object, all partition detection results of the quality inspection object are aligned with the standard morphological twin model of the quality inspection object, and the quality inspection evaluation reference data of each partition detection result is determined in the standard morphological twin model of the quality inspection object.

[0139] In this embodiment, the appearance morphological data of each surface partition of the quality inspection object refers to the specific data information extracted from the detection results of each partition of the quality inspection object, which describes the appearance aspects such as shape, size, contour, surface features, etc. of each individual surface partition of the quality inspection object.

[0140] In this embodiment, based on the appearance morphology data of all surface partitions of the quality inspection object, the inspection results of all partitions of the quality inspection object are aligned with the standard morphology twin model of the quality inspection object. The quality inspection evaluation reference data of each partition inspection result is determined in the standard morphology twin model of the quality inspection object. This means that based on the detailed appearance morphology data of each surface partition of the quality inspection object, the results of each partition obtained by actual inspection are carefully matched and matched with the twin model of the standard morphology. Through this precise local comparison process, the reference basis for evaluating the inspection results of each partition is clearly identified in the standard morphology twin model, such as the standard size range, the allowable degree of defects, etc.

[0141] To carefully match the results of each partition obtained from the actual detection with the twin model of the standard form, you can follow the following steps:

[0142] Organize and categorize the actual inspection results for each partition. This includes shape and dimension measurement data, surface defect detection data, and more. Ensure the accuracy and completeness of the data and convert it into a format suitable for comparison with the twin model. For example, organize the measurement data into a table that lists key dimensional parameters, defect type, and location for each partition.

[0143] Load a standard twin model into computer software. Ensure the model's accuracy and completeness, and ensure it corresponds to the actual object being inspected. Use professional 3D modeling software or a digital twin platform to load and manipulate the twin model. For example, use CAD software to load a twin model of a mechanical part, or an industrial IoT platform to load a twin model of production equipment.

[0144] In both the actual inspection results and the twin model, uniquely identify each partition. This can be a numeric number, an alphabetic code, or a specific name. Ensure that the identifiers are consistent between the actual inspection and the twin model to ensure accurate correspondence and matching. For example, in an automobile body inspection, each panel can be assigned a unique number, and the same number can be used to identify the corresponding panel in the twin model.

[0145] Ensure that the actual inspection results and the twin model use the same coordinate system. If the actual inspection is performed in a specific coordinate system, the twin model's coordinate system must be adjusted to align with the actual inspection coordinate system. For example, in machining, the actual inspection may be performed in the machine tool coordinate system, while the twin model may be in the design coordinate system. Using a coordinate transformation algorithm, the twin model's coordinate system can be adjusted to align with the machine tool coordinate system for accurate alignment and matching.

[0146] For each partition, the shape and size data obtained from actual inspection are compared with the corresponding data in the twin model. Numerical comparisons, graphical visualizations, and other methods can be used to intuitively display differences. For example, in 3D modeling software, the dimensions of a part obtained from actual inspection can be overlaid with those in the twin model, with dimensional differences indicated through color coding or measurement tools. Dimensional differences that fall outside the tolerance range can be marked and recorded for subsequent analysis and processing.

[0147] Match the actual detected surface defects with the corresponding areas in the twin model. Technologies such as image recognition and feature extraction can be used to automatically identify and match surface defects. For example, in electronic product inspection, image analysis software can be used to extract features from detected screen scratches. These features can then be matched against the screen areas in the twin model to determine the scratch's location and severity. Defects that cannot be automatically matched can be manually intervened and confirmed.

[0148] Record and analyze the comparison and matching results for each partition. Use tables, charts, and other formats to summarize the data, providing a clear understanding of each partition's quality status and differences from the standard. For example, create a quality report that lists each partition's key dimensional parameters, defect types, and differences from the standard. By analyzing this data, you can determine the severity and distribution of quality issues, providing a basis for subsequent quality improvements.

[0149] Based on actual test results and changes in the production process, the twin model is regularly updated and optimized. This can include adjusting model parameters, adding new features, or improving the model's accuracy. For example, as products continue to improve and upgrade, the twin model can be updated based on new design changes to ensure consistency with the actual product. At the same time, by collecting more actual test data, the model can be optimized and trained to improve its accuracy and predictive capabilities. Through these steps, a detailed correspondence and matching between actual test results and the standard twin model can be achieved, providing strong support for product quality control and improvement.

[0150] The beneficial effects of the above technology are as follows: Step S201 can accurately determine the appearance morphological data of each surface partition based on the partition detection results, providing detailed basic information for subsequent evaluation. This helps to more accurately understand the specific morphological characteristics of each partition and improve the targeted quality inspection. Step S202 performs overall alignment based on the appearance morphological data of all surface partitions, making the determination of quality inspection and evaluation reference data more accurate and reliable. It can fully combine the actual partitioning situation of the quality inspection object with the standard morphological twin model to improve the scientific nature and effectiveness of the quality inspection and evaluation. The overall solution helps to improve the accuracy and efficiency of quality inspection and evaluation and ensure the reliability of quality inspection results.

[0151] Example 10:

[0152] On the basis of Example 1, the electronic grating quality inspection and evaluation method based on the digital twin model, S3: Compare the detection results of each partition of the quality inspection object with the corresponding quality inspection and evaluation reference data to obtain the quality inspection and evaluation results of the quality inspection object, and refer to Figure 4 ,include:

[0153] S301: Compare the inspection result of each partition of the quality inspection object with the corresponding quality inspection evaluation reference data to obtain the quality inspection result of each surface partition of the quality inspection object;

[0154] S302: Summarize and integrate the quality inspection results of all surface partitions of the quality inspection object to obtain a quality inspection evaluation result of the quality inspection object.

[0155] In this embodiment, the quality inspection result of the surface partition refers to the conclusion about the quality of each individual surface partition of the quality inspection object obtained by comparing its partition inspection result with the corresponding quality inspection evaluation reference data, such as whether it is qualified, what defects exist and the degree of defects.

[0156] In this embodiment, the quality inspection results for all surface zones of the inspection object are aggregated and integrated to obtain the quality inspection assessment result of the inspection object. This means collecting the specific quality inspection conclusions for each surface zone of the inspection object and conducting a comprehensive analysis and compilation. By comprehensively considering the quality inspection results of all zones, an overall evaluation of the quality of the inspection object is obtained, such as whether the object is generally qualified and the main quality issues.

[0157] The beneficial effects of the above technology are as follows: Step S301 can produce independent and accurate quality inspection results for each partition, achieving a detailed assessment of the local quality of the inspection object. This helps to quickly locate specific partitions with quality issues and improve the efficiency of problem solving. The summary and integration in step S302 can grasp the quality level of the inspection object from a holistic perspective, avoiding focusing on the details while ignoring the overall situation. This provides a reliable basis for comprehensively and comprehensively determining whether the inspection object is qualified. The overall solution not only ensures the accuracy of quality inspection but also achieves effective control of overall quality, thereby improving the quality and value of quality inspection work.

[0158] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. The electronic grating quality inspection and evaluation method based on the digital twin model is characterized by: include: S1: Input the physical scan data of the inspection object into the digital electronic raster measurement system to obtain all the partition inspection results of the inspection object, including: S101: partitioning the outer surface of the inspection object based on the surface material distribution of the inspection object to obtain the surface coverage area of ​​each material; S102: Based on the shape of the surface coverage area of ​​each material and the material type, determine the final value range of all surface partitions of the quality inspection object and all types of electronic grating parameters of each surface partition, including: Calculating the merging operability between the surface coverage areas of each two materials of the quality inspection object based on the value ranges of all types of electronic grating parameters of the surface coverage areas of each two materials of the quality inspection object; The surface coverage areas of all materials whose mergable operation degree is not less than the operation degree threshold are regarded as all mergable areas; Determine all surface partitions of the inspection object based on all mergeable areas; S103: inputting the physical scan data of the inspection object into a digital electronic grating measurement system set based on the final value range of all types of electronic grating parameters of each surface partition, and obtaining partition detection results of all surface partitions of the inspection object; S2: Align all partition test results of the quality inspection object with the standard morphological twin model of the quality inspection object to obtain quality inspection evaluation reference data for each partition test result; S3: Compare the detection result of each partition of the quality inspection object with the corresponding quality inspection evaluation reference data to obtain the quality inspection evaluation result of the quality inspection object.

2. The electronic grating quality inspection and evaluation method based on the digital twin model according to claim 1 is characterized in that: Based on the value ranges of all types of electronic grating parameters of the surface coverage areas of each two materials of the quality inspection object, the merging operability between the surface coverage areas of each two materials of the quality inspection object is calculated, including: Calculate the ratio of the interval length of the intersection between the value ranges of the same type of electronic grating parameters of the surface coverage areas of each two materials of the quality inspection object and the average value of the interval length of the value ranges of the same type of electronic grating parameters of the surface coverage areas of each two materials of the quality inspection object, and use it as the interval overlap of the value ranges of the corresponding type of electronic grating parameters of the surface coverage areas of each two materials of the quality inspection object; The average value of the interval overlap of the value ranges of all types of electronic grating parameters of the surface coverage areas of each two materials of the quality inspection object is regarded as the merging operability between the surface coverage areas of each two materials of the quality inspection object.

3. The electronic grating quality inspection and evaluation method based on the digital twin model according to claim 1 is characterized in that: All surface partitions of the inspection object are determined based on all mergeable areas, including: From all the mergable areas, select the mergable areas with more than one mergable operation degree between them and all other mergable areas, and use them as the first-tier merging areas; Merge two mergable regions corresponding to the maximum mergable operation degree among all mergable operation degrees that are not less than the operation degree threshold between each first gradient merging region and all other mergable regions to obtain a first merging region; determining whether, among all the mergable areas except all the mergable areas included in all the first merging areas, there is at least one group of mergable areas whose corresponding mergable operability is not less than the operability threshold; if so, merging the at least one group of mergable areas whose corresponding mergable operability is not less than the operability threshold to obtain a second merging area; otherwise, retaining the determination result; All surface partitions of the quality inspection object are determined based on all the first merged regions and all the second merged regions.

4. The electronic grating quality inspection and evaluation method based on the digital twin model according to claim 3 is characterized in that: All surface partitions of the inspection object are determined based on all first merged regions and all second merged regions, including: Calculating the merging operability between every two regions in all first merging regions and all second merging regions; Determine whether there are two regions with a mergable operability not less than a threshold operability threshold among all the first merged regions and all the second merged regions; if so, merge the two regions with a mergable operability not less than the threshold operability threshold into a third merged region; otherwise, merge all the mergable regions contained in each first merged region into a single surface partition of the quality inspection object; and at the same time, merge all the mergable regions contained in each second merged region into a single surface partition of the quality inspection object; Continue to calculate the mergible operation degree between each of the third merged areas until all the newly obtained merged areas do not contain at least one group of merged areas whose mergible operation degree is not less than the operation degree threshold. Then merge all the mergible areas contained in each of the latest merged areas as a single surface partition of the quality inspection object.

5. The electronic grating quality inspection and evaluation method based on the digital twin model according to claim 4 is characterized in that: Calculate the merging operability between each two regions in all first merged regions and all second merged regions, including: The ratio of the interval length of the intersection between the value ranges of the same type of electronic grating parameters of all mergable areas contained in every two areas of all the first merged areas and all the second merged areas to the average value of the interval lengths of the value ranges of the same type of electronic grating parameters of the two corresponding areas is regarded as the interval overlap of the value ranges of the corresponding type of electronic grating parameters of the two corresponding areas; The average value of the interval overlap of the value ranges of all types of electronic grating parameters of every two areas in all the first merging areas and all the second merging areas is regarded as the merging operability between every two areas in all the first merging areas and all the second merging areas.

6. The electronic grating quality inspection and evaluation method based on the digital twin model according to claim 1 is characterized in that: S2: Align all partitioned inspection results of the inspection object with the standard morphological twin model of the inspection object to obtain quality inspection evaluation reference data for each partitioned inspection result, including: S201: Determine appearance morphology data of each surface partition of the quality inspection object based on the detection result of each partition of the quality inspection object; S202: Based on the appearance morphological data of all surface partitions of the quality inspection object, all partition detection results of the quality inspection object are aligned with the standard morphological twin model of the quality inspection object, and the quality inspection evaluation reference data of each partition detection result is determined in the standard morphological twin model of the quality inspection object.

7. The electronic grating quality inspection and evaluation method based on the digital twin model according to claim 1 is characterized in that: S3: Compare the test results of each partition of the quality inspection object with the corresponding quality inspection evaluation reference data to obtain the quality inspection evaluation results of the quality inspection object, including: S301: Compare the inspection result of each partition of the quality inspection object with the corresponding quality inspection evaluation reference data to obtain the quality inspection result of each surface partition of the quality inspection object; S302: Summarize and integrate the quality inspection results of all surface partitions of the quality inspection object to obtain a quality inspection evaluation result of the quality inspection object.

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