A method for measuring the waviness of a critical area of an aircraft in RVSM

Abstract

The application belongs to the technical field of aircraft design, and particularly relates to a special method for measuring the waviness of a key area of an aircraft RVSM, target points of a measurement area are made and pasted on the measurement area; the surface information of the measurement area is collected through the target points, and measurement data is obtained after processing; the measurement data is matched with theoretical data boundaries to obtain measurement point cloud data, the measurement point cloud data is fitted with a reference surface to obtain a smooth surface; the smooth surface is fitted with an actual measurement surface, and then waviness parameter analysis is performed to obtain the wavelength, amplitude and waviness parameter of each wave on the actual measurement intersection line. Through rapid calibration of a measurement system, target point measurement, completion of surface measurement and detection of the measurement area, and then matching of the measurement data with the theoretical data boundaries, fitting of the reference surface, fitting of the actual measurement surface, and finally waviness analysis, the measurement precision is greatly improved and the measurement period is shortened.

Description

Technical Field

[0001] This application belongs to the field of aircraft design technology, and specifically relates to a dedicated method for measuring the waviness of critical areas of an aircraft RVSM. Background Technology

[0002] When an aircraft operates in RVSM airspace, its altitude measurement system error must meet the requirements specified in Advisory Circular AC-21-13 (Airworthiness Approval for Aircraft Operating with a 300-meter (1000-foot) Vertical Separation Standard in RVSM Airspace). The static pressure measured by the aircraft's static pressure source is related to flight altitude. In RVSM airworthiness, a critical area is designated near the aircraft's static pressure source. Factors such as skin surface waviness and static pressure sensor installation step differences within this critical area are significant sources of altitude measurement system error.

[0003] Aircraft surface waviness measurement generally employs two-dimensional and three-dimensional methods. For critical areas of the aircraft RVSM (Reverse Vehicle Surface Measuring), three-dimensional photogrammetry is typically used due to its high accuracy and speed. However, for critical areas of multiple aircraft RVSMs, higher demands are placed on the accuracy, stability, and efficiency of waviness measurement data. Traditional three-dimensional measurement methods cannot meet the requirements for RVSM surface waviness measurement.

[0004] Therefore, how to conduct more effective RVSM surface waviness measurement is a problem that needs to be solved. Summary of the Invention

[0005] To address the aforementioned issues, this application provides a dedicated method for measuring the waviness of critical areas of an aircraft RVSM, thereby resolving the problem that traditional three-dimensional measurement methods in the prior art cannot meet the requirements for measuring the surface waviness of RVSMs.

[0006] The technical solution of this application is: a dedicated method for measuring the waviness of critical areas in an aircraft RVSM (Real Vehicle Surface Mode), comprising:

[0007] Create target points for the measurement area and paste the target points into the measurement area;

[0008] By locating target points, surface information of the measurement area is collected and processed to obtain measurement data;

[0009] The measurement data is matched with the theoretical data boundary to obtain the measurement point cloud data. The measurement point cloud data is then fitted with a reference surface to obtain a smooth surface.

[0010] The smooth surface is fitted to the measured surface, and then the waviness parameter is analyzed to obtain the wavelength, amplitude and waviness parameters of each waviness on the measured intersection line.

[0011] Preferably, the surface information of the measurement area is collected as follows:

[0012] Set the measurement point density, scanning parameters, and scanning mode, and use a laser scanner to collect surface information of the measurement area;

[0013] The laser scanner transmits the collected data to the back-end equipment, which verifies the integrity and relative positional relationship of the collected data; after the verification is passed, the measurement data is obtained.

[0014] Preferably, the measurement point density is set to 5 mm, and the scanning parameters include scanning resolution, exposure parameters, and scanning control parameters; the scanning mode adopts long-distance scanning mode.

[0015] Preferably, based on the coordinates of the matching points in the measurement data and the corresponding coordinate points in the theoretical data, the measurement data is matched against the theoretical data boundary using the coordinate transformation function to obtain the measurement point cloud data.

[0016] Preferably, the measured point cloud data is fitted with a reference surface. The reference surface is formed by processing the measured point cloud data using the least squares method based on the characteristics of the measured surface.

[0017] Preferably, the least squares method is as follows:

[0018] f(x) = c0 + c1x + c2x² + ... + cnxn;

[0019] Where c0, c1, c2, cn, and xn are the set curve shape coefficients, x is the set dimensionless axial parameter, and f(x) is the longitudinal coordinate of the reference curve.

[0020] Preferably, when performing waviness parameter analysis, the given plane is intersected with the reference surface and the measured surface through planar intersection analysis to obtain the curve wave data on the plane, and the wavelength, amplitude and waviness parameters of each ripple on the measured intersection line are calculated.

[0021] Preferably, the specific method for analyzing plane intersections is as follows:

[0022] The intersection of the given plane with the reference surface and the measured surface is obtained to obtain the reference curve and the measured curve in the given plane. The difference between the measured curve and the reference curve in the given plane in the direction of the normal of the reference curve is calculated to obtain the waviness curve. The position of the point of maximum or minimum curvature on the waviness curve is obtained by calculation, and then the crest and trough of the waviness are obtained.

[0023] The length of the straight line connecting adjacent crests and troughs is the wavelength of the ripple, and the distance from the trough point between adjacent crests to the line connecting the crests is the amplitude.

[0024] Preferably, when fitting the smooth surface to the measured surface, the maximum deviation of the point cloud fitting between the measured surface and the smooth surface is no more than 0.1 mm, and the fitting is completed.

[0025] Preferably, a waviness analysis software is used for waviness analysis. During the analysis, the fitted data point cloud is filtered at a 2mm interval, and the filtered data point cloud is used to fit and form a reference surface for the measurement area. Each side of the reference surface for the measurement area has 48 horizontal profiles with a horizontal profile interval of 20mm. The horizontal profiles near the center of the sensor pass through the center point of the sensor.

[0026] The dedicated method for measuring waviness in critical areas of aircraft RVSM in this application has the following advantages:

[0027] Starting with the preparation of customized target points for the measurement area, through rapid calibration of the measurement system, target point measurement, completion of surface measurement and inspection of the measurement area, and then proceeding to boundary matching of measurement data with theoretical data, fitting of reference surface, fitting of measured surface, and finally using a dedicated formatting program for waviness analysis, a detailed and dedicated three-dimensional waviness measurement method is provided. This method greatly improves measurement accuracy, shortens the measurement cycle, and ensures the consistency of measurements across multiple machines. Attached Figure Description

[0028] Figure 1 This is a schematic diagram of the overall process of this application;

[0029] Figure 2 This is a schematic diagram of the target point pasting template for this application;

[0030] Figure 3 This is a schematic diagram of the waviness analysis in this application. Detailed Implementation

[0031] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions in the embodiments of this application will be described in more detail below with reference to the accompanying drawings. In the drawings, the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The described embodiments are only some, not all, of the embodiments of this application. The embodiments described below with reference to the accompanying drawings are exemplary and intended to explain this application, and should not be construed as limiting this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application. The embodiments of this application will be described in detail below with reference to the accompanying drawings.

[0032] The first aspect of this application provides a dedicated method for measuring the waviness of critical areas in an aircraft RVSM, such as... Figure 1 Specifically, it includes the following steps:

[0033] Step 1: Preparation and application of target points in the measurement area:

[0034] To ensure measurement efficiency and consistency across multiple measurement setups, and to facilitate matching with the theoretical coordinate system, a target point pasting template for the measurement area was specially manufactured. Target points are pasted into the template openings on the equipment according to actual measurement needs. A schematic diagram of the target point template is shown below. Figure 2 As shown.

[0035] Preferably, the spacing between the special target point pasting templates is 30mm to 250mm, see Figure 2 As shown.

[0036] Step 2, rapid calibration of the measurement system:

[0037] Specifically, the equipment is quickly calibrated using a rapid calibration board to obtain its position in the theoretical coordinate system.

[0038] Step 3, Target Point Measurement:

[0039] The position of the target point on the equipment is measured to obtain the position of the target point on the equipment, and then the position of the target point in the theoretical coordinate system is obtained.

[0040] The position of the target point can be obtained by acquiring the structural parameters of the current device, thereby obtaining the coordinates of the template pasting position of the target point. Then, the position of the target point on the template is measured by measuring the ruler to obtain the specific coordinates of the target point in the theoretical coordinate system.

[0041] Step 4, Surface measurement and inspection of the measurement area:

[0042] Specifically, the steps include the following:

[0043] Step S410: Set the measurement point density;

[0044] Step S420: Set the scanning parameters and scanning mode;

[0045] Scanning parameters include scan resolution, exposure parameter settings, scan control, advanced parameter settings, and professional parameter settings. This measurement experiment adopts a long-distance scanning mode to increase the measurement range of the equipment and achieve the measurement goal of acquiring all data completely.

[0046] Step S430: A laser scanner is used to collect surface information of the measurement area; the laser scanner transmits the collected data to the back-end equipment, which verifies the integrity and relative positional relationship of the collected data; after the verification is passed, the measurement data is obtained.

[0047] The backend device can be a laptop, etc.

[0048] A laser scanner is used to collect surface information of the measurement area. During the measurement process, the integrity and relative positional relationship of the measurement data are viewed in real time through a laptop to ensure the integrity and accuracy of the data collected in the measurement area.

[0049] Preferably, the measurement point density is set to 5mm; attention should be paid to the angle of the test piece and the distance between the test piece and the workpiece. The test piece should be moved smoothly, and the data of the blank positions should be collected completely using a laser.

[0050] Step 5: Matching the boundary between measured data and theoretical data:

[0051] Based on the coordinates of the matching points obtained from the measurement and the corresponding coordinates on the theoretical shape, the position matching between the measured point cloud and the theoretical shape is completed through the coordinate transformation function.

[0052] Step 6, Reference Surface Fitting: The reference surface is formed into a smooth surface using the least squares method based on the measured surface characteristics.

[0053] Preferably, the least squares method is as follows:

[0054] f(x) = c0 + c1x + c2x² + ... + cnxn;

[0055] Where c0, c1, c2, cn, and xn are the set curve shape coefficients, x is the set dimensionless axial parameter, and f(x) is the longitudinal coordinate of the reference curve.

[0056] Step 7, Measured surface fitting: The measured surface reflects the true geometric features of the measurement area, and the maximum deviation between the measured surface and the fitted point cloud is no more than 0.1 mm.

[0057] Step 8, Ripple Parameter Analysis:

[0058] The goal of waviness analysis is to obtain the true waviness of the measured surface. When performing waviness parameter analysis, the given plane is intersected with the reference surface and the measured surface through planar intersection analysis to obtain the curve wave data on the plane, and the wavelength, amplitude and waviness parameters of each waviness on the measured intersection line are calculated.

[0059] Combination Figure 3 The specific method for analyzing plane intersections is as follows:

[0060] The intersection of the given plane with the reference surface and the measured surface is obtained to obtain the reference curve and the measured curve in the given plane. The difference between the measured curve and the reference curve in the given plane in the direction of the normal of the reference curve is calculated to obtain the waviness curve. The position of the point of maximum or minimum curvature on the waviness curve is obtained by calculation, and then the crest and trough of the waviness are obtained.

[0061] The length of the straight line connecting adjacent crests and troughs is the wavelength L of the ripple, and the distance from the trough point between adjacent crests to the line connecting the crests is the amplitude b.

[0062] As needed for analysis and evaluation, the calculation of waviness parameters of measured curves and theoretical curves on multiple planes can be completed simultaneously. The calculation results are displayed in graphical form and output as records.

[0063] Preferably, waviness analysis software, such as gear waviness analysis software, is used for waviness analysis. During the analysis, the fitted data point cloud is filtered at a 2mm interval, and the filtered data point cloud is used to fit and form the reference surface of the measurement area. Each side of the reference surface of the measurement area has 48 horizontal profiles with a horizontal profile interval of 20mm. The horizontal profiles near the center of the sensor pass through the center point of the sensor.

[0064] In summary, this application has the following advantages:

[0065] Starting with the preparation of customized target points for the measurement area, through rapid calibration of the measurement system, target point measurement, completion of surface measurement and inspection of the measurement area, and then proceeding to boundary matching of measurement data with theoretical data, fitting of reference surface, fitting of measured surface, and finally using a dedicated formatting program for waviness analysis, a detailed and dedicated three-dimensional waviness measurement method is provided. This method greatly improves measurement accuracy, shortens the measurement cycle, and ensures the consistency of measurements across multiple machines.

[0066] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A dedicated method for measuring the waviness of critical areas in an aircraft RVSM, characterized in that, include: Create target points for the measurement area and paste the target points into the measurement area; By locating target points, surface information of the measurement area is collected and processed to obtain measurement data; The measurement data is matched with the theoretical data boundary to obtain the measurement point cloud data. The measurement point cloud data is then fitted with a reference surface to obtain a smooth surface. The smooth surface is fitted to the measured surface, and then the waviness parameter is analyzed to obtain the wavelength, amplitude and waviness parameters of each waviness on the measured intersection line. When performing waviness parameter analysis, the intersection of the given plane with the reference surface and the measured surface is obtained through planar intersection analysis. The wave data of the curve on the plane is obtained, and the wavelength, amplitude and waviness parameters of each wave on the measured intersection line are calculated. The specific method for analyzing plane intersection lines is as follows: The intersection of the given plane with the reference surface and the measured surface is obtained to obtain the reference curve and the measured curve in the given plane. The difference between the measured curve and the reference curve in the given plane in the direction of the normal of the reference curve is calculated to obtain the waviness curve. The position of the point of maximum or minimum curvature on the waviness curve is obtained by calculation, and then the crest and trough of the waviness are obtained. The length of the straight line connecting adjacent crests and troughs is the wavelength of the ripple, and the distance from the trough point between adjacent crests to the line connecting the crests is the amplitude.

2. The dedicated method for measuring the waviness of critical areas in an aircraft RVSM as described in claim 1, characterized in that, The surface information of the measurement area is collected as follows: Set the measurement point density, scanning parameters, and scanning mode, and use a laser scanner to collect surface information of the measurement area; The laser scanner transmits the collected data to the back-end equipment, which verifies the integrity and relative positional relationship of the collected data; after the verification is passed, the measurement data is obtained.

3. The dedicated method for measuring waviness in critical areas of an aircraft RVSM as described in claim 2, characterized in that, The measurement point density is set to 5mm, and the scanning parameters include scanning resolution, exposure parameters, and scanning control parameters; the scanning mode is long-distance scanning mode.

4. The dedicated method for measuring waviness in critical areas of an aircraft RVSM as described in claim 1, characterized in that, Based on the coordinates of the matching points in the measurement data and the corresponding coordinates in the theoretical data, the measurement data is matched with the theoretical data boundary through the coordinate transformation function to obtain the measurement point cloud data.

5. The dedicated method for measuring the waviness of critical areas in an aircraft RVSM as described in claim 1, characterized in that, A reference surface is fitted to the measured point cloud data. The reference surface is formed by processing the measured point cloud data using the least squares method based on the characteristics of the measured surface.

6. The dedicated method for measuring waviness in critical areas of an aircraft RVSM as described in claim 5, characterized in that, The least squares method is: f(x) = c0 + c1x + c2x² + ... + cnxn; Where c0, c1, c2, cn, and xn are the set curve shape coefficients, x is the set dimensionless axial parameter, and f(x) is the longitudinal coordinate of the reference curve.

7. The dedicated method for measuring waviness in critical areas of an aircraft RVSM as described in claim 6, characterized in that, When fitting the smooth surface to the measured surface, the maximum deviation of the point cloud fitting between the measured surface and the smooth surface is no more than 0.1 mm, and the fitting is complete.

8. The dedicated method for measuring waviness in critical areas of an aircraft RVSM as described in claim 6, characterized in that, Ripple analysis software was used to perform ripple analysis. During the analysis, the fitted data point cloud was filtered at a 2mm interval, and the filtered data point cloud was used to fit and form the reference surface of the measurement area. 48 horizontal profiles were taken on each side of the reference surface of the measurement area, with a horizontal profile interval of 20mm. The horizontal profiles near the center of the sensor passed through the center point of the sensor.

Images