A parameter detection device and detection method related to a stress concentration coefficient of a key component

Abstract

The application discloses a kind of parameter detection devices related to key component stress concentration coefficient, including base, image size measurement system, white light interferometry system and rotating table, using the detection method of parameter detection devices related to key component stress concentration coefficient, including the following steps: the image of notch sample is collected, the bottom surface microtopography point cloud of notch sample is collected, the structural stress concentration characteristic parameter size of notch sample is calculated, trend is leveled, the calculation of three-dimensional surface stress concentration characteristic parameter is carried out.The application belongs to the technical field of parameter related to stress concentration coefficient, specifically solves the function that existing technology cannot measure structural stress concentration characteristic parameter and surface stress concentration characteristic parameter simultaneously, needs manual test bar rotation, removes trend, and key information is easily lost in leveling process, so as to make measurement inaccurate, is a kind of new parameter detection device and detection method related to key component stress concentration coefficient.

Description

Technical Field

[0001] This invention belongs to the technical field of parameters related to stress concentration factor, specifically referring to a detection device and detection method for parameters related to stress concentration factor of key components. Background Technology

[0002] Key components are the core load-bearing parts of high-end equipment. When these components are subjected to cyclic loads, fatigue cracks can initiate. Through crack propagation, fatigue fracture eventually occurs, leading to serious safety accidents. The root cause of crack initiation is stress concentration. The stress concentration factor describes the degree of stress concentration; therefore, improving the accuracy of stress concentration factor calculation is fundamental research for upgrading the technology of key components. Notched specimens are the standard test bars used in GB / T 2039-2012 "Metallic Materials - Uniaxial Tensile Creep Test Method" to study the fatigue performance of key components. Stress concentration factors can be divided into structural stress concentration factors and surface stress concentration factors. Calculating the structural stress concentration factor of a notched specimen requires obtaining its structural parameters, while calculating the surface stress concentration factor requires obtaining the characterization parameters of the microscopic three-dimensional morphology of the bottom surface of the notched specimen. Therefore, accurately obtaining these parameters is fundamental to subsequent stress concentration factor calculations.

[0003] Currently, common commercial instruments for measuring notched specimens lack the capability to simultaneously measure structural stress concentration parameters and surface stress concentration parameters. This necessitates the use of multiple instruments based on different principles to measure various parameters, such as laser confocal microscopes and image dimensional measuring instruments. This complicates the measurement process, makes it difficult to standardize measurement benchmarks, and creates significant challenges for data processing, ultimately impacting measurement accuracy. Furthermore, measuring the surface morphology of different notch bottom regions using commercial instruments requires manual rotation of the specimen, making it difficult to accurately measure the surface morphology in different areas. The trend removal methods employed in commercial instruments are not calibrated according to the actual notch trend, potentially leading to the loss of crucial information during calibration and resulting in inaccurate measurements. Summary of the Invention

[0004] The technical problem to be solved by this invention is:

[0005] Existing technologies cannot simultaneously measure structural stress concentration characterization parameters and surface stress concentration characterization parameters, which makes the measurement process complex; it requires manual rotation of the test bar, making it difficult to measure the surface morphology in different areas; and the trend removal method does not calibrate according to the actual notch trend, which can easily lead to the loss of key information during the calibration process, resulting in inaccurate measurements.

[0006] To solve the above-mentioned technical problems, the technical solution proposed by this invention is as follows:

[0007] A device for detecting parameters related to the stress concentration factor of a key component includes a base, an image size measurement system, a white light interferometry system, and a rotating stage. The image size measurement system is fixedly installed on both sides of the base. The white light interferometry system is fixedly erected on the upper side of the base via a Z-axis moving device. The rotating stage is fixedly installed on the base via a precision two-dimensional moving platform. The notched sample is disassembled and fixed on the rotating stage.

[0008] Furthermore, the image size measurement system includes a CCD industrial camera, a telecentric lens, and a coaxial parallel light source. The CCD industrial camera is fixed to one side of the base via a mounting bracket. The telecentric lens is located on the other side of the mounting bracket, corresponding to the position of the CCD industrial camera. The coaxial parallel light source is fixed on the side of the base away from the telecentric lens.

[0009] Furthermore, the white light interferometry system includes a second CCD industrial camera, a white light interferometer lens, and a white light source. The second CCD industrial camera is fixed on the Z-axis moving device via a connecting bracket. The white light interferometer lens is installed on the side of the second CCD industrial camera close to the notched sample, and the white light source is fixed on one side of the white light interferometer lens.

[0010] Furthermore, the Z-axis moving device includes a ball screw and a piezoelectric ceramic. The ball screw is fixed to the upper side of the base by a mounting bracket, the piezoelectric ceramic is fixedly mounted on the ball screw, and the second CCD industrial camera is fixed to the piezoelectric ceramic by a connecting bracket.

[0011] Furthermore, the rotary table includes a rotary drive motor, a clamping turntable, and a fixed platform. The precision two-dimensional moving platform is provided with a mounting plate. The rotary drive motor is fixedly mounted on one side of the mounting plate and its output shaft passes through the mounting plate. The clamping turntable is fixed on the output shaft of the rotary drive motor. The fixed platform is installed on the end of the mounting plate away from the clamping turntable. The notched sample is clamped between the clamping turntable and the fixed platform.

[0012] Furthermore, the mounting plate is fixed to the nut of the ball screw and slides relative to the ball screw.

[0013] Furthermore, the detection method using a detection device with parameters related to the stress concentration factor of critical components includes the following steps:

[0014] S1: Images of the notched sample are acquired using a CCD industrial camera, a telecentric lens, and a coaxial parallel light source.

[0015] S2: Use a CCD industrial camera, a white light interference lens, a white light source, and a ball screw to collect point clouds of the micro-morphology of the bottom surface of the notched sample.

[0016] S3: Obtain the structural stress concentration characterization parameters of the notched specimen using image size measurement technology.

[0017] The structural stress concentration characterization parameters include the notch depth h, the radius r of the notch bottom arc, and the notch angle Φ. The Hough transform is used to detect the line and the circle, and the radius r of the notch bottom arc and the notch angle Φ are calculated accordingly. The image grayscale values ​​are used to traverse and find feature points to calculate the notch depth h.

[0018] S4: Obtain the microscopic image of the bottom of the notch based on the image size measurement system, perform trend leveling on the micro-morphology point cloud obtained by the white light interferometry system, process the micro-morphology point cloud of the bottom surface of the notch based on the white light interferometry system, determine the range of the selected curve trend based on the size of the lowest point of the notch in the image in step S1 and the sampled point cloud, obtain the trend of the curve at the bottom of the notch using image processing and expand it into a smooth surface, subtract the expanded smooth surface from the rough surface obtained by measurement to obtain the surface micro-morphology after trend removal, and remove noise points by median filtering;

[0019] S5: Calculate the three-dimensional characterization parameters of surface micromorphology in ISO 25178 for the point cloud after trend removal, extract the two-dimensional cross-sectional profile from the three-dimensional point cloud, and calculate the two-dimensional characterization parameters in ISO 4287 using the formula.

[0020] Furthermore, the calculation formula and results for the two-dimensional surface stress concentration characterization parameters are as follows:

[0021]

[0022] Among them, the arithmetic mean deviation of the profile R a Maximum outline height R z Average height R of the contour unit y .

[0023] Furthermore, the calculation formula and results for the three-dimensional surface stress concentration characterization parameters are as follows:

[0024]

[0025] S z =Z max (x, y) + Z min (x, y)

[0026]

[0027] Among them, surface roughness S a Maximum peak-to-valley height S z 10 o'clock height S z10 .

[0028] The beneficial effects achieved by the present invention using the above structure are as follows:

[0029] 1. By setting up an image size measurement system and a white light interferometry system, the steps are simplified and the measurement of dimensional parameters related to structural stress concentration and surface characterization parameters related to surface stress concentration can be performed simultaneously.

[0030] 2. By setting up a rotary table to rotate the sample, the surface morphology of different areas of the sample can be measured, thus overcoming the error caused by manual rotation;

[0031] 3. The surface topography point cloud trend is removed by using notched sample images to calculate the surface stress concentration characterization parameters. Attached Figure Description

[0032] Figure 1 This is a schematic diagram of the overall structure of a detection device for parameters related to the stress concentration factor of key components proposed in this invention.

[0033] Figure 2 This is a schematic diagram of the structure of a detection device for parameters related to the stress concentration factor of key components proposed in this invention from another angle.

[0034] Figure 3 This is a schematic diagram of the third angle of a detection device for parameters related to the stress concentration factor of key components proposed in this invention;

[0035] Figure 4 This is a flowchart of a detection method for a detection device for parameters related to the stress concentration factor of key components, as proposed in this invention.

[0036] Figure 5 This is a schematic diagram of the structural stress concentration characterization parameters of a detection device for a parameter related to the stress concentration factor of a key component proposed in this invention.

[0037] Figure 6 This is a schematic diagram of the Hough line detection method for a detection device for parameters related to the stress concentration factor of key components proposed in this invention.

[0038] Figure 7 This is a schematic diagram illustrating the notch depth calculation method of a detection device for a parameter related to the stress concentration factor of a key component proposed in this invention.

[0039] Figure 8 This is a schematic diagram of the Hough circle detection method for a detection device for parameters related to stress concentration factors of key components proposed in this invention.

[0040] Figure 9This is a schematic diagram of the trend leveling process of a detection method for a detection device for parameters related to the stress concentration factor of key components proposed in this invention.

[0041] Figure 10 This is a schematic diagram illustrating the calculation process of two-dimensional surface stress concentration characterization parameters for a detection device for parameters related to the stress concentration factor of key components proposed in this invention.

[0042] The components include: 1. Base; 2. Image size measurement system; 3. White light interferometry measurement system; 4. Z-axis moving device; 5. Precision two-dimensional moving platform; 6. Rotary stage; 7. Notched sample; 8. CCD industrial camera one; 9. Telecentric lens; 10. Coaxial parallel light source; 11. CCD industrial camera two; 12. White light interferometry lens; 13. White light source; 14. Ball screw; 15. Piezoelectric ceramic; 16. Rotary drive motor; 17. Clamping turntable; 18. Fixed stage.

[0043] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used together with the embodiments of the invention to explain the invention and do not constitute a limitation thereof. Detailed Implementation

[0044] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are within the scope of protection of the present invention.

[0045] like Figure 1-3 As shown, the present invention proposes a detection device for parameters related to the stress concentration factor of key components, including a base 1, an image size measurement system 2, a white light interferometry system 3, and a rotating stage 6. The image size measurement system 2 is fixedly installed on both sides of the base 1. The white light interferometry system 3 is fixedly erected on the upper side of the base 1 via a Z-axis moving device 4. The rotating stage 6 is fixedly installed on the base 1 via a precision two-dimensional moving platform 5. The notched sample 7 is disassembled and fixed on the rotating stage 6.

[0046] In order to acquire images of the structural stress concentration characterization parameters of the notched specimen to be calculated, the image size measurement system 2 includes a CCD industrial camera 8, a telecentric lens 9, and a coaxial parallel light source 10. The CCD industrial camera 8 is fixed to one side of the base 1 by a mounting bracket. The telecentric lens 9 is located on the other side of the mounting bracket and corresponds to the position of the CCD industrial camera 8. The coaxial parallel light source 10 is fixed on the side of the base 1 away from the telecentric lens 9.

[0047] To acquire images of the bottom of the notched sample, the white light interferometry system 3 includes a CCD industrial camera 11, a white light interferometer lens 12, and a white light source 13. The CCD industrial camera 11 is fixed on the Z-axis moving device 4 via a connecting bracket. The white light interferometer lens 12 is installed on the side of the CCD industrial camera 11 close to the notched sample 7, and the white light source 13 is fixed on one side of the white light interferometer lens 12.

[0048] To facilitate adjustment of the distance between the white light interferometry system 3 and the notched sample 7, the Z-axis moving device 4 includes a ball screw 14 and a piezoelectric ceramic 15. The ball screw 14 is fixed to the upper side of the base 1 via a mounting bracket, and the piezoelectric ceramic 15 is fixedly mounted on the ball screw 14. The CCD industrial camera 11 is fixed to the piezoelectric ceramic 15 via a connecting bracket. The piezoelectric ceramic 15 is used to continuously acquire multiple images of the bottom of the notched sample 7, and then the images are processed using a point cloud algorithm to generate a point cloud of the micro-morphology of the bottom surface of the notched sample 7. To reduce the trouble and errors caused by manual rotation, the rotating stage 6 includes a rotary table. The precision two-dimensional moving platform 5 is equipped with a mounting plate, a rotary drive motor 16, a clamping turntable 17, and a fixed stage 18. The rotary drive motor 16 is fixed on one side of the mounting plate and its output shaft passes through the mounting plate. The clamping turntable 17 is fixed on the output shaft of the rotary drive motor 16. The fixed stage 18 is installed on the end of the mounting plate away from the clamping turntable 17. The notched sample 7 is clamped between the clamping turntable 17 and the fixed stage 18. The precision two-dimensional moving platform and the rotary stage are used to adjust the position of the sample to acquire images of different areas. The mounting plate is fixed on the nut of the ball screw 14 and slides relative to the ball screw 14.

[0049] During the specific measurement, images were acquired using CCD industrial cameras 8 and 11. Images of the notched sample 7 were acquired using a telecentric lens 9 and the industrial cameras. Next, a known object, such as a calibration plate, was selected as a standard calibrator for image calibration. After calibration, the acquired notched images were preprocessed using the OpenCV computer vision library, including binarization and noise removal. After preprocessing, the stress concentration parameters of the structure were measured. The measured parameters included the notch depth h, the notch angle Φ, and the radius r of the notch bottom arc. Figure 5 As shown.

[0050] When calculating the notch angle, the Canny edge detection algorithm and Hough line transform are used to extract straight lines with edge features from the image. The straight lines at both ends of the notched sample are obtained through threshold adjustment and slope filtering methods. The notch angle is then calculated using the angles returned from these two straight lines. The calculation process is as follows: Figure 6 As shown.

[0051] To calculate the notch depth, the image is first rotated using the tilt angle of the edge line at the notch-free point of the specimen, ensuring the edge line is vertical. The bottom point of the notch is then obtained by traversing the image, and the notch depth is calculated based on the vertical distance from this bottom point to the edge line. The calculation process is as follows: Figure 7 As shown.

[0052] To calculate the radius of the arc at the bottom of the notch, first obtain the bottom point of the notch and its neighboring points in the image. Then, perform a Hough circle transform on this region to find areas with circular features and fit a circle. By adjusting the threshold and using a center selection method, obtain the circle at the bottom arc of the notch. Return the diameter of this circle, thus obtaining the radius of the arc at the bottom of the notch. The calculation process is as follows: Figure 8 As shown.

[0053] The original images of the notched sample 7 were acquired using a piezoelectric ceramic 15, a CCD industrial camera 11, and a white light interferometer lens 12. The images were numbered sequentially according to the acquisition order, with different numbers representing acquisition positions at different heights. Next, a point cloud extraction algorithm was applied to the acquired images. The maximum grayscale value of each pixel in all images was compared, and the image with the maximum grayscale value was selected to represent the relative height of that point. This height data was then used for interpolation calculations and noise removal preprocessing to obtain the surface micro-morphology point cloud of the notch. The trend at the bottom of the notch was extracted based on the size of the image sampling area. The smooth surface at the bottom of the notch was fitted using the least squares method. The micro-morphology point cloud with the trend removed was obtained based on the residual between the obtained surface micro-morphology point cloud and the smooth surface. The processing procedure is as follows: Figure 9 As shown.

[0054] Finally, the surface stress concentration characterization parameters are calculated on the trend-leveled point cloud. When calculating the two-dimensional stress characterization parameters, the three-dimensional point cloud is first converted into a two-dimensional height map. The location of the two-dimensional contour to be calculated is determined by drawing horizontal lines on the two-dimensional height map. Figure 10 As shown. Substituting the height data at this location into the calculation formula for the two-dimensional characterization parameters, the arithmetic mean deviation R of the profile is calculated. a Maximum outline height R z Average height R of the contour unit y The calculation formula is:

[0055]

[0056] R z =Z p +Z v

[0057]

[0058] Substituting the height data of all sampled point clouds into the calculation formula for the three-dimensional characterization parameters yields the surface roughness S. a Maximum peak-to-valley height S z 10 o'clock height S z10 The calculation formula is:

[0059]

[0060] S z =Z max (x, y) + Z min (x, y)

[0061]

[0062] The calculation results are as follows Figure 10 As shown.

[0063] It should be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, 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 process, method, article, or apparatus.

[0064] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

[0065] The present invention and its embodiments have been described above. This description is not restrictive, and the accompanying drawings are only one embodiment of the present invention; the actual structure is not limited thereto. In conclusion, if those skilled in the art are inspired by this description and design similar structures and embodiments without departing from the spirit of the invention, such designs should fall within the protection scope of the present invention.

Claims

1. A detection method of a detection device of a parameter related to a stress concentration factor of a critical component, characterized in that: The detection device comprises a base (1), an image size measurement system (2), a white light interference measurement system (3) and a rotating table (6), the image size measurement system (2) is fixedly installed on both sides of the base (1), the white light interference measurement system (3) is fixedly erected on the upper side of the base (1) through a Z-axis moving device (4), and the rotating table (6) is fixedly arranged on the base (1) through a precise two-dimensional moving platform (5), and a notch sample (7) is detachably fixed on the rotating table (6); The image size measurement system (2) comprises a CCD industrial camera (8), a telecentric lens (9) and a coaxial parallel light source (10), the CCD industrial camera (8) is fixed on one side of the base (1) through a mounting seat, the telecentric lens (9) is arranged at a position corresponding to the CCD industrial camera (8) on the other side of the mounting seat, and the coaxial parallel light source (10) is fixedly arranged on the side of the base (1) away from the telecentric lens (9); The white light interference measurement system (3) comprises a CCD industrial camera (11), a white light interference lens (12) and a white light source (13), the CCD industrial camera (11) is fixed on the Z-axis moving device (4) through a connecting frame, the white light interference lens (12) is installed on the side of the CCD industrial camera (11) close to the notch sample (7), and the white light source (13) is fixed on the side of the white light interference lens (12); The Z-axis moving device (4) comprises a ball screw (14) and a piezoelectric ceramic (15), the ball screw (14) is fixed on the upper side of the base (1) through a mounting bridge, and the piezoelectric ceramic (15) is fixedly installed on the ball screw (14), and the CCD industrial camera (11) is fixed on the piezoelectric ceramic (15) through the connecting frame; The detection method of the detection device comprises the following steps: S1: acquiring a picture of the notch sample by using the CCD industrial camera (8), the telecentric lens (9) and the coaxial parallel light source (10); S2: acquiring a bottom surface micro-morphology point cloud of the notch sample by using the CCD industrial camera (11), the white light interference lens (12), the white light source (13) and the ball screw (14); S3: obtaining a structural stress concentration representation parameter size of the notch sample by using an image size measurement technology, wherein the structural stress concentration representation parameter comprises a notch depth h, a notch bottom circular arc radius r and a notch angle Φ, a straight line and a circle are detected by using a Hough transform, so as to calculate the notch bottom circular arc radius r and the notch angle Φ, and a feature point is found by using image gray value traversal, so as to calculate the notch depth h. S4: Obtain the microscopic image of the notch bottom according to the image size measurement system (2), trend leveling is performed on the micro-topography point cloud obtained by the white light interference measurement system (3), the micro-topography point cloud of the notch bottom surface based on the white light interference measurement system (3) is processed, the range of the selected curve trend is determined according to the size of the lowest bottom point of the notch and the sampling point cloud, the trend of the curve is obtained by image processing and is converted into a smooth curved surface, the rough curved surface obtained by measurement is subtracted from the converted smooth curved surface to obtain the curved surface after trend removal, and the noise points are removed by median filtering; S5: Calculate the surface micro-topography three-dimensional characterization parameters of the point cloud after trend removal, extract the two-dimensional cross-section profile in the three-dimensional point cloud, and calculate the two-dimensional characterization parameters by formula.

2. The detection method of the device for detecting a parameter related to the stress concentration factor of a critical component according to claim 1, characterized in that: The rotating table (6) comprises a rotating drive motor (16), a clamping turntable (17) and a fixed table (18), the precise two-dimensional moving platform (5) is provided with a mounting plate, the rotating drive motor (16) is fixedly arranged on one side of the mounting plate and the output shaft penetrates through the mounting plate, the clamping turntable (17) is fixed on the output shaft of the rotating drive motor (16), the fixed table (18) is installed at one end of the mounting plate away from the clamping turntable (17), and the notch sample (7) is clamped between the clamping turntable (17) and the fixed table (18).

3. The detection method of the detection device for parameters related to the stress concentration factor of key components according to claim 2, characterized in that: The mounting plate is fixed on the nut of the ball screw (14) and slides relative to the ball screw (14).

4. The detection method of the detection device for parameters related to the stress concentration factor of key components according to claim 3, characterized in that: The two-dimensional characterization parameter calculation formula and calculation result are as follows: R z = Z p + Z v wherein the profile arithmetic mean deviation R a , the profile maximum height R z , the average height of the profile elements R y .

5. The method of claim 4, wherein the parameter is a stress concentration factor of the critical component. The three-dimensional characterization parameter calculation formula and calculation result are as follows: The three-dimensional characterization parameter calculation formula and calculation result are as follows: ​ S z = Z max (x,y) + Z min (x,y) wherein the surface roughness S a , the maximum peak-valley height S z , the ten-point height S z10 .

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