Skin defect detection method

Abstract

The invention provides a skin defect detection method which comprises the following steps: collecting pit defect data and surrounding structure feature data of a skin, the surrounding structure feature data being feature data of a reference object around a pit; structural parameters of the skin are obtained from a preset theoretical model of the skin, and the skin represented by the theoretical model comprises a reference object and does not have defects; according to the pit defect data, the surrounding structure feature data and the structure parameters, defect feature data are obtained through calculation, wherein the defect feature data comprise at least one of the pit position, the pit depth, the pit radius, the pit contour, the pit smoothness and the distance between the pit and the nail line. According to the invention, the efficiency and accuracy of skin defect detection are improved, so that the efficiency and accuracy of skin maintenance are improved.

Description

Technical Field

[0001] The invention relates to the technical field of nondestructive testing, and in particular to a skin defect detection method. Background Art

[0002] In the manufacturing, use and maintenance of aerospace, automobile, shipbuilding, wind power generation, construction, rail transportation, national defense and military industries, the skin is prone to pit defects due to external forces or other reasons. The conventional treatment method for skin pits is to detect and evaluate the defects manually or semi-automatically, so as to formulate corresponding concession acceptance or maintenance plans.

[0003] The purely manual processing method usually uses a manual method to measure the pit shape, depth, radius, and distance from the pit center to the connecting nail line and other characteristic dimensions with the help of translucent paper, rulers and other tools. The measurement data is then submitted to the design department for evaluation and a repair or acceptance plan is formulated. The semi-automatic method is usually that the manufacturing or maintenance site staff uses manual methods or semi-automatic tools such as scanners to complete the pit feature data measurement. The measurement data is then transmitted to the design department or semi-automatic evaluation system for rapid evaluation, and then a repair or acceptance plan is formulated.

[0004] However, both manual measurement and semi-automatic scanning require manual input of multiple characteristic parameters of the pits and transfer them to the designer or input evaluation system to complete the defect evaluation. The process is cumbersome and inefficient. In addition, the manual measurement or input of defect characteristic data has a low degree of standardization and there is a risk of measurement or recording errors. Therefore, the present invention provides a skin defect detection method to solve the above problems. Summary of the invention

[0005] The object of the present invention is to provide a skin defect detection method to improve the efficiency and accuracy of skin defect detection, thereby improving the efficiency and accuracy of skin repair.

[0006] In order to achieve the purpose of the present invention, the technical solution adopted by the present invention is: A skin defect detection method comprises the following steps: Collecting pit defect data and surrounding structure feature data, wherein the surrounding structure feature data is feature data of a reference object surrounding the pit; Acquiring structural parameters of the skin from a preset theoretical model of the skin, wherein the skin represented by the theoretical model includes a reference object and has no defects; Defect feature data is calculated based on the pit defect data, the surrounding structure feature data and the structure parameters, and the defect feature data includes at least one of the pit position, pit depth, pit radius, pit contour, pit smoothness and the distance between the pit and the nail line.

[0007] Further, defect feature data is calculated based on the pit defect data, the surrounding structure feature data and the structure parameters, including: Generate a skin model according to the pit defect data and the surrounding structure feature data; Aligning the skin model with the theoretical model to obtain a reference model; The reference model is used to perform calculation based on the pit defect data, the surrounding structure feature data and the structure parameters to obtain defect feature data.

[0008] Furthermore, after the defect characteristic data is calculated according to the pit defect data, the surrounding structure characteristic data and the structure parameter, the method further includes: Acquiring strength evaluation conditions, wherein the strength evaluation conditions include a plurality of preset limiting values, and the limiting values ​​are used to indicate data boundaries where strength evaluation of pit defects needs to be performed; Determining whether strength assessment is required according to the defect characteristic data and the strength assessment condition; Determine the pit defect treatment method based on the strength assessment results.

[0009] Furthermore, after aligning the skin model with a preset theoretical model to obtain a reference model, the method further includes: calculating the alignment between the skin model and the theoretical model; determining whether the alignment is within an evaluable range; If the alignment degree is within the evaluable range, the detection continues; if the alignment degree is not within the evaluable range, a prompt is given to regenerate the skin model.

[0010] Further, judging whether strength assessment is required according to the defect characteristic data and the strength assessment condition includes: Comparing the defect feature data with the strength assessment condition, and obtaining a strength assessment result that needs to be strength assessed if the defect feature data meets the strength assessment condition; If the defect characteristic data does not meet the strength evaluation condition, a strength evaluation result that does not require strength evaluation is obtained.

[0011] Further, comparing the defect characteristic data with the strength evaluation condition includes: Comparing the defect characteristic data with the strength evaluation conditions to obtain a number of judgment results; Whether the defect characteristic data meets the strength evaluation condition is determined according to a plurality of the determination results.

[0012] Furthermore, the defect characteristic data is compared with the strength evaluation condition to obtain several judgment results, including: If the defect feature data meets the strength evaluation condition, the judgment result is 1; if the defect feature data does not meet the strength evaluation condition, the judgment result is 0.

[0013] Further, judging whether the defect characteristic data meets the strength assessment condition according to a plurality of the judgment results includes: Screening a number of the judgment results; When several of the judgment results are all 0, the defect feature data does not meet the strength evaluation condition; otherwise, the defect feature data meets the strength evaluation condition.

[0014] Furthermore, the pit defect treatment method is determined based on the strength evaluation results, including: When strength assessment is required, the defect characteristic data is sent to a terminal device of a strength assessor so that the strength assessor can perform strength assessment; When strength evaluation is not required, the defect characteristic data is directly sent to the terminal device of the on-site maintenance personnel to prompt the on-site maintenance personnel to handle the pit defect.

[0015] Furthermore, the data of the pit defects and surrounding structural characteristics of the skin are collected, including: Scan the pit with a scanner to obtain point cloud data of the pit; The reference objects around the pit are scanned by a scanner to obtain surrounding structural feature data, wherein the reference objects include at least one of a mounting hole on the skin, an edge on the skin, and a corner on the skin.

[0016] Beneficial effects of the present invention: 1. The present invention collects the pit defect data and surrounding structure feature data of the skin, obtains the structural parameters of the skin from a preset theoretical model of the skin, and then calculates the defect feature data based on the pit defect data, surrounding structure feature data and structural parameters, thereby completing the measurement of the pit defect and improving the efficiency and accuracy of skin defect detection and processing.

[0017] 2. The present invention reduces manual measurement and input operations in the data calculation and recording process, effectively avoids manual input errors, improves the efficiency and accuracy of skin defect detection, and thus improves the efficiency and accuracy of skin repair. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 The present invention is an overall flow chart of a skin defect detection method.

[0019] Figure 2This is a schematic diagram of an application of a skin defect detection method of the present invention.

[0020] Figure 3 for Figure 2 A top view of the skin in Figure 1.

[0021] Figure 4 for Figure 2 AA section view.

[0022] Figure 5 It is a flow chart of detecting and processing skin dents according to an embodiment of the present invention.

[0023] Description of reference numerals: 1. Scanner; 2. Pit; 3. Mounting hole; 4. Skin. DETAILED DESCRIPTION

[0024] In order to make the purpose, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. Unless otherwise defined, the technical terms or scientific terms used herein should be understood by people with general skills in the field to which the present invention belongs. "Including" and similar words used in this article mean that the elements or objects appearing before the word include the elements or objects listed after the word and their equivalents, without excluding other elements or objects.

[0025] This embodiment provides a skin defect detection method, referring to Figure 1 and Figure 2 , the skin defect detection method comprises the following steps: S1: collecting defect data of the pit 2 of the skin 4 and surrounding structural feature data, where the surrounding structural feature data is feature data of reference objects around the pit 2; When it is found that the skin 4 has defects, first collect the image data of the pit 2 and store and record the image data of the pit 2, make a preliminary judgment on the skin 4 defect based on the image data of the pit 2, and judge whether the skin 4 defect is within the range that the on-site maintenance personnel can handle based on the image data of the pit 2. If the skin 4 defect is within the range that the on-site maintenance personnel can handle, it will be handed over to the on-site maintenance personnel for processing. The on-site maintenance personnel can choose to directly repair the skin 4 defect, or continue to detect to obtain more data before repairing. If the skin 4 defect is not within the range that the on-site maintenance personnel can handle, further detection is performed to obtain the data required by the strength assessor for evaluation and send it to the strength assessor. When further detection is required, the detection personnel scan the pit 2 through the optical scanner 1 to obtain the pit 2 defect data of the skin 4, that is, the point cloud data of the pit 2, and then scan the reference objects around the pit 2 through the optical scanner 1 to obtain the surrounding structural feature data, and the reference objects include at least one of the mounting holes 3 on the skin 4 around the skin 4 defect, the edges on the skin 4, and the corners on the skin 4.

[0026] S2: obtaining structural parameters of the skin 4 from a preset theoretical model of the skin 4, wherein the skin 4 represented by the theoretical model includes a reference object and has no defects; When designing and manufacturing the skin 4, the structural parameters of the skin 4 are recorded and saved in the theoretical model. The structural parameters of the skin 4 are the material thickness, size specification parameters, etc. of the skin 4. The structural parameters of the skin 4 are obtained from the preset theoretical model as reference data for subsequent inspection. The skin 4 represented by the theoretical model includes a reference object and has no defects.

[0027] S3: Defect feature data is calculated based on the defect data of pit 2, surrounding structural feature data and structural parameters, and the defect feature data includes at least one of the position of pit 2, depth of pit 2, radius of pit 2, contour of pit 2, smoothness of pit 2 and the distance between pit 2 and the nail line, wherein the distance between pit 2 and the nail line is the shortest distance between the edge of pit 2 and the rivet, and the rivet is used to penetrate the mounting hole on the skin to fix the skin to the frame.

[0028] Reference Figure 3 and Figure 4 , generate the skin 4 model according to the pit 2 defect data and the surrounding structure feature data, align the skin 4 model with the theoretical model to obtain the reference model, calculate the alignment between the skin 4 model and the theoretical model, and judge whether the alignment is within the evaluable range. If the alignment is within the evaluable range, continue the test; if the alignment is not within the evaluable range, prompt to regenerate the skin 4 model. Calculate the defect feature data based on the pit 2 defect data, the surrounding structure feature data and the structural parameters using the reference model. Store and record the defect feature data for subsequent strength assessment personnel to facilitate evaluation.

[0029] S4: Obtain strength evaluation conditions, which include several preset limit values, where the limit values ​​are used to indicate the data boundaries where strength evaluation of the pit 2 defect is required, determine whether strength evaluation is required based on defect feature data and the strength evaluation conditions, and determine a method for handling the pit 2 defect based on the strength evaluation result.

[0030] Reference Figure 3 and Figure 5 After obtaining the defect feature data, continue to obtain the strength assessment conditions, which include several preset limit values, wherein the limit values ​​are used to indicate the data boundaries that require strength assessment of the pit 2 defect. Compare the defect feature data with the strength assessment conditions to obtain several judgment results. If the defect feature data meets the strength assessment conditions, the judgment result is 1, and if the defect feature data does not meet the strength assessment conditions, the judgment result is 0. Determine whether the defect feature data meets the strength assessment conditions based on several judgment results. Screen several judgment results. When several judgment results are all 0, the defect feature data does not meet the strength assessment conditions, otherwise the defect feature data meets the strength assessment conditions. If the defect feature data meets the strength assessment conditions, a strength assessment result that requires strength assessment is obtained; if the defect feature data does not meet the strength assessment conditions, a strength assessment result that does not require strength assessment is obtained. When strength assessment is required, the defect feature data is sent to the terminal device of the strength assessor to enable the strength assessor to perform strength assessment; when strength assessment is not required, the defect feature data is directly sent to the terminal device of the on-site maintenance personnel to prompt the on-site maintenance personnel to handle the pit 2 defect.

[0031] The following is an example of detecting a pit on the skin 4. Figure 2 and Figure 5 , for specific instructions: During the manufacturing process, a dent 2 is produced in the wall panel of the skin 4 due to a collision, and the dent is now tested and evaluated.

[0032] Step 1: Collect the pit 2 defect data of the skin 4 and the surrounding structure feature data.

[0033] First, the inspector uses an optical scanner 1, such as a structured light scanner 1, to scan the wall panel of the skin 4 to obtain point cloud data of the pit 2 defect, and then scans the point cloud data of the reference objects around the pit 2 defect, such as the point cloud data of the mounting holes 3, edges, corners, etc. on the skin 4 around the pit 2 defect, for subsequent defect feature extraction.

[0034] Step 2: Obtain the structural parameters of skin 4 from the preset theoretical model of skin 4.

[0035] When designing and manufacturing the skin 4, the structural parameters of the skin 4 are recorded and saved in a theoretical model, and the structural parameters of the skin 4 are obtained from the preset theoretical model of the skin 4 as reference data for subsequent testing.

[0036] The third step is to calculate the defect characteristic data based on the defect data of pit 2, the surrounding structure characteristic data and the structure parameters.

[0037] Combination Figure 3 and Figure 4 , generate the skin 4 model according to the collected pit 2 defect data and surrounding structure feature data, align the skin 4 model with the theoretical model. In this embodiment, four key holes (P1-P4) are used as features for aligning the skin 4 model with the theoretical model. Calculate the alignment between the skin 4 model and the theoretical model, and determine whether the alignment is within the evaluable range. If the alignment is within the evaluable range, continue the detection. If the alignment is not within the evaluable range, prompt to regenerate the skin 4 model. After the skin 4 model is aligned with the theoretical model, a reference model is obtained, and the reference model is used to perform calculations based on the pit 2 defect data, the surrounding structure feature data and the structural parameters to obtain the defect feature data.

[0038] In this embodiment, the reference model is used to calculate the minimum envelope circle diameter D of pit 2, the distance l between pit 2 and the nail connection positioning line, and the depth d of pit 2 based on the defect data of pit 2, the surrounding structural feature data and the structural parameters. The depth d of pit 2 includes the depth of pit 2 at different positions of the pit. According to the depth of pit 2 at different positions of the pit, it can be judged whether wrinkles, cracks or holes appear in the pit.

[0039] Step 4: Obtain strength assessment conditions. The strength assessment conditions are used to indicate the data range for which strength assessment of the pit 2 defect is required. Determine whether strength assessment is required based on the defect characteristic data and the strength assessment conditions. Determine the treatment method for the pit 2 defect based on the strength assessment result.

[0040] In this embodiment, the strength evaluation conditions are specifically: Condition 1: Depth of pit 2 d>2mm; Condition 2: The minimum enveloping circle diameter D of pit 2>100mm; Condition 3: The distance between pit 2 and the nail line is l<2D; Condition 4: Any of sharp wrinkles, cracks or holes appears.

[0041] According to condition 1, if the depth of pit 2 d>2mm, condition 1 is met and judgment result 1 is obtained, otherwise judgment result 0 is obtained; according to condition 2, if the minimum enveloping circle diameter of pit 2 D>100mm, condition 2 is met and judgment result 1 is obtained, otherwise judgment result 0 is obtained; according to condition 3, if the distance l between pit 2 and nail line is <2D, condition 3 is met and judgment result 1 is obtained, otherwise judgment result 0 is obtained; according to condition 4, if any of sharp wrinkles, cracks or holes appears, condition 4 is met and judgment result 1 is obtained, otherwise judgment result 0 is obtained. Thus, four judgment results are obtained, and the four judgment results are screened and judged. When several judgment results are 0, the defect feature data does not meet the strength assessment condition, otherwise the defect feature data meets the strength assessment condition. If the defect feature data meets the above-mentioned strength assessment condition, the defect feature data is sent to the terminal device of the strength assessor so that the strength assessor can perform strength assessment, and the strength assessor completes the defect assessment and issues a maintenance plan, which is then passed to the on-site maintenance personnel to complete the maintenance process. If the defect characteristic data does not meet the above strength evaluation conditions, it is directly sent to the terminal device of the on-site maintenance personnel to prompt the on-site maintenance personnel to handle the defect of pit 2. The data report formed after processing is archived and the maintenance record is updated.

[0042] Beneficial effects of the present invention: 1. The present invention collects the pit 2 defect data and the surrounding structural feature data of the skin 4, obtains the structural parameters of the skin 4 from a preset theoretical model of the skin 4, and then calculates the defect feature data according to the pit 2 defect data, the surrounding structural feature data and the structural parameters, thereby completing the measurement of the pit 2 defect and improving the efficiency and accuracy of the skin 4 defect detection and processing.

[0043] 2. The present invention reduces manual measurement and input operations in the data calculation and recording process, effectively avoids manual input errors, improves the efficiency and accuracy of skin 4 defect detection, and thus improves the efficiency and accuracy of skin 4 maintenance.

[0044] It should be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of further restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0045] 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 adopt the form of a complete hardware embodiment, a complete software embodiment or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0046] Although the embodiments of the present invention are described in detail above, it is obvious to those skilled in the art that various modifications and variations can be made to these embodiments. However, it should be understood that such modifications and variations are within the scope and spirit of the present invention described in this application. Moreover, the present invention described herein may have other embodiments and may be implemented or realized in a variety of ways.

Claims

1. A skin defect detection method, characterized in that: include: Collecting defect data of the pit (2) of the skin (4) and surrounding structural feature data, wherein the surrounding structural feature data is feature data of a reference object around the pit (2); Acquiring structural parameters of the skin (4) from a preset theoretical model of the skin (4), wherein the skin (4) represented by the theoretical model includes a reference object and has no defects; Defect feature data is calculated based on the pit (2) defect data, the surrounding structure feature data and the structure parameters, and the defect feature data includes at least one of the pit (2) position, pit (2) depth, pit (2) radius, pit (2) contour, pit (2) smoothness and the distance between the pit (2) and the nail line.

2. A skin defect detection method according to claim 1, characterized in that: Defect characteristic data is obtained by calculation based on the defect data of the pit (2), the surrounding structural characteristic data and the structural parameters, including: Generating a skin (4) model according to the pit (2) defect data and the surrounding structure feature data; Aligning the skin (4) model with the theoretical model to obtain a reference model; The reference model is used to perform calculations based on the pit (2) defect data, the surrounding structure feature data and the structure parameters to obtain defect feature data.

3. A skin defect detection method according to claim 1, characterized in that: After the defect characteristic data is calculated based on the defect data of the pit (2), the surrounding structural characteristic data and the structural parameters, the method further comprises: Acquiring strength evaluation conditions, wherein the strength evaluation conditions include a plurality of preset limiting values, wherein the limiting values ​​are used to indicate data boundaries for which strength evaluation of the pit (2) defect is required; Determining whether strength assessment is required according to the defect characteristic data and the strength assessment condition; The method for handling the pit (2) defect is determined based on the strength evaluation results.

4. A skin defect detection method according to claim 2, characterized in that: After aligning the skin (4) model with a preset theoretical model to obtain a reference model, the method further includes: Calculating the alignment between the skin (4) model and the theoretical model; determining whether the alignment is within an evaluable range; If the alignment is within the evaluable range, the detection continues; if the alignment is not within the evaluable range, a prompt is given to regenerate the skin (4) model.

5. A skin defect detection method according to claim 3, characterized in that: Determining whether strength assessment is required according to the defect characteristic data and the strength assessment condition includes: Comparing the defect feature data with the strength assessment condition, and obtaining a strength assessment result that needs to be strength assessed if the defect feature data meets the strength assessment condition; If the defect characteristic data does not meet the strength evaluation condition, a strength evaluation result that does not require strength evaluation is obtained.

6. A skin defect detection method according to claim 5, characterized in that: Comparing the defect characteristic data with the strength assessment condition includes: Comparing the defect characteristic data with the strength evaluation conditions to obtain a number of judgment results; Whether the defect characteristic data meets the strength evaluation condition is determined according to a plurality of the determination results.

7. A skin defect detection method according to claim 6, characterized in that: Comparing the defect characteristic data with the strength evaluation conditions to obtain several judgment results, including: If the defect feature data meets the strength evaluation condition, the judgment result is 1; if the defect feature data does not meet the strength evaluation condition, the judgment result is 0.

8. A skin defect detection method according to claim 7, characterized in that: Judging whether the defect characteristic data meets the strength assessment condition according to a plurality of the judgment results includes: Screening a number of the judgment results; When several of the judgment results are all 0, the defect feature data does not meet the strength evaluation condition; otherwise, the defect feature data meets the strength evaluation condition.

9. A skin defect detection method according to claim 3, characterized in that: Determining the pit (2) defect treatment method based on the strength evaluation result also includes: When strength assessment is required, the defect characteristic data is sent to a terminal device of a strength assessor so that the strength assessor can perform strength assessment; When strength assessment is not required, the defect characteristic data is directly sent to the terminal device of the on-site maintenance personnel to prompt the on-site maintenance personnel to handle the pit (2) defect.

10. A skin defect detection method according to claim 1, characterized in that: Collecting defect data of the pit (2) of the skin (4) and characteristic data of the surrounding structure, including: Scanning the pit (2) with a scanner (1) to obtain point cloud data of the pit (2); A scanner (1) is used to scan reference objects around the pit (2) to obtain surrounding structural feature data, wherein the reference objects include at least one of a mounting hole (3) on the skin (4), an edge on the skin (4), and a corner on the skin (4).

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