Skin depression safety margin assessment method

Abstract

The invention provides a safety margin assessment method for skin depression. The safety margin assessment method comprises the following steps: collecting pit defect data and surrounding structure feature data; constructing a skin geometric model according to the pit defect data and the surrounding structure feature data; aligning the skin geometric model with a preset ideal mathematical model according to the surrounding structure feature data to obtain a check model boundary; performing model segmentation along the boundary of the check model to obtain a check model with defects; and performing safety margin evaluation based on the check model with the defects to obtain the safety margin. According to the invention, the efficiency of evaluating the strength of the skin depression is improved.

Description

Technical Field

[0001] The invention relates to the technical field of nondestructive testing, and in particular to a safety margin assessment method for skin dents. 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. When a dent occurs on the skin, it is necessary to conduct a strength assessment of the dent, and then formulate a corresponding concession acceptance or maintenance plan based on the results of the strength assessment. In necessary cases, such as when the depth of the damage dent is large or the distance between the dent and the connection hole on the skin is small, due to the requirements of strength or damage tolerance, the skin structure needs to be re-evaluated to obtain defect characteristic data. At this time, it needs to be calculated by engineers based on the defect characteristic data combined with engineering methods.

[0003] At present, when dealing with skin dents, first, the manufacturing or maintenance site staff use manual measurement or semi-automatic methods, such as scanning measurement, to measure the geometric information of the dent, including the shape, depth, radius, and distance from the center of the dent to the connecting nail line. The test data is then sent to the design or site engineer for preliminary evaluation. Under certain conditions, for example, when the damage area or dent depth is large, or when the distance from the dent to the connecting hole is small, the structural strength must be evaluated to assess the impact of structural defects or damage on strength and durability. The strength evaluation process is usually that the strength engineer calculates the safety margin of the new strength or fatigue damage tolerance based on the input defect data according to the existing engineering methods. Or the input defect data is manually entered into a semi-automatic evaluation tool for strength evaluation, and then a maintenance or acceptance plan is specified based on the calculation results.

[0004] Whether it is manual measurement or semi-automatic scanning, it is necessary to manually measure or input multiple defect parameters and pass them to the designer or input the evaluation system to complete the defect evaluation. The process is cumbersome and inefficient. Therefore, the present invention provides a safety margin evaluation method for skin dents to solve the above problem. Summary of the invention

[0005] The object of the present invention is to provide a method for evaluating the safety margin of skin dents so as to improve the efficiency of strength evaluation of skin dents.

[0006] In order to achieve the purpose of the present invention, the technical solution adopted by the present invention is: A method for evaluating the safety margin of skin dents 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; Constructing a skin geometry model according to the pit defect data and the surrounding structure feature data; Aligning the skin geometric model with a preset ideal digital model according to the surrounding structural feature data to obtain a verification model boundary, wherein the skin represented by the ideal digital model includes a reference object and has no defects; Performing model segmentation along the boundary of the verification model to obtain a verification model with defects; A safety margin is evaluated based on the defective verification model to obtain a safety margin.

[0007] Furthermore, before collecting the pit defect data and the surrounding structure feature data, it also includes: The minimum range of measuring the skin profile is determined according to the location of the depression, and the pit defect data is collected within the minimum range of measuring the skin profile.

[0008] Furthermore, the minimum range of measuring the skin profile is determined according to the location of the depression, including: Collecting image data at the location of the depression; Extracting a first contour line of the concave; A second contour line is obtained based on the first contour line, and the range within the second contour line is the minimum range for measuring the skin profile.

[0009] Further, obtaining a second contour line based on the first contour line includes: The second contour line is obtained by extending the first contour line outward by a preset fixed width.

[0010] Furthermore, the safety margin is evaluated based on the defective verification model to obtain the safety margin, including: Performing finite element analysis on the defective verification model to obtain a finite element model; A load is applied to the finite element model to calculate a safety margin.

[0011] Furthermore, a finite element analysis is performed on the defective verification model to obtain a finite element model, including: Filling the defective part in the defective verification model with the first grid; The second grid is used to fill the parts of the defective verification model except the defective parts, so as to obtain a finite element model.

[0012] Furthermore, the density of the second grid is smaller than the density of the first grid.

[0013] Furthermore, applying load to the finite element model to calculate the safety margin includes: applying a load to the finite element model; Adjust the size and direction of the load so that the load meets the conditions of different working scenarios; The finite element models with different loads are loaded in sequence, and the safety margin under each working condition is calculated.

[0014] Furthermore, after the safety margin is evaluated based on the defective verification model and the safety margin is obtained, the following steps are performed: Obtaining an assessment of the effect of the defect on the skin strength and durability based on the safety margin; If the impact assessment is within an acceptable range, an indication message is issued that the skin can be received and used; if the impact assessment is not within an acceptable range, an indication message is issued that the skin needs to be repaired.

[0015] Furthermore, the impact of defects on skin strength and durability is evaluated based on the safety margin, including: 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.

[0016] Beneficial effects of the present invention: 1. The present invention collects the pit defect data and surrounding structural feature data of the skin, obtains the skin geometric model according to the pit defect data and the surrounding structural feature data, and then aligns the preset ideal digital model with the skin geometric model according to the surrounding structural features, compares the ideal digital model with the skin geometric model to obtain the verification model boundary, completes the model segmentation according to the verification model boundary to obtain the defective verification model, performs finite element analysis on the defective verification model to obtain the finite element model, and then applies load to the finite element model to calculate the safety margin, and can determine the skin maintenance or acceptance plan according to the safety margin, thereby completing the strength evaluation of the pit defect. The entire evaluation process reduces manual measurement and calculation operations, and improves the efficiency and accuracy of strength evaluation of skin defects.

[0017] 2. The present invention obtains a finite element model and applies load to the finite element model to calculate a safety margin. According to the safety margin, a repair or acceptance plan for the skin can be determined, thereby reducing the occurrence of overly conservative evaluation data caused by the use of engineering methods in conventional methods, and is beneficial to structural weight reduction.

[0018] 3. The present invention 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. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1The present invention is an overall flow chart of a method for evaluating the safety margin of skin dents.

[0020] Figure 2 It is a schematic diagram of the application of a safety margin assessment method for skin dents of the present invention.

[0021] Figure 3 It is a schematic diagram of the skin geometric model of the present invention.

[0022] Figure 4 It is a schematic diagram of the alignment of the skin geometry model of the present invention with the ideal digital model.

[0023] Figure 5 Schematic diagram of a defective calibration model of the present invention.

[0024] Figure 6 is a schematic diagram of a finite element model of the present invention.

[0025] Figure 7 It is a schematic diagram of applying load to a defective calibration model according to the present invention.

[0026] Description of reference numerals: 1. Scanner; 2. Pit; 3. Mounting hole; 4. Skin. DETAILED DESCRIPTION

[0027] 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.

[0028] This embodiment provides a method for evaluating the safety margin of skin dents, referring to Figure 1 and Figure 2 The safety margin assessment method for skin dents comprises the following steps: S1: Collecting the defect data of the pit 2 and the surrounding structural feature data, where the surrounding structural feature data is the feature data of the reference object around the pit.

[0029] Before collecting the defect data of the pit 2 and the surrounding structural feature data, the image data at the location of the depression is first collected, and the first contour line of the depression is extracted based on the collected image data. The first contour line is the edge line of the depression gap, and the second contour line is obtained by extending the preset fixed value width outward along the first contour line. The range within the second contour line is used as the minimum range for measuring the skin 4 profile, and the pit 2 defect data is collected within the minimum range for measuring the skin 4 profile. Determining the minimum range for measuring the skin 4 profile before measurement avoids invalid and redundant measurements caused by large-scale measurements, and makes the depression measurement more accurate and targeted. At the same time, due to the reduction in the measurement range, the amount of data processed is reduced, thereby improving the efficiency of strength assessment. At the same time, the surrounding structural feature data is collected. The surrounding structural feature data is the feature data of the reference object around the depression. The reference object includes at least one of the mounting hole 3 on the skin 4 around the skin 4 depression, the edge on the skin 4, and the corner on the skin 4.

[0030] S2: Construct the geometric model of skin 4 based on the defect data of pit 2 and the surrounding structure feature data.

[0031] Reference Figure 3 , the collected pit 2 defect data and surrounding structural feature data are input into the modeling software, and the geometric model of the skin 4 is constructed by the modeling software. The geometric model of the skin 4 is a simulation model of the measured skin 4 with a depression. By analyzing the geometric model of the skin 4, the evaluation result can be obtained by simulation, which reduces the waste of physical tests and resources, and can reduce the consumption of human resources, thereby improving the efficiency of strength evaluation.

[0032] S3: Align the geometric model of the skin 4 with the preset ideal digital model according to the surrounding structural feature data to obtain the verification model boundary. The skin 4 represented by the ideal digital model includes the reference object and has no defects.

[0033] Reference Figure 4When designing and manufacturing the skin 4, the structural parameters of the skin 4 will be recorded and saved in the ideal digital model. The structural parameters of the skin 4 are the material thickness, size specification parameters, etc. of the skin 4. The skin 4 represented by the ideal digital model includes a reference and has no defects. The ideal digital model and the surrounding structural features in the geometric model of the skin 4 are used as a comparison. The geometric model of the skin 4 is aligned with the preset ideal digital model according to the surrounding structural features. After alignment, the alignment degree of the ideal digital model and the geometric model of the skin 4 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, it is prompted to regenerate the geometric model of the skin 4. After the skin 4 geometric model is aligned with the ideal digital model, the boundaries of the ideal digital model and the skin 4 geometric model are in a coincident state, and the same surrounding structural features in the ideal digital model and the skin 4 geometric model are also in a coincident state. By comparing the ideal digital model with the skin 4 geometric model, the concave edge in the skin 4 geometric model is located and connected to obtain the defect boundary line, and 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, which is used as the verification model boundary.

[0034] S4: Divide the model along the boundary of the verification model to obtain a verification model with defects.

[0035] Reference Figure 5 , the model is divided according to the boundary of the verification model to obtain a verification model with defects. Through this step, the part that does not need to be analyzed and evaluated is removed, reducing the amount of subsequent processing data, thereby improving the efficiency of strength evaluation.

[0036] S5: Perform safety margin assessment based on the defective verification model to obtain the safety margin.

[0037] Reference Figure 6 , the first mesh is used to fill the defective part in the defective verification model, that is, the part within the defect boundary line is filled with the first mesh. The second mesh is used to fill the part other than the defective part in the defective verification model, that is, the part between the defect boundary line and the verification model boundary is filled with the second mesh, thereby obtaining a finite element model. The density of the second mesh is less than that of the first mesh. Figure 7, apply loads to the finite element model, that is, apply forces of different sizes and directions to the finite element model. Forces of different sizes and directions can simulate different working conditions. The size and direction of the load are adjusted so that the load meets the conditions of different working conditions. The finite element models with different loads are loaded in turn, and then the safety margin under each working condition is calculated. According to the safety margin, the impact assessment of the defect on the strength and durability of the skin 4 is obtained. 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 an acceptable range, an indication that the skin 4 can be received and used is issued. If the impact assessment is not within an acceptable range, an indication that the skin 4 needs to be repaired is issued. After receiving the indication that the repair is required, the maintenance personnel will repair the skin.

[0038] The following is an example of detecting a pit 2 on the skin 4. Figure 1 and Figure 2 , for specific instructions: During the manufacturing process, a dent 2 is produced on the wall panel of the skin 4 due to a collision, and the dent 2 is now subjected to inspection and strength assessment.

[0039] Step 1: Collect pit 2 defect data and surrounding structure feature data.

[0040] First, the inspector collects image data at the location of the depression, and extracts the first contour line of the depression based on the collected image data. The first contour line is the edge line of the depression gap, and the second contour line is obtained by extending the width of a preset fixed value outward along the first contour line, for example, the second contour line is obtained by extending 5mm outward along the first contour line. The range within the second contour line is used as the minimum range for measuring the profile of the skin 4. Then the inspector uses an optical scanner 1, such as a structured light scanner 1, to scan the wall panel of the skin 4 within the minimum range to obtain the point cloud data of the pit 2 defect, and then scans the point cloud data of the reference object around the pit 2 defect, such as the point cloud data of any one of the mounting holes 3, edges, corners, etc. on the skin 4 around the pit 2 defect. In this embodiment, the point cloud data of the four mounting holes 3 on the skin 4 around the defect are scanned, and the four mounting holes 3 are respectively the first mounting hole P1, the second mounting hole P2, the third mounting hole P3 and the fourth mounting hole P4.

[0041] Step 2: Construct the geometric model of skin 4 based on the pit 2 defect data and the surrounding structure feature data.

[0042] Reference Figure 3 The collected 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 by the modeling software.

[0043] Step 3: Align the geometric model of skin 4 with the preset ideal digital model according to the surrounding structural feature data to obtain the verification model boundary. The skin 4 represented by the ideal digital model includes the reference object and has no defects.

[0044] Reference Figure 4 , four mounting holes 3 are used as reference objects to align the ideal digital model with the geometric model of the skin 4. After alignment, the alignment degree of the ideal digital model and the geometric model of the skin 4 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 is continued. If the alignment degree is not within the comparable range, the geometric model of the skin 4 is prompted to be regenerated. After the ideal digital model is aligned with the geometric model of the skin 4, the boundary of the ideal digital model and the geometric model of the skin 4 is in a coincidence state, and the four mounting holes 3 in the ideal digital model and the geometric model of the skin 4 are also in a coincidence state. The ideal digital model is compared with the geometric model of the skin 4, and the concave edge in the geometric model of the skin 4 is located and connected to obtain a defect boundary line. The same surrounding structural features of the ideal digital model and the geometric model of the skin 4 are located and connected to obtain a boundary line. In this embodiment, the mounting holes 3 in the ideal digital model and the geometric model of the skin 4 are located and connected to obtain a boundary line, and the boundary line is used as the verification model boundary.

[0045] Step 4: Divide the model along the boundary of the verification model to obtain a verification model with defects.

[0046] Reference Figure 5 , the model is divided according to the verification model boundary to obtain the verification model with defects.

[0047] Step 5: Perform safety margin assessment based on the defective verification model to obtain the safety margin.

[0048] Reference Figure 6, the first grid is used to fill the pit 2 part in the defective verification model, that is, the part within the defect boundary line is filled with the first grid. The second grid is used to fill the part other than the defective part in the defective verification model, that is, the part between the defect boundary line and the verification model boundary is filled with the second grid, so as to obtain a finite element model. The density of the second grid is less than the density of the first grid. Apply a load to the finite element model, that is, apply forces of different sizes and directions to the finite element model. Forces of different sizes and directions can simulate different working conditions, and adjust the size and direction of the load so that the load meets the conditions of different working conditions. The finite element models with different loads are loaded in turn, and the finite element model under a working condition is loaded each time, and the safety margin under the working condition is calculated, so that the safety margin under each working condition can be calculated. The impact assessment of the defect on the strength and durability of the skin 4 is obtained according to the safety margin. When the safety margin is greater than 0, the impact of the defect on the strength and durability of the skin 4 is within the set range, that is, the impact assessment of the defect on the strength and durability of the skin 4 is within the acceptable range; when the safety margin is less than 0, the impact of the defect on the strength and durability of the skin 4 is not within the set range, that is, the impact assessment of the defect on the strength and durability of the skin 4 is not within the acceptable range. If the impact assessment is within the acceptable range, an indication message that the skin 4 can be received and used is issued. If the impact assessment is not within the acceptable range, an indication message that the skin 4 needs to be repaired is issued. After receiving the indication message that the repair needs to be performed, the maintenance personnel will repair the skin.

[0049] Beneficial effects of the present invention: The present invention collects the pit 2 defect data and surrounding structural feature data of the skin 4, obtains the skin 4 geometric model according to the pit 2 defect data and the surrounding structural feature data, aligns the preset ideal digital model with the skin 4 geometric model according to the surrounding structural features, compares the ideal digital model with the skin 4 geometric model to obtain the verification model boundary, completes the model segmentation according to the verification model boundary to obtain the defective verification model, performs finite element analysis on the defective verification model to obtain the finite element model, applies load to the finite element model to calculate the safety margin, and can judge the maintenance or acceptance plan of the skin 4 according to the safety margin, thereby completing the strength evaluation of the pit 2 defect. The entire evaluation process reduces the manual measurement and calculation operations, and improves the efficiency and accuracy of the strength evaluation of the skin 4 defects.

[0050] The present invention obtains a finite element model and applies load to the finite element model to calculate a safety margin. According to the safety margin, a maintenance or acceptance plan of the skin 4 can be determined, thereby reducing the occurrence of overly conservative evaluation data caused by the use of engineering methods in conventional methods, and is beneficial to structural weight reduction.

[0051] The present invention reduces manual input operations in the data calculation and recording process, effectively avoids manual input errors, improves the efficiency and accuracy of the skin 4 defect strength assessment, and thus improves the efficiency and accuracy of the skin 4 repair.

[0052] The present invention determines the minimum range of measuring the skin 4 surface according to the location of the depression, and the pit 2 defect data is collected within the minimum range of measuring the skin 4 surface. The skin 4 geometric model is obtained by a scanning method, which 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.

[0053] The present invention is described with reference to the flowcharts and / or block diagrams of the methods according to the embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as the combination of processes and / or blocks in the flowcharts 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, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0054] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0055] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0056] It should also 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 more 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.

[0057] 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 method for assessing the safety margin of skin dents, characterized in that: The following steps are involved: Collecting pit (2) defect data and surrounding structure feature data, wherein the surrounding structure feature data is feature data of a reference object surrounding the pit; Constructing a geometric model of the skin (4) according to the defect data of the pit (2) and the characteristic data of the surrounding structure; Aligning the geometric model of the skin (4) with a preset ideal digital model according to the surrounding structural feature data to obtain a verification model boundary, wherein the skin (4) represented by the ideal digital model includes a reference object and has no defects; Performing model segmentation along the boundary of the verification model to obtain a verification model with defects; A safety margin is evaluated based on the defective verification model to obtain a safety margin.

2. A method for assessing the safety margin of skin dents as claimed in claim 1, characterized in that: Before collecting the pit (2) defect data and surrounding structure feature data, it also includes: The minimum range of the measured skin (4) profile is determined according to the location of the depression, and the defect data of the pit (2) is collected within the minimum range of the measured skin (4) profile.

3. A method for assessing the safety margin of skin dents as claimed in claim 2, characterized in that: The minimum range of the surface of the skin (4) to be measured is determined according to the location of the depression, including: Collecting image data at the location of the depression; Extracting a first contour line of the concave; A second contour line is obtained based on the first contour line, and the range within the second contour line is the minimum range for measuring the profile of the skin (4).

4. A method for assessing the safety margin of skin dents as claimed in claim 3, characterized in that: Obtaining a second contour line based on the first contour line includes: The second contour line is obtained by extending the first contour line outward by a preset fixed width.

5. The method for evaluating the safety margin of skin dents according to claim 1, characterized in that: The safety margin is evaluated based on the defective verification model to obtain the safety margin, including: Performing finite element analysis on the defective verification model to obtain a finite element model; A load is applied to the finite element model to calculate a safety margin.

6. A method for assessing safety margin of skin dents as claimed in claim 5, characterized in that: The finite element model is obtained by performing finite element analysis on the defective verification model, including: Filling the defective part in the defective verification model with the first grid; The second grid is used to fill the parts of the defective verification model except the defective parts, so as to obtain a finite element model.

7. A method for assessing the safety margin of skin dents as claimed in claim 6, characterized in that: The density of the second grid is smaller than the density of the first grid.

8. The method for evaluating the safety margin of skin dents according to claim 5, characterized in that: Applying load to the finite element model to calculate the safety margin includes: applying a load to the finite element model; Adjust the size and direction of the load so that the load meets the conditions of different working scenarios; The finite element models with different loads are loaded in sequence, and the safety margin under each working condition is calculated.

9. The method for evaluating the safety margin of skin dents according to claim 1, characterized in that: After the safety margin is obtained by evaluating the safety margin based on the defective verification model, it also includes: Obtaining an assessment of the effect of the defect on the skin strength and durability based on the safety margin; If the impact assessment is within an acceptable range, an indication message is issued that the skin (4) can be received and used; if the impact assessment is not within an acceptable range, an indication message is issued that the skin (4) needs to be repaired.

10. A method for assessing the safety margin of skin dents as claimed in claim 9, characterized in that: The impact of the defect on the strength and durability of the skin (4) is evaluated based on the safety margin, including: 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.

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