Honeycomb core component processing surface shape precision measuring method and system

Abstract

The invention discloses a honeycomb core component processing surface shape precision measurement method, which comprises the following steps: integrating a line laser sensor and a numerical control machine tool, calibrating a sensor installation inclination angle, scanning and measuring a honeycomb core processing surface, and splicing measurement data of single scanning into whole surface morphology data of a honeycomb core. Honeycomb grid topological structure identification is carried out on a top view of the honeycomb core surface morphology data, morphology data of each honeycomb edge are segmented, noise data such as burrs and abnormal points contained in the morphology data are removed, surface shape data of each honeycomb edge are extracted, surface shape data of the whole honeycomb core are spliced according to original positions of the surface shape data, registration with a theoretical mathematical model is carried out, and the surface shape data of the honeycomb core are obtained. And calculating the error of the measured surface shape of the honeycomb core relative to the theoretical mathematical model. According to the method, the problem of difficulty in surface shape measurement and data processing of the honeycomb core with the discontinuous thin-wall structure is effectively solved, and the measurement requirement of the surface shape precision of the actually-processed honeycomb core can be met.

Description

Technical Field

[0001] The present invention relates to the field of line laser measurement technology, and in particular to a method and system for measuring the shape accuracy of a processed surface of a honeycomb core component. Background Art

[0002] Honeycomb core is a low-density honeycomb material that is widely used in aerospace, high-speed trains and other fields due to its high specific strength, specific stiffness and other excellent properties. Honeycomb core is usually bonded with upper and lower skins to form a sandwich structure to achieve the purpose of weight reduction. As the core material of the sandwich structure, the honeycomb core needs to be processed into a specific geometric shape during the preparation of the sandwich structure, and then bonded with the upper and lower skins to form an integral sandwich structure. The machining surface is the mating surface with the skin, and its machining accuracy directly affects its degree of fit with the upper and lower skins. Aviation manufacturing companies require the machining accuracy of the honeycomb core surface to be ±0.2mm. If the surface accuracy of the honeycomb core machining surface does not meet the requirements, its bonding surface is prone to debonding or insufficient glue application, reducing the strength of the sandwich component. The machining surface accuracy of the honeycomb core is a key factor affecting the quality of the sandwich component. The guarantee of the machining surface accuracy must be achieved through effective surface accuracy detection methods.

[0003] As a composite material completely different from traditional metal materials, the honeycomb core has strong structural anisotropy and high toughness of the material itself, which makes its processing technology very complicated. At present, most scholars focus on its research on processing technology and its impact on the quality of the processed surface, such as the uncut fibers and honeycomb wall tearing that are easy to produce. There is insufficient research on the surface accuracy of honeycomb core processing. The weak stiffness characteristics of honeycomb materials make it easy to deform under stress during processing, resulting in a certain error between the ideal processing surface shape and the actual processing surface shape, which restricts the accuracy of the processing surface shape. Therefore, there is an urgent need to study the honeycomb core surface accuracy evaluation technology to improve the processing accuracy of honeycomb materials.

[0004] Patent application number 202310723545.4, entitled "A Honeycomb Material Processing Surface Profile Accuracy Measurement Device and Method Thereof," discloses a method for measuring the profile of a honeycomb material using its RGBD information, but does not disclose methods for processing the measurement data. Patent applications number 201610585321.1, entitled "A Honeycomb Core Surface Profile Measurement Method," and patent application number 201610585419.7, entitled "A Honeycomb Core Surface Profile Measurement Device," disclose a membrane-coated honeycomb core surface profile measurement method. A thin film is applied to the surface of the workpiece to be measured, which is then pressed against the honeycomb core surface with a certain degree of vacuum. The film surface is measured using a laser displacement sensor, and the honeycomb core surface profile is then extracted. Patent applications No. 201711001309.2, entitled "A Method for Identifying Honeycomb Edge Regions from Honeycomb Core Surface Measurement Data," and No. 201910503383.7, entitled "A Method for Identifying Honeycomb Edges from Honeycomb Core Surface Measurement Data," both disclose methods for identifying honeycomb edge regions in three-dimensional honeycomb core surface measurement data. Patent applications No. 201711002057.5, entitled "Method for Removing Burrs from Honeycomb Core Surface Shape Measurement Data," and No. 201810379213.8, entitled "Method for Removing Burrs from Honeycomb Core Surface Shape Measurement Data," both disclose methods for removing noise data from three-dimensional honeycomb core surface measurement data. Patent applications No. 201910829610.5, entitled "Method for Measuring Honeycomb Core Surface Profile," and No. 201910829120.5, entitled "Method for Determining Line Laser Installation Error Angle," both disclose methods for calibrating line laser sensors. However, the aforementioned patents only disclose a single technology, failing to implement a complete method and system for measuring the shape of the honeycomb core machined surface. Furthermore, no effective solution for calculating honeycomb core surface shape errors has been found. The urgent challenge of achieving 3D measurement of honeycomb core machined surfaces is to rationally integrate existing line laser scanning measurement methods with honeycomb core measurement data processing methods. Summary of the Invention

[0005] In view of the above problems, the present invention discloses a method and system for measuring the shape accuracy of the processed surface of a honeycomb core component.

[0006] A method for measuring the shape accuracy of a honeycomb core component machining surface comprises the following steps:

[0007] Step 1: Set up the measurement platform and perform an initial scan of the honeycomb core surface or standard part used to calibrate the laser sensor. Install the line laser sensor on the spindle of the CNC motion machine tool. The CNC machine tool controls the line laser sensor to perform an initial scan along the honeycomb core surface or standard part to obtain measurement data of the honeycomb core surface.

[0008] Step 2: Calibration of the Line Laser Sensor

[0009] Based on the measurement data of the honeycomb core surface or standard parts in step 1, the inclination error of the line laser installation is calibrated;

[0010] Step 3: Scan the honeycomb core to be tested

[0011] The CNC machine tool drives the line laser sensor to scan along a certain path to ensure that the entire honeycomb core to be tested is within the sensor's range;

[0012] Step 4: Measurement Data Stitching

[0013] The data scanned by each track of the line laser is a strip area consistent with the width of the line laser. After the measurement movement is completed, the measurement data is transformed from the sensor coordinate system to the machine tool coordinate system according to the scanning track, and the data measured under different measurement paths are spliced ​​into the topography data of the entire honeycomb core surface being measured;

[0014] Step 5: Reconstruction of the cellular grid topology from the measurement data

[0015] The top view of the surface topography data of the honeycomb core to be tested is used to identify the honeycomb intersections, honeycomb edges, and periodic hexagonal units, establish the honeycomb grid topology structure, determine the position of each honeycomb edge, and segment the data of each honeycomb edge for separate data processing;

[0016] Step 6: Extracting the honeycomb core surface shape from the measured data

[0017] Process the segmented honeycomb edge morphology data, remove the noise data in the measurement data, extract the morphology data of each honeycomb edge, and splice it into the entire honeycomb core surface shape data according to its original position;

[0018] Step 7: Calculation of honeycomb core machining surface shape accuracy

[0019] The extracted honeycomb core surface shape is registered with the theoretical model, the measured honeycomb core surface shape and the theoretical model are transformed into the same coordinate system, and the error of the measured honeycomb core surface shape relative to the theoretical model is calculated.

[0020] Furthermore, the measurement platform is constructed by:

[0021] The line laser sensor is installed on the machine tool spindle through a standard tool holder interface that matches the machine tool spindle. The grating scale / encoder installed on the machine tool spindle provides a trigger signal. The CNC machine tool controls the line laser sensor to scan along the honeycomb core surface or standard parts to obtain measurement data of the honeycomb core surface or standard parts. At the same time, during the scanning measurement process, the measurement data is continuously stored in the local computer in real time, ensuring that large-sized workpieces can be scanned.

[0022] Furthermore, the calibration of the line laser sensor is implemented as follows:

[0023] By scanning the honeycomb core surface or the standard part itself, the misalignment formed after data splicing is used to reversely calculate the inclination angle of the line laser sensor, and the calculated inclination angle of the line laser sensor is mechanically adjusted or directly numerically compensated into the measurement data.

[0024] Furthermore, the method for scanning the honeycomb core to be tested is:

[0025] When the line laser sensor moves to scan the honeycomb core, the tilt direction of the sensor is kept unchanged so that the center line of the sensor laser plane is parallel to the axis of each honeycomb cell. The sensor is driven by the CNC machine tool to move in parallel planes so that the height of the scanning track matches the height of the honeycomb core, completing the scanning of the entire honeycomb core surface to be measured. The projection of the scanning track on the two-dimensional plane is an equidistant straight line.

[0026] Furthermore, the method for extracting the honeycomb grid from the measurement data is as follows:

[0027] The honeycomb edge intersections, honeycomb edges, and periodic hexagonal units are identified in the top view of the honeycomb core surface morphology measurement data; first, the feature points of the honeycomb core morphology image are roughly checked based on the image grayscale changes, and the feature points are roughly identified using a corner detection algorithm. At the same time, an image compression algorithm is used to perform feature enhancement and noise suppression to improve the accuracy of the honeycomb edge intersections in the feature points; further, according to the different distributions of honeycomb edges in the neighborhoods of different types of feature points and the different geometric patterns formed, a precise identification method for feature points as Y-shaped intersections, human-shaped intersections, or redundant feature points is proposed; based on the honeycomb edge intersection positioning method and the positional relationship analysis of the honeycomb grid geometric elements, a sequential identification method for the honeycomb grid topology structure is used to achieve reconstruction of the grid topology structure of the entire measured surface of the honeycomb core.

[0028] Furthermore, the method for extracting the surface shape of the honeycomb core from the measurement data is as follows:

[0029] The honeycomb edge morphology measurement data is reduced from three-dimensional space to a two-dimensional plane, and the noise data is identified on the two-dimensional plane, and then restored to the original three-dimensional space to eliminate the noise data. In the two-dimensional plane, an adaptive sampling fitting method is used for coarse noise identification to eliminate noise far away from the honeycomb edge. Regression analysis is used for fine noise identification to eliminate noise near the honeycomb edge. Local weighted regression is used to synchronously smooth and streamline the honeycomb edge measurement data after noise elimination to extract the honeycomb edge end face data, which is then spliced ​​into complete grid-like honeycomb core surface shape data.

[0030] Furthermore, the communication between the motion control, sensor and computer in the measurement system is realized by:

[0031] It includes real-time tasks and non-real-time tasks: the real-time task mainly completes the line laser scanning measurement function, uses the encoder to output a signal synchronized with the displacement of the motion axis to control the line laser to perform synchronous scanning and measurement on the workpiece; the line laser measurement data is transmitted to the computer in real time and stored on the computer hard disk, and the synchronous action instructions in the CNC module are used to control the working state of the line laser; the non-real-time task is mainly used to perform preparatory work before data collection and data processing after measurement, including calibration of the sensor installation inclination angle, generation of measurement CNC program, data splicing, recognition of honeycomb grid geometric elements, and extraction of grid surface shape data and other data processing processes.

[0032] A honeycomb core component machining surface shape accuracy measurement system, comprising:

[0033] Line laser sensor;

[0034] A numerically controlled motion platform, used for clamping the laser measuring sensor and completing the position adjustment of the laser measuring sensor, wherein the numerically controlled motion platform is equipped with a grating ruler / encoder for providing a trigger signal;

[0035] A main control system, comprising a numerical control system for controlling the numerical control motion platform and a data processing system for processing data measured by the laser measurement sensor;

[0036] The data processing system comprises:

[0037] The data splicing module is used to complete the data splicing of each segmented data based on the segmented data transmitted by the line laser sensor, and splice the data measured under different measurement paths into the topography data of the entire measured honeycomb core surface;

[0038] The line laser sensor calibration module is used to reversely calculate the inclination angle of the line laser sensor based on the misalignment formed by the initial scan data, thereby completing the calibration of the line laser sensor;

[0039] Coordinate construction module, used to complete the construction of machine tool coordinate system, sensor coordinate system and workpiece coordinate system;

[0040] The coordinate conversion module is used to complete the scanning trajectory and transform the measurement data from the sensor coordinate system to the machine tool coordinate system based on the measured data output by the data splicing module;

[0041] Honeycomb grid topology reconstruction module, used to extract honeycomb edge intersections, honeycomb edges, and periodic hexagonal units based on the honeycomb core surface topography measurement data output by the coordinate conversion module;

[0042] A denoising module, used to perform denoising on the data identified by the cellular grid topology reconstruction module;

[0043] The registration module is used to identify the error after comparing the data processed by the denoising module with the theoretical numerical model, calculate the error of each data point, and obtain the distribution information of the measured honeycomb core processing surface error.

[0044] Compared with the prior art, the present invention has the following advantages:

[0045] 1. High measurement accuracy. The measurement system based on line laser has an accuracy of up to micron level, which can realize accurate measurement of honeycomb wall surface morphology.

[0046] 2. Provides a complete solution for automated measurement of honeycomb core processing surfaces;

[0047] 3. It involves a complete solution of measurement data splicing, noise reduction, surface shape extraction and error calculation.

[0048] 4. Suitable for on-machine measurement, it realizes the effective measurement of the surface shape of the processed honeycomb core and the solution of its surface error distribution. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the embodiments of the present invention or the technical solutions of the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0050] Figure 1 The present invention is a flow chart of the method for measuring the shape accuracy of the processed surface of the honeycomb core component.

[0051] Figure 2 This is a physical diagram of the sensor installation in an embodiment of the present invention.

[0052] Figure 3 2 is a diagram of an apparatus for constructing a measurement platform in an embodiment of the present invention.

[0053] Figure 4 Schematic diagram of the scanning trajectory of the linear laser sensor in an embodiment of the present invention.

[0054] Figure 5 It is the coordinate system in the linear laser measurement system in the embodiment of the present invention.

[0055] Figure 6 It is the communication architecture in the measurement system in the embodiment of the present invention.

[0056] Figure 7 This is a three-dimensional digital model of a polygonal composite honeycomb core measured in Example 1 of the present invention and its measurement site.

[0057] Figure 8This is the surface morphology measurement data of the polygonal composite honeycomb core in Example 1 of the present invention.

[0058] Figure 9 This is a cloud diagram of the surface shape data of the polygonal composite honeycomb core extracted in Example 1 of the present invention.

[0059] Figure 10 This is a cloud diagram of the surface shape error distribution of the polygonal composite honeycomb core in the first embodiment of the present invention.

[0060] Figure 11 This is a three-dimensional digital model of the parabolic honeycomb core measured in Example 1 of the present invention and its measurement site.

[0061] Figure 12 This is a cloud diagram of the measured data of the parabolic honeycomb core surface in Example 1 of the present invention.

[0062] Figure 13 This is the surface shape of the parabolic honeycomb core extracted in Example 1 of the present invention.

[0063] Figure 14 This is the distribution of surface shape errors of the parabolic honeycomb core in the first embodiment of the present invention. DETAILED DESCRIPTION

[0064] To make the purpose, technical solutions and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention are clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention:

[0065] like Figure 1 As shown: The embodiment of the present invention discloses a method for measuring the shape accuracy of the processed surface of a honeycomb core component. The technical solution adopted by the present invention is specifically implemented as follows:

[0066] Step 1: Set up the measurement platform

[0067] The line laser sensor is installed on the machine tool spindle through the standard tool holder interface that matches the machine tool spindle, such as Figure 2 As shown, the grating ruler / encoder installed on the machine tool spindle provides a trigger signal, and the laser sensor is used to scan along the surface of the honeycomb core through the CNC machine control line to obtain the measurement data of the honeycomb core surface. The device diagram is shown in Figure 3 As shown; at the same time, during the scanning measurement process, the measurement data is continuously stored in the local computer in real time, ensuring that large-sized workpieces can be scanned.

[0068] Step 2: Calibration of the Line Laser Sensor

[0069] In this embodiment, the method in the patent application number 201910829120.5 can be used. By scanning the surface of the honeycomb core itself, the misalignment amount formed after data splicing is used to inversely calculate the inclination angle of the line laser sensor. The calculated inclination angle of the line laser sensor is mechanically adjusted or directly numerically compensated to the measurement data to solve the misalignment problem during data splicing caused by the fact that the line laser coordinate system is not completely parallel to the machine tool coordinate system.

[0070] Step 3: Scan the honeycomb core to be tested

[0071] When the line laser sensor moves and scans the honeycomb core, the tilt direction of the line laser sensor is kept unchanged, so that the center line of the laser plane of the line laser sensor is parallel to the axis of each honeycomb cell. The line laser sensor is driven by the CNC machine tool to move along a predetermined path in mutually parallel planes, so that the height of the scanning track matches the height of the honeycomb core, completing the scanning of the entire honeycomb core surface to be measured. The projection of the scanning track on the two-dimensional plane is an equidistant straight line, such as Figure 4 shown.

[0072] Step 4: Measurement Data Stitching

[0073] The data scanned by each track of the line laser is a strip area consistent with the width of the line laser. After the measurement movement is completed, the measurement data is transformed from the sensor coordinate system to the machine tool coordinate system according to the scanning track, and the data measured under different measurement paths are spliced ​​into the topography data of the entire honeycomb core surface being measured. The coordinate system in the line laser measurement system is as follows: Figure 5 shown.

[0074] Step 5: Reconstruction of the cellular grid topology from the measurement data

[0075] The top view of the honeycomb core surface morphology measurement data is used to identify honeycomb edge intersections, honeycomb edges, and periodic hexagonal units. In this embodiment, the method in the patent with application number 201910503383.7 can be used. First, the feature points of the honeycomb core morphology image are roughly checked based on the image grayscale change, and the existing corner detection algorithm is used for identification, including the use of Harris, CSS, and SUSAN corner detection algorithms to roughly identify the feature points. At the same time, the image compression algorithm can be used for feature enhancement and noise suppression to improve the accuracy of the honeycomb edge intersections in the feature points. Furthermore, according to the different distribution of honeycomb edges in the neighborhood of different types of feature points and the different geometric patterns formed, a precise identification method for feature points as Y-shaped intersections, human-shaped intersections, or redundant feature points is proposed. Based on the honeycomb edge intersection positioning method and the positional relationship analysis of the honeycomb grid geometric elements, a sequential identification method for the honeycomb grid topology structure is used to realize the reconstruction of the grid topology structure of the entire measured surface of the honeycomb core.

[0076] Step 6: Extracting the honeycomb core surface shape from the measured data

[0077] In this embodiment, the method described in patent application number 201810379213.8 can be used to reduce the dimensionality of honeycomb edge topography measurement data from three-dimensional space to a two-dimensional plane. Noise data is identified on the two-dimensional plane and then restored to the original three-dimensional space to remove the noise data. In the two-dimensional plane, an adaptive sampling and fitting method is used for coarse noise identification to remove noise far from the honeycomb edge. Regression analysis is used for fine noise identification to remove noise near the honeycomb edge. This patent further improves the method by using local weighted regression to simultaneously smooth and streamline the honeycomb edge measurement data after noise removal, extracting honeycomb edge end face data, and then splicing it into complete grid-like honeycomb core surface shape data.

[0078] Step 7: Calculation of honeycomb core machining surface shape accuracy

[0079] The extracted honeycomb core surface shape is registered with the theoretical model, the measured honeycomb core surface shape and the theoretical model are transformed into the same coordinate system, and the error of the measured honeycomb core surface shape relative to the theoretical model is calculated.

[0080] The implementation methods of communication between motion control, sensors and computers in the measurement system include real-time tasks and non-real-time tasks: the real-time task mainly completes the line laser scanning measurement function, and uses the encoder to output a signal synchronized with the displacement of the motion axis to control the line laser to perform synchronous scanning measurement on the workpiece. The data measured by the line laser is transmitted to the computer in real time and stored on the computer hard disk. The synchronous action instructions in the CNC module are used to control the working state of the line laser; the non-real-time task is mainly used to perform preparatory work before data collection and data processing after measurement, including calibration of sensor installation inclination angle, generation of measurement CNC program, data splicing, recognition of honeycomb grid geometric elements, and extraction of grid surface shape data and other data processing processes. The communication architecture is such as Figure 6 shown.

[0081] Example 1

[0082] Given the honeycomb core wall thickness range (0.05 to 0.13 mm), the sensor model selected was the Gocator 2520 from LMI Technologies, Canada. The sensor provides 1920 data points per measurement, with an x-axis resolution of 13 to 17 μm, an x-axis field of view of 25 to 32.5 mm, and a z-axis measurement range of 25 mm. The scanning measurement system developed in this study was integrated into the machining center to perform on-machine measurement of the processed honeycomb core. The measured data was then used to identify the geometric elements of the honeycomb mesh and extract the mesh-like surface shape, thereby obtaining the discontinuous honeycomb core surface shape. To analyze the surface shape error of the measured sample, the coordinate system of the extracted surface shape must be aligned with the coordinate system of the theoretical model. When measuring the honeycomb core on-machine, the coordinate system selected during scanning trajectory planning can be used for coarse alignment, and the ICP algorithm can be used for fine alignment. Aligning the extracted honeycomb core surface shape with the theoretical model allows the error at each data point to be calculated, thus obtaining the distribution of the measured surface shape error. The polygonal composite honeycomb core used for measurement is as follows Figure 7 As shown in the figure, the surface morphology measurement data cloud map is as follows Figure 8 As shown, there are a lot of noise data such as burrs and abnormal points near and below the honeycomb grid end surface data. The surface shape data cloud map extracted by the patent of this invention is Figure 9 The number of data points is 424249. It can be seen that the algorithm in this paper can effectively remove noise data and obtain the grid-like honeycomb core surface shape. The extracted honeycomb core surface is aligned with the theoretical digital model, and the obtained honeycomb core processing surface shape error distribution diagram is as follows: Figure 10 As shown in the figure, the calculated RMS value of the machined surface shape error is 0.046 mm, which is within the machining accuracy tolerance. The machined surface shape error distribution diagram clearly shows the error distribution and provides a data basis for further surface shape correction. Compared to other published invention patents, no calculation results have been reported for the machined surface shape error of honeycomb cores.

[0083] Example 2

[0084] The parabolic honeycomb core is measured as Figure 11 As shown, the surface morphology measurement data cloud map is Figure 12 , a large number of noise data points can be clearly seen. The surface shape data cloud map extracted by the algorithm in this paper is Figure 13 , a total of 90634 data points, the grid-shaped honeycomb core processing surface is complete, and the noise data has been eliminated. After registration with the ideal digital model, the calculated processing surface error distribution cloud map is as follows Figure 14 As shown in the figure, the RMS value of the parabolic honeycomb core machining surface error calculated by the algorithm in this paper is 0.069 mm, which is within the tolerance range required by the machining accuracy.

[0085] The above description is only a preferred specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any technician familiar with the technical field, within the technical scope disclosed by the present invention, who makes equivalent replacements or changes based on the technical solution and inventive concept of the present invention, should be covered by the scope of protection of the present invention.

Claims

1. A method for measuring the shape accuracy of a honeycomb core component processing surface, characterized in that: The steps include: Step 1: Set up the measurement platform and perform an initial scan of the honeycomb core surface or standard part used to calibrate the laser sensor. Install the line laser sensor on the spindle of the CNC motion machine tool. The CNC machine tool controls the line laser sensor to perform an initial scan along the honeycomb core surface or standard part to obtain measurement data of the honeycomb core surface. Step 2: Calibration of the Line Laser Sensor Based on the measurement data of the honeycomb core surface or standard parts in step 1, the inclination error of the line laser installation is calibrated; Step 3: Scan the honeycomb core to be tested The CNC machine tool drives the line laser sensor to scan along a certain path to ensure that the entire honeycomb core to be tested is within the sensor's range; Step 4: Measurement Data Stitching The data scanned by each track of the line laser is a strip area consistent with the width of the line laser. After the measurement movement is completed, the measurement data is transformed from the sensor coordinate system to the machine tool coordinate system according to the scanning track, and the data measured under different measurement paths are spliced ​​into the topography data of the entire honeycomb core surface being measured; Step 5: Reconstruction of the cellular grid topology from the measurement data The top view of the surface topography data of the honeycomb core to be tested is used to identify the honeycomb intersections, honeycomb edges, and periodic hexagonal units, establish the honeycomb grid topology structure, determine the position of each honeycomb edge, and segment the data of each honeycomb edge for separate data processing; Step 6: Extracting the honeycomb core surface shape from the measured data Process the segmented honeycomb edge morphology data, remove the noise data in the measurement data, extract the morphology data of each honeycomb edge, and splice it into the entire honeycomb core surface shape data according to its original position; Step 7: Calculation of honeycomb core machining surface shape accuracy The extracted honeycomb core surface shape is registered with the theoretical model, the measured honeycomb core surface shape and the theoretical model are transformed into the same coordinate system, and the error of the measured honeycomb core surface shape relative to the theoretical model is calculated.

2. The method for measuring the shape accuracy of the processed surface of a honeycomb core member according to claim 1, wherein: The implementation method of building the measurement platform is as follows: The line laser sensor is installed on the machine tool spindle through a standard tool holder interface that matches the machine tool spindle. The grating scale / encoder installed on the machine tool spindle provides a trigger signal. The CNC machine tool controls the line laser sensor to scan along the honeycomb core surface or standard parts to obtain measurement data of the honeycomb core surface or standard parts. At the same time, during the scanning measurement process, the measurement data is continuously stored in the local computer in real time, ensuring that large-sized workpieces can be scanned.

3. The method for measuring the shape accuracy of the processed surface of a honeycomb core member according to claim 1, wherein: The calibration method of the line laser sensor is as follows: By scanning the honeycomb core surface or the standard part itself, the misalignment formed after data splicing is used to reversely calculate the inclination angle of the line laser sensor, and the calculated inclination angle of the line laser sensor is mechanically adjusted or directly numerically compensated into the measurement data.

4. The method for measuring the shape accuracy of the processed surface of a honeycomb core member according to claim 1, wherein: The method for scanning the honeycomb core to be tested is as follows: When the line laser sensor moves to scan the honeycomb core, the tilt direction of the sensor is kept unchanged so that the center line of the sensor laser plane is parallel to the axis of each honeycomb cell. The sensor is driven by the CNC machine tool to move in parallel planes so that the height of the scanning track matches the height of the honeycomb core, completing the scanning of the entire honeycomb core surface to be measured. The projection of the scanning track on the two-dimensional plane is an equidistant straight line.

5. The method for measuring the shape accuracy of the processed surface of a honeycomb core member according to claim 1, wherein: The method for extracting the honeycomb grid from the measurement data is as follows: The top view of the honeycomb core surface topography measurement data is used to identify honeycomb edge intersections, honeycomb edges, and periodic hexagonal units. First, based on the grayscale changes in the image, the feature points of the honeycomb core topography image are roughly checked. A corner detection algorithm is used to roughly identify the feature points. An image compression algorithm is used to enhance features and suppress noise, improving the accuracy of honeycomb edge intersections in the feature points. Based on the different distributions of honeycomb edges in the neighborhoods of different feature points and the different geometric patterns formed, a method is proposed to accurately identify feature points as Y-shaped intersections, human-shaped intersections, or redundant feature points. Based on the honeycomb edge intersection positioning method and the position relationship analysis of the honeycomb grid geometric elements, a sequential identification method of the honeycomb grid topology structure is used to reconstruct the grid topology structure of the entire measured surface of the honeycomb core.

6. The method for measuring the shape accuracy of the processed surface of a honeycomb core member according to claim 1, wherein: The method for extracting the surface shape of the honeycomb core from the measurement data is as follows: The honeycomb edge morphology measurement data is reduced from three-dimensional space to a two-dimensional plane, noise data is identified on the two-dimensional plane, and then restored to the original three-dimensional space to remove the noise data; On a two-dimensional plane, an adaptive sampling and fitting method is used for coarse noise identification to remove noise far away from the honeycomb edge; regression analysis is used for fine noise identification to remove noise near the honeycomb edge; local weighted regression is used to synchronously smooth and streamline the honeycomb edge measurement data after noise removal, and the honeycomb edge end face data is extracted, which is then spliced ​​into a complete grid-like honeycomb core surface shape data.

7. The method for measuring the shape accuracy of the processed surface of a honeycomb core member according to claim 1, wherein: The method for implementing communication between motion control, sensors and computers in the measurement system is as follows: It includes real-time tasks and non-real-time tasks: the real-time task mainly completes the line laser scanning measurement function, uses the encoder to output a signal synchronized with the displacement of the motion axis to control the line laser to perform synchronous scanning and measurement on the workpiece; the line laser measurement data is transmitted to the computer in real time and stored on the computer hard disk, and the synchronous action instructions in the CNC module are used to control the working state of the line laser; the non-real-time task is mainly used to perform preparatory work before data collection and data processing after measurement, including calibration of the sensor installation inclination angle, generation of measurement CNC program, data splicing, recognition of honeycomb grid geometric elements, and extraction of grid surface shape data and other data processing processes.

8. A honeycomb core component processing surface shape accuracy measurement system, characterized in that: include: Line laser sensor; A numerically controlled motion platform, used for clamping the laser measuring sensor and completing the position adjustment of the laser measuring sensor, wherein the numerically controlled motion platform is equipped with a grating ruler / encoder for providing a trigger signal; A main control system, comprising a numerical control system for controlling the numerical control motion platform and a data processing system for processing data measured by the laser measurement sensor; The data processing system comprises: The data splicing module is used to complete the data splicing of each segmented data based on the segmented data transmitted by the line laser sensor, and splice the data measured under different measurement paths into the topography data of the entire measured honeycomb core surface; The line laser sensor calibration module is used to reversely calculate the inclination angle of the line laser sensor based on the misalignment formed by the initial scan data, thereby completing the calibration of the line laser sensor; Coordinate construction module, used to complete the construction of machine tool coordinate system, sensor coordinate system and workpiece coordinate system; The coordinate conversion module is used to complete the scanning trajectory and transform the measurement data from the sensor coordinate system to the machine tool coordinate system based on the measured data output by the data splicing module; Honeycomb grid topology reconstruction module, used to extract honeycomb edge intersections, honeycomb edges, and periodic hexagonal units based on the honeycomb core surface topography measurement data output by the coordinate conversion module; A denoising module, used to perform denoising on the data identified by the cellular grid topology reconstruction module; The registration module is used to identify the error after comparing the data processed by the denoising module with the theoretical numerical model, calculate the error of each data point, and obtain the distribution information of the measured honeycomb core processing surface error.

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