Method for evaluating safety margin of skin dent

Abstract

The present application relates to a method for evaluating a safety margin of a skin defect, comprising: collecting dent defect data and surrounding structure feature data; on the basis of the dent defect data and the surrounding structure feature data, constructing a skin geometric model; on the basis of the surrounding structure feature data, aligning the skin geometric model with a preset ideal digital model to obtain a check model boundary; performing model segmentation along the check model boundary to obtain a check model with defects; and on the basis of the check model with defects, performing safety margin evaluation to obtain a safety margin. The method for evaluating a safety margin of a skin dent of the present application can be used to improve the efficiency of performing strength evaluation for a skin dent.

Description

Safety margin assessment method for skin dent Cross-referencing

[0001] This application claims priority to Chinese application No. 2024118373931, filed on December 12, 2024. The contents of the above application are incorporated herein by reference. Technical Field

[0002] This application relates to the field of nondestructive testing technology, and in particular to a method for assessing the safety margin of skin dents. Background Technology

[0003] In the manufacturing, use, and maintenance of aerospace, automotive, shipbuilding, wind power, construction, rail transportation, and defense industries, skin panels are prone to dents due to external forces or other reasons. When dents occur on the skin, a strength assessment is required, and an appropriate concession acceptance or maintenance plan is developed based on the assessment results. In necessary cases, such as when the dent depth is large or the distance between the dent and the connecting hole on the skin is small, due to strength or damage tolerance requirements, a new strength assessment of the skin structure is required to obtain defect characteristic data. In this case, the engineer needs to perform calculations based on the defect characteristic data and engineering methods.

[0004] Currently, when addressing skin dents, the manufacturing or maintenance site personnel first use manual or semi-automatic methods, such as scanning measurement, to obtain the geometric information of the dent, including its shape, depth, radius, and the distance from the dent center to the connecting nail line. The test data is then sent to the design or site engineers for preliminary evaluation. Under certain conditions, such as when the damaged area or dent depth is large, or when the dent is close to the connecting hole, a structural strength assessment is necessary to evaluate the impact of the structural defect or damage on strength and durability. The strength assessment process typically involves a strength engineer calculating a new strength or fatigue damage tolerance safety margin based on the input defect data and existing engineering methods. Alternatively, the input defect data can be manually entered into a semi-automated assessment tool for strength evaluation, and then a repair or acceptance plan can be specified based on the calculation results.

[0005] Both manual measurement and semi-automatic scanning require manual measurement or input of multiple defect parameters, which are then transmitted to designers or input into an evaluation system for defect assessment. This process is cumbersome and inefficient. Therefore, this application provides a method for assessing the safety margin of skin dents to solve the above problems. Summary of the Invention

[0006] Technical issues

[0007] The technical problem to be solved by this application is to provide a method for assessing the safety margin of skin dents that can improve the efficiency of skin dent strength assessment.

[0008] Technical solution

[0009] To address the aforementioned technical problems, according to embodiments of this application, a method for assessing the safety margin of skin dents is provided, comprising the following steps: collecting dent defect data and surrounding structural feature data, wherein the surrounding structural feature data is feature data of a reference object surrounding the dent; constructing a skin geometric model based on the dent defect data and the surrounding structural feature data; aligning the skin geometric model with a preset ideal digital model based on the surrounding structural feature data to obtain a verification model boundary, wherein the skin represented by the ideal digital model includes the reference object and is free of defects; segmenting the model along the verification model boundary to obtain a verification model with defects; and performing a safety margin assessment based on the verification model with defects to obtain a safety margin.

[0010] Furthermore, the safety margin assessment method for skin dents may also include: determining the minimum range of the skin profile to be measured based on the location of the dent before collecting dent defect data and surrounding structural feature data, wherein the dent defect data is collected within the minimum range of the skin profile to be measured.

[0011] Furthermore, determining the minimum range of the skin profile to be measured based on the location of the depression may include: acquiring image data at the location of the depression; extracting a first contour line of the depression; obtaining a second contour line based on the first contour line, wherein the range within the second contour line is the minimum range of the skin profile to be measured.

[0012] Furthermore, obtaining a second contour line based on the first contour line may include: extending the second contour line outward along the first contour line by a predetermined fixed width.

[0013] Furthermore, the safety margin assessment based on the defective verification model to obtain the safety margin may include: performing finite element analysis on the defective verification model to obtain a finite element model; and applying loads to the finite element model to calculate the safety margin.

[0014] Furthermore, performing finite element analysis on the defective verification model to obtain a finite element model may include: filling the defective parts of the defective verification model with a first mesh; and filling the parts of the defective verification model other than the defective parts with a second mesh, thereby obtaining a finite element model.

[0015] Furthermore, the density of the second grid can be less than the density of the first grid.

[0016] Furthermore, applying loads to the finite element model to calculate the safety margin may include: applying loads to the finite element model; adjusting the magnitude and direction of the loads so that the loads meet the conditions of different working scenarios; and sequentially loading the finite element models with different loads to calculate the safety margins under each working condition.

[0017] Furthermore, after conducting a safety margin assessment based on the defective verification model and obtaining the safety margin, the process may include: obtaining an assessment of the impact of the defect on the skin strength and durability based on the safety margin; if the impact assessment is within an acceptable range, issuing an indication that the skin can be accepted and used; if the impact assessment is not within an acceptable range, issuing an indication that the skin needs to be repaired.

[0018] Furthermore, the assessment of the impact of defects on skin strength and durability based on the safety margin may include: when the safety margin is greater than 0, the impact assessment is within an acceptable range; and when the safety margin is less than 0, the impact assessment is not within an acceptable range.

[0019] Beneficial effects

[0020] Compared with the prior art, the technical solution of this application can achieve at least the following beneficial effects:

[0021] 1. This application collects pit defect data and surrounding structural feature data of the skin, and obtains a skin geometric model based on the pit defect data and surrounding structural feature data. Then, it aligns a preset ideal digital model with the skin geometric model according to the surrounding structural features, compares the ideal digital model and the skin geometric model to obtain the boundary of the verification model, and completes the model segmentation according to the verification model boundary to obtain the verification model with defects. Finite element analysis is performed on the verification model with defects to obtain a finite element model, and then loads are applied to the finite element model to calculate the safety margin. Based on the safety margin, the repair or acceptance scheme of the skin can be determined, thereby completing the strength assessment of pit defects. The entire assessment process reduces manual measurement and calculation operations and improves the efficiency and accuracy of strength assessment of skin defects.

[0022] 2. This application obtains a safety margin by obtaining a finite element model and applying loads to the finite element model. Based on the safety margin, the repair or acceptance scheme of the skin can be determined, which reduces the occurrence of overly conservative evaluation data caused by the use of engineering methods in conventional methods and is conducive to structural weight reduction.

[0023] 3. This application reduces manual input operations in the data calculation and recording process, effectively avoids manual input errors, improves the efficiency and accuracy of skin defect strength assessment, and thus improves the efficiency and accuracy of skin repair. Attached Figure Description

[0024] Figure 1 is an overall flowchart of a method for assessing the safety margin of skin dents according to this application.

[0025] Figure 2 is a schematic diagram illustrating the application of a safety margin assessment method for skin dents according to this application.

[0026] Figure 3 is a schematic diagram of the skin geometry model of this application.

[0027] Figure 4 is a schematic diagram showing the alignment of the skin geometry model of this application with the ideal digital model.

[0028] Figure 5 is a schematic diagram of the defective verification model of this application.

[0029] Figure 6 is a schematic diagram of the finite element model of this application.

[0030] Figure 7 is a schematic diagram of applying load to the defective verification model according to this application.

[0031] Explanation of reference numerals in the attached figures:

[0032] 1. Scanner; 2. Recess; 3. Mounting hole; 4. Skin. Detailed Implementation

[0033] To make the technical problems, technical solutions, and beneficial effects to be solved by the embodiments of this application clearer, the technical solutions in the embodiments of this application will be clearly and completely described below. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application. Unless otherwise defined, the technical or scientific terms used herein should have the ordinary meaning understood by those skilled in the art to which this application pertains. The words "comprising" and similar terms used herein mean that the element or object preceding the word covers the element or object listed after the word and its equivalents, but does not exclude other elements or objects.

[0034] This embodiment provides a method for assessing the safety margin of skin dents. Referring to Figures 1 and 2, the method for assessing the safety margin of skin dents includes the following steps:

[0035] S1: Collect the defect data of pit 2 and the surrounding structural feature data. The surrounding structural feature data is the feature data of the reference objects around the pit.

[0036] Before collecting data on the pit 2 defect and surrounding structural features, image data of the pit location is first acquired. Based on the acquired image data, a first contour line of the pit is extracted. This first contour line is the edge line of the pit notch. A second contour line is obtained by extending a predetermined fixed width outward from the first contour line. The area within the second contour line serves as the minimum measurement range for the skin 4 surface. The pit 2 defect data is collected within this minimum measurement range. Determining the minimum measurement range for the skin 4 surface before measurement avoids unnecessary and redundant measurements caused by large-scale measurements, making the pit measurement more accurate and targeted. Furthermore, reducing the measurement range decreases the amount of data processed, thereby improving the efficiency of strength assessment. Simultaneously, surrounding structural feature data is collected. This data consists of feature data of reference objects around the pit, including at least one of the mounting holes 3 on the skin 4, the edges of the skin 4, and the corners of the skin 4 surrounding the pit.

[0037] S2: Construct the geometric model of skin 4 based on the pit 2 defect data and surrounding structural feature data.

[0038] Referring to Figure 3, the collected data on the pit 2 defect and the surrounding structural features are input into the modeling software, and a geometric model of the skin 4 is constructed using the software. This geometric model of the skin 4 is a simulation model of the measured skin 4 with the pit. By analyzing this geometric model of the skin 4, the evaluation results can be obtained through simulation, reducing physical testing and resource waste, reducing the consumption of human resources, and thus improving the efficiency of strength assessment.

[0039] S3: Align the geometric model of skin 4 with the preset ideal model based on the surrounding structural feature data to obtain the boundary of the verification model. The skin 4 represented by the ideal model includes the reference object and has no defects.

[0040] Referring to Figure 4, during the design and manufacturing of skin 4, its structural parameters are recorded and saved in the ideal digital model. These parameters include the material thickness and dimensional specifications. The ideal digital model represents skin 4, including the reference object and free of defects. Using the surrounding structural features in the ideal digital model and the geometric model of skin 4 as a reference, the geometric model of skin 4 is aligned with the preset ideal digital model based on these features. After alignment, the alignment degree between the ideal digital model and the geometric model of skin 4 is calculated, and it is determined whether the alignment degree is within a comparable range. If the alignment degree is within a comparable range, the inspection continues; if the alignment degree is not within a comparable range, a prompt is made to regenerate the geometric model of skin 4. After aligning the skin 4 geometric model with the ideal model, the boundaries of the ideal model and the skin 4 geometric model coincide. The same surrounding structural features in the ideal model and the skin 4 geometric model also coincide. By comparing the ideal model and the skin 4 geometric model, the concave edges in the skin 4 geometric model are located and connected to obtain the defect boundary line. The same surrounding structural features in the ideal model and the skin 4 geometric model are located and connected to obtain the boundary line. This boundary line is used as the boundary of the verification model.

[0041] S4: Divide the model along the boundary of the verification model to obtain the verification model with defects.

[0042] Referring to Figure 5, the model is divided according to the boundary of the verification model to obtain the verification model with defects. This step removes the parts that do not need to be analyzed and evaluated, reducing the amount of data to be processed in the future, thereby improving the efficiency of strength assessment.

[0043] S5: Conduct a safety margin assessment based on a defective verification model to obtain the safety margin.

[0044] Referring to Figure 6, the defective areas in the verification model are filled using the first mesh, i.e., the areas within the defect boundary line are filled using the first mesh. The areas in the verification model other than the defective areas are filled using the second mesh, i.e., the areas between the defect boundary line and the verification model boundary are filled using the second mesh, thus obtaining the finite element model. The density of the second mesh is less than that of the first mesh. Referring to Figure 7, loads are applied to the finite element model, i.e., forces of different magnitudes and directions are applied. Different magnitudes and directions of forces can simulate different working conditions. The magnitude and direction of the loads are adjusted to meet the conditions of different working conditions. The finite element models with different loads are loaded sequentially, and then the safety margins under each working condition are calculated. Based on the safety margins, the impact of defects on the strength and durability of skin 4 is assessed. When the safety margin is greater than 0, the impact assessment is within an acceptable range; when the safety margin is less than 0, the impact assessment is not within an acceptable range. If the impact assessment is within acceptable limits, an instruction message is issued that skin 4 can be accepted and used. If the impact assessment is not within acceptable limits, an instruction message is issued that skin 4 needs to be repaired. After receiving the instruction message that skin 4 needs to be repaired, the maintenance personnel will carry out the repair work on the skin.

[0045] The following example, using the detection of a pit 2 on the skin 4, will be explained in detail with reference to Figures 1 and 2:

[0046] During the manufacturing process, a dent 2 was created in the wall panel of the skin 4 due to an impact. The dent 2 is now being inspected and its strength evaluated.

[0047] Step 1: Collect data on pit 2 defects and surrounding structural features.

[0048] First, the inspector collects image data of the location of the dent. Based on the collected image data, the first contour line of the dent is extracted. The first contour line is the edge line of the dent. A second contour line is obtained by extending a predetermined fixed width outward from the first contour line, for example, by extending 5mm outward from the first contour line. The area within the second contour line is used as the minimum range for measuring the surface of the skin 4. Next, the inspector uses an optical scanner 1, such as a structured light scanner 1, to scan the wall panel of the skin 4 within this minimum range to obtain the point cloud data of the dent 2 defect. Then, the point cloud data of reference objects around the dent 2 defect is scanned, such as the point cloud data of any one of the mounting holes 3, edges, corners, etc. on the skin 4 around the dent 2 defect. In this embodiment, the point cloud data of the four mounting holes 3 on the skin 4 around the defect are scanned. The four mounting holes 3 are the first mounting hole P1, the second mounting hole P2, the third mounting hole P3, and the fourth mounting hole P4.

[0049] Step 2: Construct the geometric model of skin 4 based on the pit 2 defect data and surrounding structural feature data.

[0050] Referring to Figure 3, the point cloud data of the pit 2 defect and the point cloud data of the four mounting holes 3 are input into the modeling software, and the geometric model of the skin 4 is constructed through the modeling software.

[0051] Step 3: Align the geometric model of skin 4 with the preset ideal model based on the surrounding structural feature data to obtain the boundary of the verification model. The skin 4 represented by the ideal model includes the reference object and has no defects.

[0052] Referring to Figure 4, the four mounting holes 3 are used as references to align the ideal digital model with the skin 4 geometric model. After alignment, the alignment degree between the ideal digital model and the skin 4 geometric model is calculated, and it is determined whether the alignment degree is within the comparable range. If the alignment degree is within the comparable range, the detection continues; if the alignment degree is not within the comparable range, a prompt is made to regenerate the skin 4 geometric model. After alignment, the boundaries of the ideal digital model and the skin 4 geometric model coincide, and the four mounting holes 3 in the ideal digital model and the skin 4 geometric model also coincide. By comparing the ideal digital model and the skin 4 geometric model, the concave edges in the skin 4 geometric model are located and connected to obtain the defect boundary line. The same surrounding structural features in the ideal digital model and the skin 4 geometric model are located and connected to obtain the boundary line. In this embodiment, the mounting holes 3 in the ideal digital model and the skin 4 geometric model are located and connected to obtain the boundary line, which is used as the boundary of the verification model.

[0053] Step 4: Divide the model along the boundary of the verification model to obtain the verification model with defects.

[0054] Referring to Figure 5, the model is divided according to the boundary of the verification model to obtain the verification model with defects.

[0055] Step 5: Conduct a safety margin assessment based on the defective verification model to obtain the safety margin.

[0056] Referring to Figure 6, the first mesh is used to fill the pit 2 area in the defective verification model, that is, the area within the defect boundary line is filled with the first mesh. The second mesh is used to fill the area in the verification model other than the defective area, that is, the area between the defect boundary line and the verification model boundary is filled with the second mesh, thus obtaining the finite element model. The density of the second mesh is less than that of the first mesh. Loads are applied to the finite element model, that is, forces of different magnitudes and directions are applied to the finite element model. Different magnitudes and directions of forces can simulate different working conditions. The magnitude and direction of the loads are adjusted so that the loads meet the conditions of different working conditions. The finite element models with different loads are loaded sequentially, each time loading a finite element model under a different working condition, and the safety margin under that working condition is calculated, thus obtaining the safety margin for each working condition. The impact of the defect on the strength and durability of skin 4 is assessed based on the safety margin. When the safety margin is greater than 0, the impact of the defect on the strength and durability of skin 4 is within the set range, meaning the impact assessment is within acceptable limits. When the safety margin is less than 0, the impact of the defect on the strength and durability of skin 4 is not within the set range, meaning the impact assessment is not within acceptable limits. If the impact assessment is within acceptable limits, an indication that skin 4 can be accepted and used is issued. If the impact assessment is not within acceptable limits, an indication that skin 4 requires repair is issued. After receiving the indication that repair is required, maintenance personnel will perform repairs on the skin.

[0057] In summary, the technical solution of this application can achieve at least the following beneficial effects:

[0058] This application collects data on the pit 2 defect of skin 4 and surrounding structural features, and obtains a geometric model of skin 4 based on these data. Then, it aligns a pre-defined ideal digital model with the geometric model of skin 4 according to the surrounding structural features. By comparing the ideal digital model and the geometric model of skin 4, the boundary of the verification model is obtained. The model is then segmented according to the verification model boundary to obtain a verification model with defects. Finite element analysis is performed on the verification model with defects to obtain a finite element model. Loads are then applied to the finite element model to calculate the safety margin. Based on the safety margin, a repair or acceptance plan for skin 4 can be determined, thus completing the strength assessment of the pit 2 defect. The entire assessment process reduces manual measurement and calculation operations, improving the efficiency and accuracy of strength assessment of skin 4 defects.

[0059] This application obtains a safety margin by acquiring a finite element model and applying loads to the finite element model. Based on the safety margin, the repair or acceptance scheme for the skin 4 can be determined, which reduces the occurrence of overly conservative evaluation data caused by the use of engineering methods in conventional methods and is conducive to structural weight reduction.

[0060] This application reduces manual input operations in the data calculation and recording process, effectively avoids human input errors, and improves the efficiency and accuracy of the skin 4 defect strength assessment, thereby improving the efficiency and accuracy of skin 4 repair.

[0061] This application determines the minimum range of the measuring skin 4 surface based on the location of the depression. The depression 2 defect data is collected within the minimum range of the measuring skin 4 surface, and the geometric model of the skin 4 is obtained through a scanning method. This method is more accurate than the traditional method of using an envelope circle to characterize defects, thereby improving the efficiency and accuracy of the skin 4 defect strength assessment.

[0062] This application is described with reference to flowchart illustrations and / or block diagrams of methods according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in one or more blocks of the flowchart illustrations and / or one or more blocks of the block diagrams.

[0063] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means that implement the functions specified in one or more flowcharts and / or one or more block diagrams.

[0064] These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process, such that the instructions, which execute on the computer or other programmable apparatus, provide steps for implementing the functions specified in one or more flowcharts and / or one or more block diagrams.

[0065] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0066] While the embodiments of this application have been described in detail above, it will be apparent 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 fall within the scope and spirit of this application. Furthermore, the application described herein may have other embodiments and can be implemented or carried out in various ways.

Claims

1. A method for assessing the safety margin of skin dents, comprising the following steps: Collect pit defect data and surrounding structural feature data, wherein the surrounding structural feature data is the feature data of reference objects around the pit; A skin geometric model is constructed based on the pit defect data and the surrounding structural feature data; The skin geometric model is aligned with the preset ideal model based on the surrounding structural feature data to obtain the verification model boundary. The skin represented by the ideal model includes the reference object and has no defects. The model is segmented along the boundary of the verification model to obtain a verification model with defects; and A safety margin assessment is performed based on the defective verification model to obtain the safety margin.

2. The method for assessing the safety margin of skin dent as described in claim 1, further comprising: Before collecting pit defect data and surrounding structural feature data, the minimum range of the measuring skin profile is determined based on the location of the pit, and the pit defect data is collected within the minimum range of the measuring skin profile.

3. The method for assessing the safety margin of skin dents as described in claim 2, wherein, The step of determining the minimum range of the skin profile to be measured based on the location of the depression includes: acquiring image data at the location of the depression; extracting the first contour line of the depression; and obtaining a second contour line based on the first contour line, wherein the range within the second contour line is the minimum range of the skin profile to be measured.

4. The method for assessing the safety margin of skin dents as described in claim 3, wherein, The step of obtaining the second contour line based on the first contour line includes: extending the second contour line outward along the first contour line by a predetermined fixed width.

5. The method for assessing the safety margin of skin dents as described in claim 1, wherein the safety margin assessment based on a verification model with defects to obtain the safety margin includes: The defective verification model is subjected to finite element analysis to obtain a finite element model; And the safety margin is calculated by applying loads to the finite element model.

6. The method for assessing the safety margin of skin dents as described in claim 5, wherein the finite element analysis of the defective verification model to obtain the finite element model includes: The defective areas in the defective verification model are filled using the first mesh; And a second mesh is used to fill the parts of the verification model with defects, excluding the defective parts, to obtain a finite element model.

7. The method for assessing the safety margin of skin dents as described in claim 6, wherein, The density of the second grid is less than the density of the first grid.

8. The method for assessing the safety margin of skin dents as described in claim 5, wherein, The step of applying loads to the finite element model to calculate the safety margin includes: applying loads to the finite element model; adjusting the magnitude and direction of the loads so that the loads meet the conditions of different working scenarios; and sequentially loading the finite element models with different loads to calculate the safety margins under each working condition.

9. The method for assessing the safety margin of skin dent as described in claim 1, further comprising: After obtaining the safety margin by performing a safety margin assessment based on the verification model with defects, the impact of defects on skin strength and durability is assessed based on the safety margin. If the impact assessment is within acceptable limits, an instruction is issued that the skin can be accepted and used; if the impact assessment is not within acceptable limits, an instruction is issued that the skin needs to be repaired.

10. The method for assessing the safety margin of skin dents as described in claim 9, wherein, The assessment of the impact of defects on skin strength and durability based on the safety margin includes: when the safety margin is greater than 0, the impact assessment is within an acceptable range; and when the safety margin is less than 0, the impact assessment is not within an acceptable range.

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