Structural member curved surface waviness detection method, device, equipment and medium

Abstract

The invention discloses a structural member curved surface waviness detection method, device and equipment and a medium, relates to the technical field of waviness detection, and aims to solve the technical problems of poor detection precision, poor applicability, low efficiency, narrow detection range and the like in the prior art. The method comprises the following steps: scanning a measurement area of a to-be-measured structural member according to a preset scanning path by adopting a three-coordinate measuring machine to obtain scanning data; wherein the measurement area is a free-form surface; the scanning data comprises point position information of each measurement point; comparing the scanning data with a theoretical model of the to-be-measured structural member to obtain a normal distance of each measurement point; and according to the normal distance of each measurement point, the waviness of the measurement area is obtained, so that the waviness detection function which is not possessed by the existing mainstream three-coordinate measuring machine is supplemented, the detection of the waviness of the curved surface of the large complex structural member is realized, and the method has the advantages of wide detection range, high efficiency and the like.

Description

Technical Field

[0001] This application relates to the field of waviness detection technology, and provides a method, apparatus, equipment and medium for detecting the waviness of curved surfaces of structural components. Background Technology

[0002] Currently, there are two main methods for measuring the surface waviness of parts in the industry: (1) Measurement is performed by combining industrial fast-curing material reverse copying and microscopy. The method uses depth ratio for quantitative judgment. Although this method has high sampling accuracy and a resolution of up to 0.1μm, it cannot be used for large parts because the microscope has a small measurement range. (2) Measurement is performed by using a roughness tester. The tester automatically scans the measurement surface with a metal probe. It does not require a theoretical model and can directly obtain the surface waviness of the workpiece. It has the advantages of accurate and fast measurement. However, the probe of the existing roughness tester can only move linearly within the measurement range. According to the survey, the maximum size of the worktable of the existing roughness tester is only 1000mm×1000mm, which is not suitable for measuring large and complex curved parts.

[0003] In addition, the national standard GB / T16747-2009 uses the amplitude value as the basic parameter for evaluating waviness. The waviness measurement results of the ground surface are obtained after filtering by various methods. At the same time, the evaluation parameters of waviness, the radius of curvature of the probe, the cutoff value and the average amplitude of waviness are specified. However, since it is difficult to process irregular surfaces by grinding, the grinding standard only focuses on straight lines or arcs and lacks waviness measurement of free-form surfaces. Summary of the Invention

[0004] This application provides a method, apparatus, equipment, and medium for detecting the waviness of curved surfaces of structural components, which solves the technical problems of poor detection accuracy, poor applicability, low efficiency, and narrow detection range in the prior art.

[0005] On the one hand, a method for detecting the waviness of a structural component surface is provided, the method comprising: A coordinate measuring machine is used to scan the measurement area of ​​the structural component under test according to a preset scanning path to obtain scanning data; wherein, the measurement area is a freeform surface; the scanning data contains the position information of each measurement point; The scanned data is compared with the theoretical model of the structure under test to obtain the normal distance of each measurement point; The waviness of the measurement area is obtained based on the normal distance of each measurement point.

[0006] Optionally, the step of comparing the scanned data with the theoretical model of the structure under test to obtain the normal distance of each measurement point includes: For any sampling interval, least squares linear fitting is performed on each measurement point within the sampling interval to obtain the fitting curve; For any measurement point within any sampling interval, the slope of the line profile of any measurement point in the fitted curve is taken as the reference profile vector direction of the measurement point. The distance between any measurement point and the fitted curve is taken as the axial distance of any measurement point; The normal distance of any measurement point is obtained based on the axial distance of any measurement point and the direction of the reference profile vector.

[0007] Optionally, the step of obtaining the waviness of the measurement area based on the normal distance of each measurement point includes: For any sampling interval, the maximum normal distance and the minimum normal distance of all measurement points in the sampling interval are taken as the peak and trough values ​​of the sampling interval. The waviness peak and valley values ​​of the measurement area are obtained based on the peak and valley values ​​of each sampling interval. The waviness of the measurement area is obtained by the absolute value of the difference between the peak value and the trough value of the waviness of the measurement area.

[0008] Optionally, after using a coordinate measuring machine to scan the measurement area of ​​the structural component to be measured and obtaining the scan data, the method further includes: For any given sampling interval, perform univariate linear regression on each measurement point in the given sampling interval to obtain a univariate linear regression model for the given sampling interval. Based on the univariate linear regression model, obtain the set of fitted theoretical contour heights corresponding to any sampling interval; Based on the actual contour height set of any sampling interval and the fitted theoretical contour height set, obtain the contour height difference set corresponding to any sampling interval; The ripple degree of any sampling interval is obtained by using the absolute value of the difference between the maximum and minimum profile height differences in the set of profile height differences.

[0009] Optionally, before using a coordinate measuring machine to scan the measurement area of ​​the structural component to be measured according to a preset scanning path to obtain scan data, the method further includes: Adjust the orientation of the structure under test and over-clamp the structure under test; Establish the coordinate system of the structural component to be tested; Import the digital model file of the structural component to be tested into the measurement software of the measuring machine; wherein the digital model file contains a preset scanning path.

[0010] Optionally, before using a coordinate measuring machine to scan the measurement area of ​​the structural component to be measured according to a preset scanning path to obtain scan data, the method further includes: The scanning parameters are set, including probe type, scanning mode, scanning increment, and sampling length.

[0011] Optionally, the probe type is a Φ1mm spherical probe, the scanning method is an open-line scanning method, the scanning increment is in the range of 0.06mm to 0.12mm, and the sampling length is 6mm.

[0012] On the one hand, a device for detecting the waviness of a structural component surface is provided, the device comprising: The area scanning unit is used to scan the measurement area of ​​the structural component under test using a coordinate measuring machine according to a preset scanning path to obtain scanning data; wherein, the measurement area is a freeform surface; the scanning data includes the position information of each measurement point; The data comparison unit is used to compare the scanned data with the theoretical model of the structure under test to obtain the normal distance of each measurement point; The waviness acquisition unit is used to obtain the waviness of the measurement area based on the normal distance of each measurement point.

[0013] On one hand, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement any of the methods described above.

[0014] On the one hand, a storage medium is provided that stores computer program instructions thereon, which, when executed by a processor, implement any of the methods described above.

[0015] Compared with the prior art, the beneficial effects of this application are as follows: In this application, when performing waviness detection on the curved surface of a structural component, firstly, a coordinate measuring machine can be used to scan the measurement area of ​​the structural component under test according to a preset scanning path to obtain scanning data; wherein, the scanning data contains the position information of each measurement point; the measurement area is a free-form surface; then, the scanning data can be compared with the theoretical model of the structural component under test to obtain the normal distance of each measurement point; finally, the waviness of the measurement area can be obtained based on the normal distance of each measurement point.

[0016] Therefore, in this application, since a coordinate measuring machine (CMM) is used to inspect the surface waviness of structural components, compared with existing microscopes and roughness testers, this application, relying on the high precision of the CMM, can not only accurately measure the external dimensions of structural components, but also precisely measure their form and position tolerances. Furthermore, because the CMM has a larger inspection range and variable probe angle, it can adapt to scanning complex curved surfaces and even closed-angle regions. Moreover, the inspection and data processing processes are automatically run based on pre-programmed procedures. Therefore, this application not only boasts advantages such as high inspection accuracy, applicability, efficiency, and a wide inspection range, but also avoids the subjective qualitative judgment of traditional "visual inspection and tactile examination," eliminating human intervention. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0018] Figure 1 This is a schematic diagram of an application scenario provided by an embodiment of this application; Figure 2 A schematic diagram of a method for detecting the surface waviness of structural components provided in an embodiment of this application; Figure 3 A schematic diagram of normal distance and waviness provided for an embodiment of this application; Figure 4 This is a schematic diagram of a structural component surface waviness detection device provided in an embodiment of this application.

[0019] The diagram is labeled as follows: 10-Structural component surface waviness detection device, 101-Processor, 102-Memory, 103-I / O interface, 104-Database, 40-Structural component surface waviness detection device, 401-Area scanning unit, 402-Data comparison unit, 403-Waviness acquisition unit, 404-Measurement preparation unit, 405-Scanning parameter setting unit. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. Based on the embodiments of 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 specified, the embodiments and features in the embodiments of this application can be arbitrarily combined with each other. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than that shown here.

[0021] Currently, there are two main methods for measuring the surface waviness of parts in the industry: (1) Measurement is performed by combining industrial fast-curing material reverse copying and microscopy. The method uses depth ratio for quantitative judgment. Although this method has high sampling accuracy and a resolution of up to 0.1μm, it cannot be used for large parts because the microscope has a small measurement range. (2) Measurement is performed by using a roughness tester. The tester automatically scans the measurement surface with a metal probe. It does not require a theoretical model and can directly obtain the surface waviness of the workpiece. It has the advantages of accurate and fast measurement. However, the probe of the existing roughness tester can only move linearly within the measurement range. According to the survey, the maximum size of the worktable of the existing roughness tester is only 1000mm×1000mm, which is not suitable for measuring large and complex curved parts.

[0022] In addition, the national standard GB / T16747-2009 uses the amplitude value as the basic parameter for evaluating waviness. The waviness measurement results of the ground surface are obtained after filtering by various methods. At the same time, the evaluation parameters of waviness, the radius of curvature of the probe, the cutoff value and the average amplitude of waviness are specified. However, since it is difficult to process irregular surfaces by grinding, the grinding standard only focuses on straight lines or arcs and lacks waviness measurement of free-form surfaces.

[0023] Based on this, this application provides a method for detecting the surface waviness of structural components. In this method, firstly, a coordinate measuring machine (CMM) is used to scan the measurement area of ​​the structural component under test according to a preset scanning path to obtain scanning data. The scanning data includes the positional information of each measurement point; the measurement area is a free-form surface. Then, the scanning data is compared with the theoretical model of the structural component under test to obtain the normal distance of each measurement point. Finally, the waviness of the measurement area is obtained based on the normal distance of each measurement point. Therefore, in this application, because a CMM is used to detect the surface waviness of the structural component, compared to existing microscopes and roughness testers, this application, relying on the high precision of the CMM, can not only accurately measure the external dimensions of the structural component but also precisely measure its form and position tolerances. Furthermore, since the coordinate measuring machine has a larger detection range and a variable probe angle, it can adapt to scanning complex curved surfaces and even closed-angle regions. Moreover, the detection and data processing processes rely on pre-programmed procedures to run automatically. Therefore, this application not only has the advantages of high detection accuracy, applicability, efficiency, and wide detection range, but also avoids the subjective qualitative judgment of traditional "seeing and touching" and eliminates human intervention.

[0024] After introducing the design concept of the embodiments of this application, the following is a brief introduction to the application scenarios to which the technical solutions of the embodiments of this application can be applied. It should be noted that the application scenarios described below are only for illustrating the embodiments of this application and are not intended to limit the scope. In specific implementation, the technical solutions provided by the embodiments of this application can be flexibly applied according to actual needs.

[0025] like Figure 1 The diagram shown illustrates an application scenario provided by an embodiment of this application. This application scenario may include a structural component surface waviness detection device 10.

[0026] The structural component surface waviness detection device 10 can be used to detect the waviness of structural component surfaces. For example, it can be used with in-vehicle computers, personal computers (PCs), servers, and laptops. The structural component surface waviness detection device 10 may include one or more processors 101, memory 102, I / O interfaces 103, and databases 104. Specifically, the processor 101 can be a central processing unit (CPU) or a digital processing unit, etc. The memory 102 can be volatile memory, such as random-access memory (RAM); the memory 102 can also be non-volatile memory, such as read-only memory, flash memory, hard disk drive (HDD), or solid-state drive (SSD); or the memory 102 can be any other medium capable of carrying or storing desired program code in the form of instructions or data structures that can be accessed by a computer, but is not limited thereto. The memory 102 can be a combination of the above-mentioned memories. The memory 102 can store some program instructions of the structural component surface waviness detection method provided in the embodiments of this application. When these program instructions are executed by the processor 101, they can be used to implement the steps of the structural component surface waviness detection method provided in the embodiments of this application, so as to solve the technical problems of poor detection accuracy, poor applicability, low efficiency and narrow detection range in the prior art. The database 104 can be used to store data such as scanning data, theoretical models of the structural components under test, univariate linear regression models and contour height difference sets involved in the solutions provided in the embodiments of this application.

[0027] In this embodiment, the structural component surface waviness detection device 10 can obtain waviness detection instructions through the I / O interface 103. Then, the processor 101 of the structural component surface waviness detection device 10 will solve the technical problems existing in the prior art, such as poor detection accuracy, poor applicability, low efficiency, and narrow detection range, according to the program instructions of the structural component surface waviness detection method provided in this embodiment of the application stored in the memory 102. In addition, the scan data, the theoretical model of the structural component under test, the univariate linear regression model, and the contour height difference set can be stored in the database 104.

[0028] Of course, the methods provided in the embodiments of this application are not limited to... Figure 1 The application scenarios shown can also be used in other possible scenarios, and this application embodiment does not impose any limitations. Figure 1The functions that the various devices in the application scenarios shown can achieve will be described in subsequent method embodiments, and will not be elaborated on here. Below, the methods of the embodiments of this application will be described in conjunction with the accompanying drawings.

[0029] like Figure 2 The diagram shown is a flowchart illustrating a method for detecting the surface waviness of structural components according to an embodiment of this application. This method can... Figure 1 The structural component surface waviness detection equipment 10 is used to perform the operation. Specifically, the process of this method is described as follows.

[0030] Step 201: Using a coordinate measuring machine, scan the measurement area of ​​the structural component to be measured according to the preset scanning path to obtain scanning data.

[0031] The measurement area is a freeform surface; the scan data contains the location information of each measurement point.

[0032] Specifically, in order to enable the structural component under test to be automatically detected based on a preset scanning path, in this embodiment of the application, before using a coordinate measuring machine to scan the measurement area of ​​the structural component under test according to the preset scanning path and obtaining the scanning data, "measurement preparation" can also be performed.

[0033] That is, firstly, the orientation of the structure to be measured can be determined, and the structure to be measured can be clamped to ensure that the structure to be measured has a fixed relationship with the mechanical coordinate system of the equipment, thereby realizing automatic rotation measurement of curved surfaces when multi-angle detection is involved in curved surface measurement.

[0034] Then, the coordinate system of the structure to be tested can be manually established.

[0035] Next, the digital model file of the structural component to be tested can be imported into the measuring machine's software. Using the workpiece function in the CAD module of the measuring machine's software, the coordinate system of the structural component to be tested can be associated with the digital model, ensuring that the axis and origin of the structural component's coordinate system are consistent with the digital model. To quickly and accurately obtain waviness detection results for critical areas, the digital model file also contains preset scanning paths. Furthermore, in practical applications, the scanning point acquisition frequency can be set to 1000 points / second; the larger the scanning area, the longer the scanning and calculation time.

[0036] Then, you can select the starting point, direction point, and ending point on the digital model and adjust them to a single cross section to ensure that the scanning path is at the same height.

[0037] Furthermore, after completing the "measurement preparation," the scanning parameters can be set. These parameters include key factors such as stylus type, scanning method, scanning increment, and sampling length. Specifically, as shown in Table 1, which is a schematic table of scanning parameters provided in this embodiment, the stylus type can be set to a Φ1mm spherical stylus to ensure full coverage of all waviness textures and to avoid damaging the part surface. The scanning method can be set to an open-line scanning method to ensure high accuracy and fast scanning speed for various curved surfaces. The scanning increment can be set to the range of 0.06mm to 0.12mm to ensure reasonable density of the scanned point pattern, high measurement accuracy, and high measurement efficiency. The sampling length can be set to 6mm to ensure coverage of the waviness variation range caused by different cutting parameters.

[0038] Table 1

[0039] Then, after all the preparations are completed, the subsequent "surface waviness inspection of structural components" can be carried out.

[0040] Specifically, a coordinate measuring machine can be used to perform a full-area scan of the measurement area (the area where the surface waviness of the part is concentrated) of the structural component under test according to the preset scanning path in the digital model file, and obtain scan data. The measurement area contains L measurement points and multiple sampling intervals consisting of M consecutive measurement points, where M = sampling length / measurement increment. The first sampling interval is taken from the first measurement point to the Mth measurement point, and then the second sampling interval is obtained by shifting one measurement point to the right, and so on, to obtain N sampling intervals, where N = LM.

[0041] Step 202: Compare the scanned data with the theoretical model of the structure to be tested to obtain the normal distance of each measurement point.

[0042] Specifically, firstly, the starting position of the scan can be set as the x-coordinate. The origin, with M detection points in a sampling interval, will have the coordinates... The measurement coordinates obtained by point scanning are marked .

[0043] Then, for any sampling interval, a least-squares linear fit can be performed on each measurement point within that interval to obtain a fitted curve; that is, in order to simulate the theoretical reference profile corresponding to any sampling interval, a least-squares linear fit (or cubic polynomial curve fit) can be performed on the measurement points of that sampling interval, and the equation of the fitted curve is as follows:

[0044] Therefore, the formula for the coordinates of the actual measured point is as follows:

[0045] in, The coefficients of the fitted curve equation are... Let i be the coordinates of a measurement point i within any sampling interval, i = 1, 2, 3, 4...M. Let i be the axial distance from the measurement point i to the fitted curve.

[0046] Next, for any measurement point within any sampling interval, the slope of the line profile at any measurement point in the fitted curve is defined as the reference profile vector direction of that measurement point; that is, the reference profile vector direction of measurement point i. It can be expressed using the following formula:

[0047] Then, the distance between any measurement point and the fitted curve can be taken as the axial distance of any measurement point; that is, the axial distance from measurement point i to the fitted curve in the sampling interval. The formula is expressed as follows:

[0048] Next, the axial distance of any measurement point i can be used as a reference. and reference profile vector direction This is used to obtain the normal distance of any measurement point i within any sampling interval. The formula is expressed as follows:

[0049] Step 203: Obtain the waviness of the measurement area based on the normal distance of each measurement point.

[0050] Specifically, firstly, for any given sampling interval, substitute all the measurement points within that interval with the normal distance. The formula is used to select the maximum normal distance as follows. minimum normal distance :

[0051]

[0052] Then, the maximum and minimum normal distances of all measurement points within any sampling interval can be used as the peak and trough values ​​of that sampling interval; that is, the maximum normal distance. That is, the minimum normal distance corresponding to the peak value of any sampling interval. That is, the trough value corresponding to any sampling interval.

[0053] Next, the waviness peak and trough values ​​of the measurement area can be obtained based on the peak and trough values ​​of each sampling interval; that is, the waviness peak and trough values ​​of the current measurement area can be obtained by calculating the peak and trough values ​​of all sampling intervals, as shown in the following formula:

[0054]

[0055] in, The peak value of the waviness in the measurement area. The value represents the trough value of the waviness in the measurement area.

[0056] Finally, the waviness of the measurement area can be directly obtained from the absolute value of the difference between the peak and trough values ​​of the waviness in the measurement area. That is, the absolute value of the difference between the peak and trough values ​​of the waviness is the waviness. :

[0057] In another possible implementation, to eliminate the influence of errors introduced by tool wear, machine tool precision, etc., on the measurement results, in this embodiment, after using a coordinate measuring machine to scan the measurement area of ​​the structural component to be measured and obtaining the scan data, a "univariate linear regression processing" can be introduced to obtain a more accurate surface waviness of the structural component. .

[0058] Specifically, firstly, for any given sampling interval, a univariate linear regression can be performed on each measurement point within that interval to obtain a univariate linear regression model for that interval. That is, by substituting the corresponding set of sampled data into the interval, a univariate linear regression model for that set of sampled data can be obtained.

[0059] Then, based on the univariate linear regression model, the set of fitted theoretical profile heights corresponding to any sampling interval can be obtained; that is, the fitted theoretical profile height of measurement point i can be expressed by the following formula. :

[0060] Next, the set of contour height differences corresponding to any sampling interval can be obtained by comparing the actual contour height set with the fitted theoretical contour height set for any sampling interval; that is, the difference can be obtained by measuring the actual contour height of point i. With respect to the fitting theoretical profile height The difference is used to calculate the profile height difference at measurement point i. :

[0061] Finally, the waviness of any sampling interval can be obtained directly from the absolute value of the difference between the maximum and minimum profile height differences in the set of profile height differences. That is, within any sampling interval, the profile height difference can be defined. The maximum value is the peak value within this sampling interval. Contour height difference Minimum value is the valley value The absolute value of the difference between the two is the ripple level within that sampling interval. ,Right now:

[0062] Of course, if you want to obtain the waviness within the measurement area Therefore, it is necessary to obtain the set of contour height differences corresponding to the measurement area based on the actual contour height set and the fitted theoretical contour height set of the measurement area. Similarly, the waviness of the measurement area can be obtained directly from the absolute value of the difference between the maximum and minimum contour height differences in the set of contour height differences of the measurement area. Specific implementation examples: Assuming the measurement area of ​​the structural component under test has a total of 180 measurement points, i.e., L=180, then according to the parameter settings in Table 1, the number of continuous measurement points forming the sampling interval M=sampling length / measurement increment=6 / 0.12=40, and the number of sampling intervals N=L-M+1=131, that is, there are 40 sampling intervals, and each sampling interval has 131 continuous measurement points.

[0064] Furthermore, taking the 40 measurement points in the first sampling interval as an example, as shown in Table 2, which is a schematic table of measurement point coordinates for the first sampling interval provided in this application embodiment, the least squares linear fitting is performed on the first measurement point to the 40th measurement point to obtain the model parameters of the polynomial fitting curve: p1=-0.0109, p2=-1.0205, p3=-33.4640, p4=-336.4193.

[0065] Table 2

[0066] Then, substitute all the measurement points within the first sampling interval into the axial distance calculation formula. In this process, the axial distance of each measurement point is obtained; and the reference contour direction of each measurement point in the first sampling interval is obtained according to the slope of the fitted curve contour; based on the reference contour direction and the axial distance, the normal distance of the first sampling interval can be calculated, as shown in Table 3, which is a schematic table of the axial normal slope of a measurement point in the first sampling interval provided by the embodiment of this application.

[0067] Table 3

[0068] Next, the maximum normal distance of the first sampling interval is selected based on the normal distances in Table 2. and minimum normal distance .

[0069] Then, the calculation steps for the first sampling interval are repeated to obtain the extreme values ​​of the normal distance for 131 sampling intervals, as shown in Table 4, which is a schematic table of the extreme values ​​of the normal distance for each sampling interval provided in the embodiments of this application.

[0070] Table 4

[0071] Next, the waviness peak and trough values ​​for the current measurement area can be obtained by calculating the peak and trough values ​​for all sampling intervals:

[0072]

[0073] Finally, the absolute value of the difference between the waviness peak value and the waviness trough value is the waviness of the current measurement area. :

[0074] like Figure 3 The diagram shown is a schematic representation of the normal distance and waviness provided in an embodiment of this application. It clearly shows the peak and trough values ​​of the waviness in the current measurement area. and ripple of the measurement area for The extreme values ​​of the normal distance for each sampling region are shown in Table 4.

[0075] Furthermore, to verify the effectiveness of this technical solution, an imported roughness profilometer was used to test the same sampling range. The data shows that the test results of the imported roughness profilometer are satisfactory. The detection of this technical solution The difference between the two is only The error is extremely small.

[0076] In summary, this application has the following advantages: (1) It replaced the traditional subjective qualitative judgment of “seeing and touching” and established quantifiable testing basis evaluation standards.

[0077] (2) Compared with the detection of microscopes and roughness testers, it has the advantages of wide detection range, strong applicability, high efficiency and high precision.

[0078] (3) The detection is carried out based on the preset scanning path, which avoids manual intervention and ensures the accuracy and reliability of the detection.

[0079] Based on the same inventive concept, embodiments of this application provide a structural component surface waviness detection device 40, such as... Figure 4 As shown, the structural component surface waviness detection device 40 includes: The area scanning unit 401 is used to scan the measurement area of ​​the structural component to be measured using a coordinate measuring machine according to a preset scanning path to obtain scanning data; wherein, the measurement area is a free-form surface; the scanning data contains the position information of each measurement point; The data comparison unit 402 is used to compare the scanned data with the theoretical model of the structure under test to obtain the normal distance of each measurement point; The waviness acquisition unit 403 is used to obtain the waviness of the measurement area based on the normal distance of each measurement point.

[0080] Optionally, the data comparison unit 402 is also used for: For any sampling interval, perform least-squares linear fitting on each measurement point within the sampling interval to obtain the fitting curve; For any measurement point within any sampling interval, the slope of the line profile of any measurement point in the fitted curve is taken as the reference profile vector direction of any measurement point. The distance between any measurement point and the fitted curve is taken as the axial distance of any measurement point; The normal distance of any measurement point is obtained based on the axial distance of any measurement point and the direction of the reference profile vector.

[0081] Optionally, the waviness obtaining unit 403 is also used for: For any sampling interval, the maximum and minimum normal distances of all measurement points in the sampling interval are taken as the peak and trough values ​​of the sampling interval. Based on the peak and trough values ​​of each sampling interval, the waviness peak and trough values ​​of the measurement area are obtained; The waviness of the measurement area is obtained by the absolute value of the difference between the peak value and the trough value of the waviness in the measurement area.

[0082] Optionally, the waviness obtaining unit 403 is also used for: For any given sampling interval, perform univariate linear regression on each measurement point within that interval to obtain a univariate linear regression model for that sampling interval. Based on the univariate linear regression model, the set of fitted theoretical contour heights corresponding to any sampling interval is obtained; Based on the actual contour height set and the fitted theoretical contour height set for any sampling interval, obtain the contour height difference set corresponding to any sampling interval; The ripple of any sampling interval is obtained by using the absolute value of the difference between the maximum and minimum profile height differences in the profile height difference set.

[0083] Optionally, the structural component surface waviness detection device 40 also includes a measurement preparation unit 404, used for: Adjust the orientation of the structural component under test and over-clamp the structural component under test; Establish the coordinate system of the structural component to be tested; Import the digital model file of the structural component to be tested into the measurement software of the measuring machine; the digital model file contains a preset scanning path.

[0084] Optionally, the structural component surface waviness detection device 40 further includes a scanning parameter setting unit 405, used for: The scanning parameters are set, including probe type, scanning mode, scanning increment, and sampling length.

[0085] The structural component surface waviness detection device 40 can be used to perform... Figure 2 The method performed by the structural component surface waviness detection device in the illustrated embodiment is described above. Therefore, the functions that each functional module of the structural component surface waviness detection device 40 can achieve can be found by referring to [the relevant documentation / reference]. Figure 2 The embodiments shown are described in detail below.

[0086] In some possible implementations, various aspects of the methods provided in this application can also be implemented as a program product comprising program code that, when run on a computer device, causes the computer device to perform the steps of the methods according to the various exemplary embodiments of this application described above. For example, the computer device may perform actions such as... Figure 2 The method performed by the structural component surface waviness detection device in the illustrated embodiment.

[0087] Those skilled in the art will understand that all or part of the steps of the above method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps of the above method embodiments. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks. Alternatively, if the integrated units of this application are implemented as software functional modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of the embodiments of this application, or the parts that contribute to the prior art, can be embodied in the form of software products. These computer software products are stored in a storage medium and include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as mobile storage devices, ROM, RAM, magnetic disks, or optical disks.

[0088] Although preferred embodiments of this application have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of this application.

[0089] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A method for detecting the waviness of curved surfaces of structural components, characterized in that, The method includes: A coordinate measuring machine is used to scan the measurement area of ​​the structural component under test according to a preset scanning path to obtain scanning data; wherein, the measurement area is a freeform surface; the scanning data contains the position information of each measurement point; The scanned data is compared with the theoretical model of the structure under test to obtain the normal distance of each measurement point; The waviness of the measurement area is obtained based on the normal distance of each measurement point.

2. The method as described in claim 1, characterized in that, The step of comparing the scanned data with the theoretical model of the structure under test to obtain the normal distance of each measurement point includes: For any sampling interval, least squares linear fitting is performed on each measurement point within the sampling interval to obtain the fitting curve; For any measurement point within any sampling interval, the slope of the line profile of any measurement point in the fitted curve is taken as the reference profile vector direction of the measurement point. The distance between any measurement point and the fitted curve is taken as the axial distance of any measurement point; The normal distance of any measurement point is obtained based on the axial distance of any measurement point and the direction of the reference profile vector.

3. The method as described in claim 1, characterized in that, The step of obtaining the waviness of the measurement area based on the normal distance of each measurement point includes: For any sampling interval, the maximum normal distance and the minimum normal distance of all measurement points in the sampling interval are taken as the peak and trough values ​​of the sampling interval. The waviness peak and valley values ​​of the measurement area are obtained based on the peak and valley values ​​of each sampling interval. The waviness of the measurement area is obtained by the absolute value of the difference between the peak value and the trough value of the waviness of the measurement area.

4. The method as described in claim 1, characterized in that, After scanning the measurement area of ​​the structural component under test using a coordinate measuring machine to obtain the scan data, the method further includes: For any given sampling interval, perform univariate linear regression on each measurement point in the given sampling interval to obtain a univariate linear regression model for the given sampling interval. Based on the univariate linear regression model, obtain the set of fitted theoretical contour heights corresponding to any sampling interval; Based on the actual contour height set of any sampling interval and the fitted theoretical contour height set, obtain the contour height difference set corresponding to any sampling interval; The ripple degree of any sampling interval is obtained by using the absolute value of the difference between the maximum and minimum profile height differences in the set of profile height differences.

5. The method as described in claim 1, characterized in that, Before using a coordinate measuring machine to scan the measurement area of ​​the structural component under test according to a preset scanning path to obtain scan data, the method further includes: Adjust the orientation of the structure under test and over-clamp the structure under test; Establish the coordinate system of the structural component to be tested; Import the digital model file of the structural component to be tested into the measurement software of the measuring machine; wherein the digital model file contains a preset scanning path.

6. The method as described in claim 1, characterized in that, Before using a coordinate measuring machine to scan the measurement area of ​​the structural component under test according to a preset scanning path to obtain scan data, the method further includes: The scanning parameters are set, including probe type, scanning mode, scanning increment, and sampling length.

7. The method as described in claim 6, characterized in that, The probe type is a Φ1mm spherical probe, the scanning method is an open-line scanning method, the scanning increment is in the range of 0.06mm to 0.12mm, and the sampling length is 6mm.

8. A device for detecting the waviness of curved surfaces of structural components, characterized in that, The device includes: The area scanning unit is used to scan the measurement area of ​​the structural component under test using a coordinate measuring machine according to a preset scanning path to obtain scanning data; wherein, the measurement area is a freeform surface; the scanning data includes the position information of each measurement point; The data comparison unit is used to compare the scanned data with the theoretical model of the structure under test to obtain the normal distance of each measurement point; The waviness acquisition unit is used to obtain the waviness of the measurement area based on the normal distance of each measurement point.

9. An electronic device, characterized in that, The device includes: Memory, used to store program instructions; A processor is configured to invoke program instructions stored in the memory and execute the method described in any one of claims 1-7 according to the obtained program instructions.

10. A storage medium, characterized in that, The storage medium stores computer-executable instructions for causing a computer to perform the method described in any one of claims 1-7.

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