Flatness measurement method and device, equipment and storage medium

Abstract

The invention is suitable for the technical field of measurement, and provides a flatness measurement method, device and equipment and a storage medium, and the method comprises the steps: scanning the surface of a to-be-measured target through line laser according to a preset scanning track, obtaining the scanning data of the to-be-measured target, and enabling the scanning data to comprise brightness data and point cloud data; determining point location information of the to-be-measured target according to the brightness data, wherein the point location information of the to-be-measured target is used for determining a target positioning area of the to-be-measured target; filtering the point cloud data to obtain target point cloud data; generating height data of the to-be-measured target according to the target positioning area and the target point cloud data; generating a fitting reference plane according to the height data; and calculating the flatness of the to-be-measured target according to the fitting reference plane. According to the scheme, high-precision and high-efficiency flatness measurement can be realized.

Description

Technical Field

[0001] The present application relates to the field of measurement technology, and in particular to a flatness measurement method, device, equipment and storage medium. Background Art

[0002] In the field of precision structure measurement, flatness measurement can be used to evaluate the flatness and quality of parts or structures, ensure that the flatness of parts meets design requirements, and improve product accuracy and quality.

[0003] Flatness refers to the degree of deviation of a plane from its ideal position, and is used to describe the flatness and quality of a plane surface. Flatness measurement refers to the process of measuring and evaluating the flatness of a plane surface. Flatness measurement is usually performed by scanning or measuring the plane surface using a measuring instrument (such as a flatness meter, laser measuring instrument, etc.), and then comparing the actual measurement result with the ideal plane to calculate the deviation value of the flatness.

[0004] In related schemes, flatness measurement mainly relies on physical contact methods, such as using tools such as discs and gauges to directly measure the surface of the object being measured. This method has low measurement efficiency and its accuracy is limited by the accuracy of the measuring tool and the skills of the operator. With the development of optical technology, non-contact optical measurement methods have begun to be applied to flatness measurement, such as laser scanning, optical comparators, etc. This method still has problems in measuring the flatness of precision structures. Summary of the invention

[0005] The embodiments of the present application provide a flatness measurement method, device, equipment and storage medium, which can solve the technical problem of how to achieve high-precision and high-efficiency flatness measurement.

[0006] In a first aspect, an embodiment of the present application provides a flatness measurement method, comprising:

[0007] The surface of the target to be measured is scanned by a line laser according to a preset scanning trajectory to obtain scanning data of the target to be measured, and the scanning data includes brightness data and point cloud data.

[0008] The point information of the target to be measured is determined according to the brightness data, and the point information of the target to be measured is used to determine the target positioning area of ​​the target to be measured.

[0009] The point cloud data is filtered to obtain the target point cloud data.

[0010] Generate the height data of the target to be measured based on the target positioning area and the target point cloud data.

[0011] Generates a fitted datum plane based on height data.

[0012] Calculate the flatness of the object to be measured based on the fitted reference plane.

[0013] In one implementation, determining the position information of the target to be measured according to the brightness data includes:

[0014] A corresponding brightness map is generated according to the brightness data and a brightness value interval of the brightness map is determined.

[0015] The brightness image is binarized within the brightness value interval to generate a target brightness value interval.

[0016] The target brightness value interval is processed by morphological opening operation to obtain the target brightness map.

[0017] Determine the point information of the target to be measured based on the target brightness map.

[0018] In one implementation, filtering is performed on the point cloud data to obtain target point cloud data, including:

[0019] The vertical distance between the point in the point cloud data and the preset reference plane is calculated to obtain the vertical distance between the point in the point cloud data.

[0020] Calculates the height ratio of points in the point cloud data based on their vertical distance.

[0021] Delete points in the point cloud data whose height ratio is greater than the preset height ratio threshold.

[0022] In one implementation, filtering the point cloud data to obtain target point cloud data further includes:

[0023] The corresponding shape area is segmented according to the point cloud data.

[0024] Calculates the area of ​​a shape.

[0025] Delete the shape area whose area is smaller than the preset area threshold.

[0026] In one implementation, generating a fitting reference plane according to height data includes:

[0027] The height data is sorted to obtain sorted height data.

[0028] The sorted height data is screened according to a preset interval to obtain screened height data.

[0029] Generates a fitted datum plane based on the filtered height data.

[0030] In one implementation, the installation angle of the line laser is inclined at 13 to 14 degrees relative to the X-axis.

[0031] In a second aspect, an embodiment of the present application provides a flatness measuring device, which has the function of implementing the method in the first aspect or any possible implementation thereof. Specifically, the device includes a unit for implementing the method in the first aspect or any possible implementation thereof.

[0032] In one embodiment, the device comprises:

[0033] The acquisition unit is used to scan the surface of the target to be measured using a line laser according to a preset scanning trajectory to obtain scanning data of the target to be measured, and the scanning data includes brightness data and point cloud data.

[0034] The processing unit is used to determine the point information of the target to be measured according to the brightness data, and the point information of the target to be measured is used to determine the target positioning area of ​​the target to be measured.

[0035] The processing unit is also used to filter the point cloud data to obtain target point cloud data.

[0036] The processing unit is also used to generate height data of the target to be measured according to the target positioning area and the target point cloud data.

[0037] The processing unit is also used to generate a fitting reference plane according to the height data, and the fitting reference plane is used to calculate the flatness of the target to be measured.

[0038] The processing unit is also used to calculate the flatness of the target to be measured according to the fitted reference plane.

[0039] In a third aspect, an embodiment of the present application provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the computer device implements a method according to any one of the implementation modes of the first aspect.

[0040] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a computer device, the computer device implements the method of any one of the implementation methods of the first aspect above.

[0041] In a fifth aspect, an embodiment of the present application provides a computer program product. When the computer program product is run on a computer device, the computer device executes a method of any one of the implementation modes of the first aspect above.

[0042] Compared with the prior art, the embodiments of the present application have the following beneficial effects: the laser scanning process is made more time-saving by presetting the scanning trajectory; the point information of the target to be measured can be accurately located by brightness data, providing accurate positioning information for subsequent data processing; noise and abnormal points can be removed by filtering processing, and the quality and reliability of point cloud data can be improved, making subsequent data processing more accurate and reliable; the height data generated according to the target positioning area and the target point cloud data can provide more accurate height information, providing a reliable data basis for subsequent flatness calculation; an accurate reference plane can be provided by fitting the reference plane, thereby calculating more accurate flatness, and realizing high-precision, high-efficiency, high-stability and high-automation flatness measurement. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 It is a schematic diagram of a flatness measurement scenario provided in an embodiment of the present application.

[0044] Figure 2 It is a flow chart of a flatness measurement method provided in an embodiment of the present application.

[0045] Figure 3 It is a schematic diagram of a preset scanning trajectory provided in an embodiment of the present application.

[0046] Figure 4 This is a schematic diagram of the installation of a line laser sensor provided in an embodiment of the present application.

[0047] Figure 5 This is a hardware architecture diagram for flatness measurement provided in an embodiment of the present application.

[0048] Figure 6 It is a flow chart of a flatness measurement method provided in an embodiment of the present application.

[0049] Figure 7 This is a brightness diagram of a rotating boss column provided in an embodiment of the present application.

[0050] Figure 8 This is a positioning diagram of a rotating shaft boss column provided in an embodiment of the present application.

[0051] Fig. 9 It is a structural schematic diagram of a flatness measurement device provided in an embodiment of the present application.

[0052] Fig.10 It is a schematic diagram of the structure of a computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0053] Flatness measurement technology is a key link in precision engineering and manufacturing. It involves how to accurately measure and evaluate the flatness of an object's surface. Flatness refers to the maximum distance between all points on the surface of an object and a specified reference plane under specified conditions. It is an important parameter for measuring the flatness of an object's surface. It is of great significance to ensure product quality, improve assembly accuracy, and optimize design. Figure 1 Let me introduce it in detail.

[0054] Figure 1 It is a schematic diagram of a flatness measurement scenario provided in an embodiment of the present application.

[0055] like Figure 1 As shown, Figure 1 The surface of the target to be measured is uneven. The flatness of the target to be measured can be obtained by calculating the height difference between the points of each concave and convex surface and the reference plane.

[0056] Traditional flatness measurement methods are limited by the accuracy of measuring instruments, resulting in inaccurate measurement results; or they require manual operation of measuring instruments for measurement, which is time-consuming, labor-intensive, and inefficient. They may also be affected by environmental factors such as temperature and humidity, which can affect the measurement results.

[0057] In view of the above problems, the present application proposes a flatness measurement method, which can perform flatness measurement with high precision and high efficiency.

[0058] Combine the following Figure 2 Let me introduce it in detail.

[0059] Figure 2 It is a flow chart of a flatness measurement method provided in an embodiment of the present application.

[0060] like Figure 2 As shown, Figure 2 The process includes the following steps S201 to S206.

[0061] S201 , using a line laser to scan the surface of the target to be measured according to a preset scanning trajectory to obtain scanning data of the target to be measured.

[0062] The scanning data includes brightness data and point cloud data.

[0063] Line laser can be understood as a laser beam. The target to be measured is placed on the measuring platform, and then the surface of the target to be measured is scanned by the laser beam. After reflection, it is received by the receiver. The receiver converts the collected laser data into brightness data and point cloud data.

[0064] Brightness data can be understood as the laser beam irradiating the surface of the target to be measured during the laser scanning process. After being reflected, it is received by the receiver. The receiver will record the brightness value of the laser beam at different positions, that is, brightness data. Brightness data can reflect the brightness distribution of the surface of the target to be measured.

[0065] Point cloud data can be understood as a dot matrix formed by the laser beam on the surface of the target to be measured during laser scanning. Each dot represents the position of a measurement point, and the coordinate information of the points collected finally constitutes the point cloud data. Point cloud data can be used to reconstruct the three-dimensional model of the target surface to achieve accurate measurement of the target surface.

[0066] The preset scanning trajectory refers to the moving trajectory of the line laser when scanning the target to be measured. Figure 3 Let me introduce it in detail.

[0067] Figure 3 It is a schematic diagram of a preset scanning trajectory provided in an embodiment of the present application.

[0068] like Figure 3 As shown, when the line laser moves from point A (starting scanning position) to point B (ending scanning position) and completes scanning of a target to be measured, there is no need to wait for the data processing process of the scanned data obtained by scanning. The line laser can move directly along the line segment BC to point C (i.e., the starting scanning position of the next target to be measured) to scan the next target to be measured.

[0069] This scanning trajectory design significantly saves the overall measurement time and makes the laser scanning process more efficient. In this way, laser scanning can maximize production throughput while ensuring measurement accuracy.

[0070] S202: Determine the point information of the target to be measured according to the brightness data.

[0071] The point information of the target to be measured is used to determine the target positioning area of ​​the target to be measured.

[0072] Point information is the information about the position or characteristics of a point in a specific coordinate system, and can also be understood as the coordinate information of a point on the surface of the target to be measured, such as the (x, y, z) coordinates in three-dimensional space, or the (x, y) coordinates on a two-dimensional plane. The specific point information varies according to the actual situation and is not limited here.

[0073] It can be understood that all brightness data of the target to be measured can form a brightness map, and the brightness map of the target to be measured is processed to distinguish the target positioning area of ​​the target to be measured according to the point information. For example, the outline of the target positioning area can be found in the brightness map according to certain points, so as to obtain the boundary information of the target positioning area.

[0074] By determining the target point information through brightness data, automatic positioning of the target to be measured is achieved without human intervention, which improves the accuracy of positioning. In addition, this method is applicable to targets of various shapes and sizes and only needs to be processed according to the brightness characteristics, which is highly flexible.

[0075] S203: Filter the point cloud data to obtain target point cloud data.

[0076] In point cloud data processing, filtering is usually used to remove noise, smooth point clouds, extract targets, and other operations to obtain clear and accurate target point cloud data. For example, common filtering methods include distance ratio method, area threshold method, and so on.

[0077] Filtering processing can effectively remove noise from point cloud data and improve data quality.

[0078] S204: Generate height data of the target to be measured according to the target positioning area and the target point cloud data.

[0079] It can be understood that the target positioning area is divided into effective positioning areas. Therefore, the target point cloud data within the scope of the target positioning area can be used as a data source to obtain the height data of each point.

[0080] By limiting the scope of the target positioning area, it can be ensured that only the target-related part of the target point cloud data is used to generate height data, avoiding interference from other irrelevant data and improving the accuracy of the height data; only the point cloud data within the target positioning area is processed, avoiding calculation of the entire point cloud data set, reducing the amount of calculation and improving calculation efficiency.

[0081] S205: Generate a fitting reference plane according to the height data.

[0082] The fitting reference plane can be understood as a reference plane, that is, a reference plane used to evaluate the flatness of the surface of the target to be measured. By comparing with the reference plane, the flatness of the surface of the target to be measured can be determined.

[0083] By measuring the distances from different points on the surface of the target to be measured to the reference plane, the flatness of the surface of the target to be measured can be determined. If the distances from the points on the surface of the target to be measured to the reference plane are close, it indicates that the flatness of the surface of the target to be measured is high; conversely, if there is a large difference in distance, it indicates that the flatness of the surface of the target to be measured is poor.

[0084] According to the height data, a certain number of points are selected as the data points of the fitting reference plane. The least squares method or other fitting algorithms are used to perform plane fitting on the selected data points to obtain the fitted reference plane equation. According to the plane equation, the normal vector of the plane and a point on the plane are calculated for subsequent calculations.

[0085] As an example but not limitation, assume there is a set of height data, select several points from them as data points for fitting the reference plane, and use the least squares method to fit the plane, and get the plane equation: z = ax + by + c, where a and b are the normal vectors of the plane, and c is the height of a point on the plane.

[0086] By fitting the reference plane, the overall shape and flatness of the target to be measured can be described more accurately.

[0087] S206: Calculate the flatness of the target to be measured according to the fitted reference plane.

[0088] According to the equation of the fitted reference plane and the height data of the target to be measured, the height difference from each point on the target to be measured to the fitted reference plane is calculated. According to the height difference data, the flatness of the target to be measured is calculated, such as the average height difference, the maximum height difference, etc.

[0089] As an example but not limitation, assume that the height data of the target to be measured and the equation of the fitted reference plane are calculated, the height difference from each point on the target to be measured to the fitted reference plane is calculated, and then the maximum height difference is calculated as the flatness of the target to be measured.

[0090] By generating a fitted reference plane and calculating the flatness of the target to be measured, the flatness of the target to be measured can be accurately and objectively evaluated.

[0091] The design of preset scanning trajectory significantly saves the overall laser scanning time, making the laser scanning process more efficient; the brightness data can accurately locate the point information of the target to be measured, providing accurate positioning information for subsequent data processing; the filtering process can remove noise and abnormal points, improve the quality and reliability of point cloud data, and make subsequent data processing more accurate and reliable; the height data generated according to the target positioning area and the target point cloud data can provide more accurate height information, providing a reliable data basis for subsequent flatness calculation; the fitting reference plane can provide an accurate reference plane, so as to calculate more accurate flatness, realize high-precision, high-efficiency, high-stability and high-automation flatness measurement, and meet the high requirements of modern precision manufacturing industry for flatness measurement technology.

[0092] In one implementation, the point information of the target to be measured is determined according to the brightness data, including: generating a corresponding brightness map according to the brightness data and determining the brightness value range of the brightness map; binarizing the brightness map within the brightness value range to generate a target brightness value range; performing morphological opening operation on the target brightness value range to obtain a target brightness map; and determining the point information of the target to be measured according to the target brightness map.

[0093] According to the collected brightness data, it is converted into a corresponding brightness image. Then, according to the pixel value range in the brightness image, the brightness value interval is determined, that is, the minimum and maximum values ​​of the brightness are determined.

[0094] Binarization is to convert an image into a black-and-white image containing only two values ​​(eg, 0 and 255). As an example but not a limitation, after the image is binarized, only the brightest 30% area is retained.

[0095] Morphological opening is an image processing operation in mathematical morphology, which is usually used to remove noise, smooth images, separate objects, etc. Opening is a combination of performing an erosion operation on an image and then performing a dilation operation on the result. The erosion operation is used to reduce the boundary of an object, and the dilation operation is used to expand the boundary of an object. By performing a morphological opening operation, the edge features in the image can be eliminated, making the image smoother and more continuous.

[0096] The processed target brightness image can be used to determine the target's outline and position information, thereby obtaining the point information of the target to be measured, that is, the position and shape of the target in the image.

[0097] The following is a detailed introduction with an example.

[0098] As an example but not a limitation, assume that there are two cylindrical targets to be measured. The common feature of these two cylindrical targets to be measured is that they have circular features and relatively high brightness in the brightness map. The difference is that the first type of cylindrical target to be measured has larger, higher-brightness solid rectangular support areas on both sides, while the second type of cylindrical target to be measured does not have the aforementioned solid rectangular support areas on both sides.

[0099] After the above steps are processed, the target brightness map is obtained. At this time, check whether there are any other brightness areas in the target brightness map except the brightness area of ​​the cylindrical target itself. If there are any areas, it can be determined that the first cylindrical target is currently being detected; if there are no areas, it means that the second cylindrical target is currently being detected. It can be understood that according to the judgment results, different image enhancement and denoising processes are performed on the two cylindrical targets to be tested, and finally the corresponding position information is accurately located and returned as a point set area.

[0100] Through the above steps, different targets to be measured can be effectively distinguished and located, providing accurate position information for subsequent processing.

[0101] In one implementation, point cloud data is filtered to obtain target point cloud data, including: calculating the vertical distance between points in the point cloud data and a preset reference plane to obtain the vertical distance of the points in the point cloud data; calculating the height ratio of the points in the point cloud data based on the vertical distance of the points in the point cloud data; and deleting points in the point cloud data whose height ratio is greater than a preset height ratio threshold.

[0102] By calculating the vertical distance from each point in the point cloud to the preset reference plane, the maximum height value among all points is found. Then, the ratio of the height of each point to the maximum height is calculated to obtain the height ratio corresponding to the point. If the height ratio of a point exceeds the preset height ratio threshold, it means that the point is too prominent relative to most points, that is, it is identified as noise or outlier and is removed. This method is conducive to removing points that are significantly higher or lower than most data.

[0103] In one implementation, filtering is performed on the point cloud data to obtain target point cloud data, and the process also includes: segmenting corresponding shape regions according to the point cloud data; calculating the area of ​​the shape regions; and deleting shape regions whose areas are smaller than a preset area threshold.

[0104] First, point cloud segmentation technology is used to identify the various shape regions in the point cloud data. For each identified shape region, its area is calculated and compared with the preset area threshold. If the area of ​​a region is smaller than the threshold, it usually means that the region is composed of scattered noise points, so it should be removed from the data. This method effectively identifies and removes areas composed of a small number of points that do not represent the actual surface of the object, thereby cleaning up the noise in the data.

[0105] Through the above two methods, the quality of point cloud data can be effectively improved, laying a solid foundation for subsequent point cloud processing and analysis.

[0106] In one implementation, generating a fitting reference plane based on height data includes: sorting the height data to obtain sorted height data; filtering the sorted height data according to a preset interval to obtain filtered height data; and generating a fitting reference plane based on the filtered height data.

[0107] Combined with the above, according to the target positioning area, the height information of each point is extracted from the point cloud data, that is, the height data. The height data is sorted to obtain the height data sorted from high to low or from low to high, that is, the sorted height data.

[0108] Then select the data in the middle 80% (preset interval) of the sorted data to obtain the screening height data. This can eliminate the interference of extreme values ​​and more accurately reflect the general situation of the target surface to be measured. Calculate the average value of the screening height data to obtain the average height of the target surface to be measured.

[0109] Finally, an optimal plane is fitted based on the filtered height data (which can also be understood as the filtered point cloud data), and this plane is used as the reference plane for evaluating flatness.

[0110] The array measurement mode is adopted to achieve batch measurement, which greatly reduces the time of loading and unloading and improves the measurement efficiency. By optimizing the moving trajectory of the equipment and processing the algorithm during the idle time of movement, the overall running time is reduced and the efficiency of the measurement process is improved.

[0111] In one implementation, the installation angle of the line laser is inclined at 13 to 14 degrees relative to the X-axis.

[0112] Combine the following Figure 4 Let me introduce it in detail.

[0113] Figure 4 This is a schematic diagram of the installation of a line laser sensor provided in an embodiment of the present application.

[0114] like Figure 4 As shown, in an XYZ axis space, the line laser sensor moves along the scanning direction, wherein the installation angle of the line laser sensor intersects with the X axis, and the inclination angle is 13 to 14 degrees.

[0115] It is understandable that since the precision structure presents a mirror effect after polishing, the horizontal installation has a poor scanning effect on the target to be measured on the mirror surface, and it is easy to measure a lot of invalid data. By tilting the laser sensor at an angle of 13-14 degrees, the problem of missing points caused by the reflection of the mirror sample is effectively solved, and the accuracy of the measurement is improved.

[0116] Combine the following Figure 5 Let's introduce the hardware architecture involved in the flatness measurement method mentioned above.

[0117] Figure 5 This is a hardware architecture diagram for flatness measurement provided in an embodiment of the present application.

[0118] like Figure 5 As shown, Figure 5 It includes sensors, line laser drivers, industrial computers, software control systems, splitters, motion controllers, X-axis drivers, Y-axis drivers, Z-axis drivers and servo motors corresponding to each axis driver.

[0119] As the mobile basis of the measurement system, the XYZ three-axis motion platform can accurately control the position of the laser scanning head to achieve full coverage measurement of the target surface to be measured.

[0120] Line laser is the core measurement tool of this application. It projects a laser line on the surface of the target to be measured, captures the deformation of the laser line on the surface of the target to be measured, and is used to calculate the flatness.

[0121] The industrial computer is the control center, responsible for processing the data from the line laser and motion platform, executing the image processing steps mentioned above, and finally outputting the measurement results.

[0122] Since the line laser data collection needs to be triggered by the X-axis encoder, a splitter is added in this application to transmit the feedback signal of the X-axis driver to the line laser driver and motion controller respectively, ensuring the synchronization and accuracy of data collection.

[0123] The industrial computer and the laser driver communicate via the Transmission Control Protocol (TCP) to obtain image data and point cloud data, and the industrial computer and the motion controller communicate via the Universal Serial Bus (USB) to obtain position data and issue instructions.

[0124] The software control system is used to implement the flatness measurement method mentioned above.

[0125] Combine the following Figure 6 To comprehensively introduce the flatness measurement method mentioned above.

[0126] Figure 6 It is a flow chart of a flatness measurement method provided in an embodiment of the present application.

[0127] like Figure 6 As shown, Figure 6 The process includes the following steps S601 to S608.

[0128] S601, start XY axis movement, and the encoder triggers laser scanning.

[0129] The line laser is triggered by the precise movement of the mechanical device to start scanning the target surface to collect brightness map and point cloud data.

[0130] S602: Obtain a brightness image of the laser.

[0131] S603: Automatically locate the point of the object according to the input target region (Region of Interest, ROI).

[0132] Using the collected brightness map, the system automatically locates the measurement point of the target to be measured.

[0133] S604: Obtain laser point cloud data.

[0134] S605: filtering the point cloud to remove abnormal points and outliers.

[0135] The collected point cloud data is filtered to remove noise and outliers to improve data quality.

[0136] S606 , the areas located according to the brightness map are mapped one by one to the point cloud to obtain height data.

[0137] According to the positioning results on the brightness map, the two-dimensional image points are mapped to the corresponding three-dimensional points in the point cloud data.

[0138] S607, sorting the acquired height data, selecting the middle 80% of the data and calculating the average value, eliminating the interference of extreme values.

[0139] S608 , fitting an optimal plane based on the filtered data, calculating the vertical distance from each point in the point cloud to the fitting plane, and taking the maximum value of these distances as the flatness of the target to be measured.

[0140] By comprehensively applying line laser technology, motion control technology, image processing algorithms and array measurement mode, an efficient and accurate method for measuring the flatness of precision structures has been realized. This method can not only provide high-precision measurement results, but also adapt to objects of different shapes and materials. By optimizing each link in the measurement process, the problems of low efficiency and low accuracy in traditional flatness measurement methods are solved, providing a reliable technical means for quality control of precision structures.

[0141] Combine the following Figure 7 and Figure 8 Let's introduce how to apply the flatness measurement method mentioned above.

[0142] Figure 7 This is a brightness diagram of a rotating boss column provided in an embodiment of the present application.

[0143] Figure 8 This is a positioning diagram of a rotating shaft boss column provided in an embodiment of the present application.

[0144] Assume that, taking the flatness inspection of the boss column of the rotating shaft structure surface as an example, two points are taken on each boss column to calculate the flatness. A fixture is used to place 15 points, and 5 points are measured at the same time.

[0145] Place the target to be measured in the fixture and place it on the scanning plane. The editing and running process is shown in Table 1 below.

[0146] Table 1

[0147] Serial number step Input Data 1 Array Enter the number of rows 15, the number of columns 1, the horizontal spacing, and the vertical spacing 2 Laser Scanning Enter scanning path, scanning height, laser configuration 3 Filtering 4 Positioning 1 Input position 1ROI 5 Positioning 2 Input position 2ROI ... ... ... 21 Flatness calculation Dependency positioning 1, 2...

[0148] In one example, the average measurement time for a target is 1s, the static repeatability is 1um, and the dynamic repeatability is within 5um. The brightness graph obtained after measurement is as follows: Figure 7 As shown in the figure, the obtained positioning map is Figure 8 shown. Figure 8 The yellow area in the middle indicates the corresponding point information.

[0149] The method of using laser scanning to generate brightness maps and point cloud data can automatically identify and locate irregular structures, avoid point offset problems during the measurement process, filter the collected point cloud data, remove abnormal points, reduce interference that may be introduced by the environment and the equipment itself, and improve data accuracy and reliability.

[0150] The above mainly introduces the method of the embodiment of the present application in conjunction with the accompanying drawings. It should be understood that although the various steps in the flowcharts involved in the embodiments described above are shown in sequence, these steps are not necessarily performed in sequence in the order shown in the figure. Unless there is a clear description in this article, the execution of these steps is not strictly limited in order, and these steps can be performed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the embodiments described above may include multiple steps or multiple stages, and these steps or stages are not necessarily performed at the same time, but can be performed at different times, and the execution order of these steps or stages is not necessarily performed in sequence, but can be performed in turn or alternately with other steps or at least a part of the steps or stages in other steps. A device of an embodiment of the present application is introduced below in conjunction with the accompanying drawings. For simplicity, when introducing the device below, it will be appropriately omitted, and the relevant content can refer to the relevant description in the method above, and will not be repeated.

[0151] Fig. 9 A schematic structural diagram of a flatness measuring device provided in an embodiment of the application.

[0152] like Fig. 9 As shown, the device 1000 includes the following units.

[0153] The acquisition unit 1001 is used to scan the surface of the target to be measured by using a line laser according to a preset scanning trajectory to obtain scanning data of the target to be measured, and the scanning data includes brightness data and point cloud data.

[0154] The processing unit 1002 is used to determine the point information of the target to be measured according to the brightness data, and the point information of the target to be measured is used to determine the target positioning area of ​​the target to be measured.

[0155] The processing unit 1002 is further used to perform filtering processing on the point cloud data to obtain target point cloud data.

[0156] The processing unit 1002 is further configured to generate height data of the target to be measured according to the target positioning area and the target point cloud data.

[0157] The processing unit 1002 is further configured to generate a fitting reference plane according to the height data.

[0158] The processing unit 1002 is further configured to calculate the flatness of the target to be measured according to the fitted reference plane.

[0159] In one implementation, the processing unit 1002 is also used to generate a corresponding brightness map based on the brightness data and determine the brightness value range of the brightness map; perform binarization processing on the brightness map within the brightness value range to generate a target brightness value range; perform morphological opening operation on the target brightness value range to obtain a target brightness map; and determine the point information of the target to be measured based on the target brightness map.

[0160] In one implementation, the device 1000 further includes a storage unit 1003, which can be used to store instructions and / or data, so as to implement the method in the above embodiment.

[0161] It should be noted that the information interaction, execution process and other contents between the above-mentioned units are based on the same concept as the method embodiment of the present application. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0162] Fig.10 Schematic diagram of the structure of the computer device provided in the embodiment of the present application. Fig.10 As shown, the computer device 3000 of this embodiment includes: at least one processor 3100 ( Fig.10 Only one) processor, memory 3200, and a computer program 3210 stored in the memory 3200 and executable on at least one processor 3100 are shown. When the processor 3100 executes the computer program 3210, the computer device implements the steps in the above embodiments.

[0163] The processor 3100 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc.

[0164] The memory 3200 may be an internal storage unit of the computer device 3000 in some embodiments, such as a hard disk or memory of the computer device 3000. The memory 3200 may also be an external storage device of the computer device 3000 in other embodiments, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (Flash Card), etc. equipped on the computer device 3000. Further, the memory 3200 may also include both an internal storage unit of the computer device 3000 and an external storage device. The memory 3200 is used to store an operating system, an application program, a boot loader (Boot Loader) data, and other programs, such as a program code of a computer program, etc. The memory 3200 may also be used to temporarily store data that has been output or is to be output.

[0165] Those skilled in the art can clearly understand that, for the convenience and simplicity of description, only the division of the above-mentioned functional units is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units in the embodiment can be integrated into a processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0166] The embodiment of the present application further provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a computer device, the computer device can implement the steps in the above-mentioned method embodiments.

[0167] The embodiment of the present application provides a computer program product. When the computer program product is executed on a computer device, the computer device can implement the above-mentioned methods.

[0168] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the processes in the above-mentioned embodiment method, which can be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by the processor, the computer device can implement the steps of the above-mentioned various method embodiments. Among them, the computer program includes computer program code, and the computer program code can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may at least include: any entity or device that can carry the computer program code to the camera / terminal device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electric carrier signal, a telecommunication signal, and a software distribution medium. For example, a USB flash drive, a mobile hard disk, a magnetic disk or an optical disk. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electric carrier signals and telecommunication signals.

[0169] It should be understood that the size of the sequence number of each step in the above-described embodiment does not mean the order of execution, and the order of execution of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiment of the present application. In the description, for the purpose of explanation rather than for limitation, specific details such as specific system structure, technology and the like are proposed, so as to thoroughly understand the embodiment of the present application. However, it should be clear to those skilled in the art that the present application can also be implemented in other embodiments without these specific details. In other cases, the detailed description of well-known systems, devices, circuits and methods is omitted to prevent unnecessary details from hindering the description of the present application.

[0170] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, wholes, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or combinations thereof.

[0171] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0172] Additionally, in the specification of the present application and the description of the appended claims, the terms “include,” “comprise,” “have,” and their variations all mean “including but not limited to,” unless otherwise specifically emphasized.

[0173] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0174] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0175] In the embodiments provided in the present application, it should be understood that the disclosed devices, computer equipment and methods can be implemented in other ways. For example, the device and computer equipment embodiments described above are only schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0176] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A flatness measurement method, characterized in that: include: Scanning the surface of the target to be measured by using a line laser according to a preset scanning trajectory to obtain scanning data of the target to be measured, wherein the scanning data includes brightness data and point cloud data; Determining the point information of the target to be measured according to the brightness data, wherein the point information of the target to be measured is used to determine the target positioning area of ​​the target to be measured; Performing filtering processing on the point cloud data to obtain target point cloud data; Generate height data of the target to be measured according to the target positioning area and the target point cloud data; generating a fitting reference plane according to the height data; The flatness of the object to be measured is calculated according to the fitted reference plane.

2. The method according to claim 1, characterized in that Determining the point information of the target to be measured according to the brightness data includes: Generate a corresponding brightness map according to the brightness data and determine a brightness value interval of the brightness map; Binarizing the brightness map within the brightness value interval to generate a target brightness value interval; Performing morphological opening operation on the target brightness value interval to obtain a target brightness map; The point information of the target to be measured is determined according to the target brightness map.

3. The method according to claim 1, characterized in that: The filtering process of the point cloud data to obtain target point cloud data includes: Calculating the vertical distance between the point in the point cloud data and a preset reference plane to obtain the vertical distance between the point in the point cloud data; Calculating the height ratio of the points in the point cloud data according to the vertical distance of the points in the point cloud data; The points corresponding to the height ratios greater than a preset height ratio threshold are deleted from the point cloud data.

4. The method according to claim 3, characterized in that The filtering process of the point cloud data to obtain target point cloud data also includes: Segmenting a corresponding shape area according to the point cloud data; Calculate the area of ​​the shape region; The shape regions whose areas are smaller than a preset area threshold are deleted.

5. The method according to claim 4, characterized in that Generating a fitting reference plane according to the height data comprises: Sorting the height data to obtain sorted height data; Screening the sorted height data according to a preset interval to obtain screened height data; The fitting reference plane is generated according to the screening height data.

6. The method according to any one of claims 1 to 5, characterized in that The installation angle of the line laser is inclined at 13 to 14 degrees relative to the X-axis.

7. A flatness measuring device, characterized in that: include: An acquisition unit, used to scan the surface of the target to be measured using a line laser according to a preset scanning trajectory to obtain scanning data of the target to be measured, wherein the scanning data includes brightness data and point cloud data; A processing unit, used to determine the point information of the target to be measured according to the brightness data, wherein the point information of the target to be measured is used to determine the target positioning area of ​​the target to be measured; The processing unit is further used to filter the point cloud data to obtain target point cloud data; The processing unit is further used to generate height data of the target to be measured according to the target positioning area and the target point cloud data; The processing unit is further used to generate a fitting reference plane according to the height data; The processing unit is further configured to calculate the flatness of the target to be measured according to the fitted reference plane.

8. The device according to claim 7, characterized in that The processing unit is further configured to generate a corresponding brightness map according to the brightness data and determine a brightness value interval of the brightness map; Binarizing the brightness map within the brightness value interval to generate a target brightness value interval; A morphological opening operation is performed on the target brightness value interval to obtain a target brightness map; and the point information of the target to be measured is determined according to the target brightness map.

9. A computer device, characterized in that: The computer device comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the computer device implements the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a computer device, the method according to any one of claims 1 to 7 is implemented.

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