A large-size skin contour detection method

Abstract

The present application belongs to the technical field of part shape detection, and particularly relates to a large-size skin shape detection method, comprising: establishing a to-be-detected skin numerical model, and generating a numerical model envelope prism; obtaining a seed point coordinate set of the bottom surface of the numerical model envelope prism; obtaining a surface intersection point coordinate set of the to-be-detected skin numerical model, and further obtaining a skin local barycentric matrix; obtaining a corresponding actual support torque matrix based on the skin local barycentric matrix; determining support point positions and support force sizes according to the local barycentric matrix and the actual support torque matrix, so as to unstress support the to-be-detected skin; and measuring the shape of the to-be-detected skin by using a skin shape detection device. The technical scheme analyzes the gravity distribution characteristics of the skin, carries out calculation and determines reasonable support point positions and support force sizes, so that the measurement process is carried out in an unstressed state, and the problem of easy deformation of the clamping during skin shape detection and large measurement error is solved.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of part shape detection, and particularly relates to a large-size skin shape detection method. BACKGROUND

[0002] The joint of the aircraft surface skin will affect the aerodynamic performance of the aircraft. With the increasing requirement for aerodynamic performance, large-size composite skin is gradually used to replace small-size skin to reduce the number of joints and obtain a relatively smooth aerodynamic surface. The composite skin has a large number of reinforcing ribs and other structures, so that the weight is uneven. The increase in the size of the skin reduces the overall stiffness and is prone to deformation. The existing detection method does not consider the error caused by the clamping deformation of the skin, so that the result obtained by detection is not accurate.

[0003] Therefore, in the prior art, the Chinese patent application with the publication number CN105157658A discloses a kind of aircraft skin shape detection device, the device designs with skin shape and is fitted with positioning and clamping assembly, and the shape is detected by clamping plate, and its defects are as follows: different positioning and clamping assemblies need to be designed and made for each different skin, which is not universal and has high cost;The weight of the reinforcing rib, the edge strip and other structures on the skin is not considered, and the clamping deformation error is caused.

[0004] In addition, in the prior art, the Chinese patent application with the publication number CN112525100A discloses a kind of detection skin shape tooling, the tooling designs variable number of suction disc structure, can detect the skin of different sizes with same curvature, but still cannot detect different curvature skins, and also does not consider the gravity distribution, which causes deformation error. SUMMARY

[0005] The purpose of the present application is to solve the problem of large measurement error caused by easy deformation of the skin during skin shape detection.

[0006] The technical scheme adopted to achieve the above purpose is as follows:

[0007] A large-size skin shape detection method, characterized in that it comprises the following steps:

[0008] S1, arbitrarily select a skin as the object to be detected, and establish a numerical model of the skin to be detected;

[0009] S2, according to the numerical model of the skin to be detected, generate a numerical model envelope prism according to the minimum envelope principle, and calculate the total weight of the skin ;

[0010] S3, mesh the bottom surface of the numerical model envelope prism, and obtain the bottom surface seed point coordinate set ;

[0011] S4, obtaining surface intersection point coordinate set of the to-be-tested skin model based on the digital model envelope prism and the seed point coordinate set ; ;

[0012] S5, obtaining skin local barycentric matrix based on the surface intersection point coordinate set ; ;

[0013] S6, obtaining corresponding actual support force matrix based on the skin local barycentric matrix ; ;

[0014] S7, determining support point position and support force size according to the local barycentric matrix and the actual support force matrix , and supporting the to-be-tested skin without stress according to the support point position and the support force size;

[0015] S8, measuring the shape of the to-be-tested skin by using a skin shape detection device.

[0016] Preferably, in the step S3, obtaining the bottom seed point coordinate set comprises the following steps:

[0017] S31, meshing the bottom surface of the digital model envelope prism in its plane at equal intervals ;

[0018] S32, generating seed points at the mesh intersection points; wherein the total number of transverse seed points is and the total number of longitudinal seed points is ;

[0019] S33, generating a seed point coordinate set in the digital model coordinate system; wherein the expression of the seed point coordinate set is as follows: ; ; ;

[0020] wherein, represents the X-axis coordinate value of the transverse th and longitudinal th seed point in the digital model coordinate system; represents the Y-axis coordinate value of the transverse th and longitudinal th seed point in the digital model coordinate system.

[0021] Preferably, in the step S31, the equal intervals 0.01 times the maximum width of the skin to be tested.

[0022] Preferably, in step S4, the surface intersection coordinate set is obtained The following steps are involved:

[0023] S4, combined with the digital-analog envelope prism and the seed point coordinate set , obtain the surface intersection coordinate set of the skin model to be tested , including the following steps:

[0024] S41, through the seed point, generates a series of straight lines parallel to the side edges of the digital model envelope prism ;in, Indicates the straight line, ;

[0025] S42, calculate straight line series The surface intersection points with the skin to be measured and its stiffeners and edges are obtained to obtain the surface intersection coordinate set ; Among them, the surface intersection coordinate set The expression is as follows:

[0026]

[0027] ;

[0028] in, Indicates the seed point The first on the straight line The X-axis coordinate value of the intersection point of each surface in the digital-analog coordinate system; Indicates the seed point The first on the straight line The Y-axis coordinate value of the intersection point of each surface in the digital-analog coordinate system; Indicates the seed point The first on the straight line The Z-axis coordinate value of the intersection point of each surface in the digital-analog coordinate system; Indicates the seed point The number of intersections between the straight line and the skin structure features to be measured.

[0029] Preferably, in step S5, the skin local center of gravity matrix is ​​obtained The following steps are involved:

[0030] S51, Design Intersection Matrix ;

[0031] S52, based on the intersection matrix Get the label matrix ;

[0032] S53, based on the marker matrix Get the support feasible area matrix ;

[0033] S54, combined with marker matrix and the feasible region matrix Get the local center of gravity matrix .

[0034] Preferably, in step S51, the intersection matrix ;in The expression is as follows:

[0035] ;

[0036] in, Represents the seed point The projection thickness of the digital model is 、 and Represents the seed points On the straight line The coordinate values ​​of each surface corner point in the X-axis, Y-axis and Z-axis in the digital coordinate system, 、 and Represents the seed points On the straight line The coordinate values ​​of each surface corner point in the X-axis, Y-axis and Z-axis in the digital coordinate system.

[0037] Preferably, in step S52, the marking matrix ;in The expression is as follows:

[0038] ;

[0039] in, Represents the label matrix Middle OK Elements of a column.

[0040] Preferably, in step S53, the support feasible area matrix is ​​obtained The following steps are involved:

[0041] S531, marking matrix Perform convolution operation to obtain matrix , that is, ;in, Representation matrix Middle Rank The elements of the column, where the convolution step is , is an element of the support feasible region matrix kernel;

[0042] S532, let the support feasible region matrix wherein expression is as follows:

[0043] ;

[0044] wherein, is an element of the support feasible region matrix in the i-th row and the j-th column.

[0045] Preferably, in the step S54, the local barycentric matrix ; wherein, expression is as follows:

[0046] ;

[0047] ;

[0048] wherein, is an element of the local barycentric matrix in the i-th row and the j-th column. is an X-axis coordinate of the matrix barycentric point in the i-th row and the j-th column; is a Y-axis coordinate of the matrix barycentric point in the i-th row and the j-th column; is an X-axis coordinate of the i-th horizontal and the j-th vertical seed point in the seed point coordinate set in the digital-analog coordinate system; is a Y-axis coordinate of the i-th horizontal and the j-th vertical seed point in the seed point coordinate set in the digital-analog coordinate system.

[0049] Preferably, in the step S6, the actual support force matrix comprises the following steps:

[0050] S61, performing convolution operation on the intersection matrix to obtain the local weight matrix , that is, ; wherein, ​​​​​​​​​​​​Representation matrix Middle Rank The elements of the column, where the convolution step is , The elements are all 1 Convolution kernel; , Represents the local weight matrix after convolution number of rows; , Represents the local weight matrix after convolution The number of columns;

[0051] S62, local weight matrix and the local centroid matrix Have the same matrix size, then let the actual support matrix , the expression for calculating the actual support force corresponding to the local center of gravity is as follows:

[0052] ;

[0053] in, Represents the local centroid matrix element The support force of the point where the coordinates are located.

[0054] Beneficial effects of the present invention:

[0055] This technical solution analyzes the gravity distribution characteristics of the skin to calculate and determine the appropriate support points and support forces. This allows the measurement process to be performed in a stress-free state, reducing measurement errors caused by gravity-induced skin deformation. Furthermore, this technical solution is not targeted at a specific skin shape; it can analyze and support skins of any shape, demonstrating its versatility. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 This is a preferred implementation flow chart of this technical solution;

[0057] Figure 2 Schematic diagram of the skin model to be tested;

[0058] Figure 3 Schematic diagram of the structure for generating digital-analog envelope prism;

[0059] Figure 4 Schematic diagram of the overall structure of the digital-analog envelope prism;

[0060] Figure 5 Schematic diagram of the bottom structure of the digital-analog envelope prism;

[0061] Figure 6 Schematic diagram of the grid structure of the bottom surface of the digital-analog envelope prism.

[0062] Fig.:

[0063] 1, skin model to be measured; 2, model envelope prism; 2.1, bottom surface of the envelope prism; 3, seed point. DETAILED DESCRIPTION

[0064] In order to make the purpose, technical scheme and advantages of the application clearer, the technical scheme in the application will be described clearly and completely below in combination with the drawings in the application. Obviously, the described embodiments are part of the embodiments of the application, rather than all the embodiments.

[0065] Therefore, the following detailed description of the application provided in the drawings is not intended to limit the scope of the claimed application, but only represents selected embodiments of the application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the application without creative labor are within the scope of protection of the application.

[0066] Embodiment 1

[0067] This embodiment discloses a large-size skin shape detection method. As a basic implementation of the technical scheme, the method comprises the following steps:

[0068] S1, an arbitrary selected skin is selected as the object to be measured, and a skin model to be measured is established.

[0069] S2, according to the skin model to be measured, a model envelope prism is generated according to the minimum envelope principle, and the total weight of the skin is calculated. .

[0070] S3, the bottom surface of the model envelope prism is meshed, and a set of seed point coordinates of the bottom surface is obtained. .

[0071] S4, in combination with the model envelope prism and the set of seed point coordinates , a set of surface intersection point coordinates of the skin model to be measured is obtained. .

[0072] S5, based on the set of surface intersection point coordinates , a local barycenter matrix of the skin is obtained. .

[0073] S6, based on the local barycenter matrix of the skin , a corresponding actual support force matrix is obtained. .

[0074] S7, according to the local barycenter matrix and the actual support force matrix , the support point position and the support force size are determined, and the skin to be measured is supported without stress according to the support point position and the support force size.

[0075] S8, measuring the shape of the to-be-tested skin by a skin shape detection device. The skin shape detection device includes a card board, a laser tracker, a three-dimensional scanner, etc.

[0076] Embodiment 2

[0077] The embodiment discloses a large-size skin shape detection method, which is a basic implementation scheme of the technical solution and comprises the following steps:

[0078] S1, selecting a skin as a to-be-tested object at random, and establishing a to-be-tested skin numerical model.

[0079] S2, generating a numerical model envelope prism according to the to-be-tested skin numerical model and the minimum envelope principle, and calculating the total weight of the skin .

[0080] S3, meshing the bottom surface of the numerical model envelope prism and obtaining a bottom surface seed point coordinate set . The obtaining of the bottom surface seed point coordinate set comprises the following steps:

[0081] S31, meshing the bottom surface of the numerical model envelope prism in its plane at equal intervals .

[0082] S32, generating seed points at the intersection points of the meshes; wherein the total number of transverse seed points is , and the total number of longitudinal seed points is .

[0083] S33, generating a seed point coordinate set in the numerical model coordinate system; wherein the expression of the seed point coordinate set is as follows: ; ; .

[0084] wherein represents the X-axis coordinate value of the transverse th and longitudinal th seed point in the numerical model coordinate system; represents the Y-axis coordinate value of the transverse th and longitudinal th seed point in the numerical model coordinate system.

[0085] S4, obtaining a surface intersection point coordinate set of the to-be-tested skin numerical model by combining the numerical model envelope prism and the seed point coordinate set .

[0086] S5, obtaining a skin local barycentric matrix based on the surface intersection point coordinate set . .

[0087] S6, based on the local barycentric matrix of the skin acquire the corresponding actual support matrix .

[0088] S7, according to the local barycentric matrix and the actual support matrix determine the support point position and the support force size, and support the to-be-measured skin without stress according to the support point position and the support force size.

[0089] S8, measure the shape of the to-be-measured skin by using a skin shape detection device.

[0090] Embodiment 3

[0091] The embodiment discloses a large-size skin shape detection method, as a basic implementation scheme of the technical solution, comprising the following steps:

[0092] S1, an arbitrary selected skin is selected as a to-be-measured object, and a to-be-measured skin numerical model is established.

[0093] S2, according to the to-be-measured skin numerical model, a numerical model envelope prism is generated according to the minimum envelope principle, and the total weight of the skin is calculated .

[0094] S3, the numerical model envelope prism bottom surface is meshed, and the bottom surface seed point coordinate set is acquired . Wherein, the bottom surface seed point coordinate set comprises the following steps:

[0095] S31, mesh the numerical model envelope prism bottom surface in its plane according to equal intervals ; further, the equal intervals are 0.01 times the maximum width of the to-be-measured skin.

[0096] S32, generate seed points at the grid intersection points; wherein the total number of transverse seed points is , and the total number of longitudinal seed points is .

[0097] S33, generate the seed point coordinate set in the numerical model coordinate system; wherein the expression of the seed point coordinate set is as follows: ; ; .

[0098] Wherein, represents the X-axis coordinate value of the transverse th, longitudinal th seed point in the numerical model coordinate system; Indicates horizontal , vertical The Y-axis coordinate value of a seed point in the digital-analog coordinate system.

[0099] S4, combined with the digital-analog envelope prism and the seed point coordinate set , obtain the surface intersection coordinate set of the skin model to be tested . Among them, get the surface intersection coordinate set The following steps are involved:

[0100] S41, through the seed point, generates a series of straight lines parallel to the side edges of the digital model envelope prism ;in, Indicates the straight line, .

[0101] S42, calculate straight line series The surface intersection points with the skin to be measured and its stiffeners and edges are obtained to obtain the surface intersection coordinate set ; Among them, the surface intersection coordinate set The expression is as follows:

[0102]

[0103] ;

[0104] in, Indicates the seed point The first on the straight line The X-axis coordinate value of the intersection point of each surface in the digital-analog coordinate system; Indicates the seed point The first on the straight line The Y-axis coordinate value of the intersection point of each surface in the digital-analog coordinate system; Indicates the seed point The first on the straight line The Z-axis coordinate value of the intersection point of each surface in the digital-analog coordinate system; Indicates the seed point The number of intersections between the straight line and the skin structure features to be measured.

[0105] S5, based on surface intersection coordinate sets Get the skin local center of gravity matrix .

[0106] S6, based on the skin local center of gravity matrix Get the corresponding actual support force matrix .

[0107] S7, according to the local center of gravity matrix and actual support force matrix Determine the support points and support force, and provide stress-free support for the skin to be tested based on the support points and support force.

[0108] S8, measuring the shape of the skin to be measured using a skin shape detection device.

[0109] Example 4

[0110] This embodiment discloses a large-scale skin shape detection method, which, as a basic implementation scheme of this technical solution, includes the following steps:

[0111] S1, randomly select a skin as the object to be tested and establish a digital model of the skin to be tested.

[0112] S2, based on the digital model of the skin to be tested, generate the digital model envelope prism according to the minimum envelope principle, and calculate the total weight of the skin at the same time .

[0113] S3, meshing the bottom surface of the digital model envelope prism and obtaining the bottom surface seed point coordinate set . And get the bottom seed point coordinate set The following steps are involved:

[0114] S31, the bottom surface of the digital-analog envelope prism is evenly spaced in its plane. Gridding; further, equal spacing 0.01 times the maximum width of the skin to be tested.

[0115] S32, generating seed points at the grid intersections; wherein the total number of horizontal seed points is , the total number of vertical seed points is .

[0116] S33, generate a seed point coordinate set in the digital model coordinate system ; Among them, the seed point coordinate set The expression is as follows: ; ; .

[0117] in, Indicates horizontal , vertical The X-axis coordinate value of each seed point in the digital-analog coordinate system; Indicates horizontal , vertical The Y-axis coordinate value of a seed point in the digital-analog coordinate system.

[0118] S4, combined with the digital-analog envelope prism and the seed point coordinate set , obtain a surface intersection point coordinate set of the to-be-tested skin model . The surface intersection point coordinate set is obtained by including the following steps:

[0119] S41, generating a series of straight lines passing through the seed point and parallel to the side edges of the envelope prism of the model ; wherein, represents the i-th straight line, .

[0120] S42, calculating the intersection points of the series of straight lines and the surface of the to-be-tested skin and its stiffeners and stringers, to obtain the surface intersection point coordinate set ; wherein, the expression of the surface intersection point coordinate set is as follows:

[0121]

[0122] ;

[0123] wherein, represents the X-axis coordinate value of the i-th surface intersection point on the straight line passing through the seed point in the model coordinate system; represents the Y-axis coordinate value of the i-th surface intersection point on the straight line passing through the seed point in the model coordinate system; represents the Z-axis coordinate value of the i-th surface intersection point on the straight line passing through the seed point in the model coordinate system; represents the number of intersection points of the straight line passing through the seed point and the structural features of the to-be-tested skin. S5, obtaining a skin local barycentric matrix based on the surface intersection point coordinate set . The skin local barycentric matrix is obtained by

[0124] including the following steps: S51, designing an intersection matrix .

[0125] S52, obtaining a marking matrix based on the intersection matrix .

[0126] S53, obtaining a support feasible region matrix based on the marking matrix .

[0127]

[0128] ​​​​​S54, combined with marker matrix and the feasible region matrix Get the local center of gravity matrix .

[0129] S6, based on the skin local center of gravity matrix Get the corresponding actual support force matrix .

[0130] S7, based on the local center of gravity matrix and actual support force matrix Determine the support points and support force, and provide stress-free support for the skin to be tested based on the support points and support force.

[0131] S8, measuring the shape of the skin to be measured using a skin shape detection device.

[0132] Example 5

[0133] This embodiment discloses a large-scale skin shape detection method, which, as a basic implementation scheme of this technical solution, includes the following steps:

[0134] S1, randomly select a skin as the object to be tested and establish a digital model of the skin to be tested.

[0135] S2, based on the digital model of the skin to be tested, generate the digital model envelope prism according to the minimum envelope principle, and calculate the total weight of the skin at the same time .

[0136] S3, meshing the bottom surface of the digital model envelope prism and obtaining the bottom surface seed point coordinate set . Among them, get the bottom seed point coordinate set The following steps are involved:

[0137] S31, the bottom surface of the digital-analog envelope prism is evenly spaced in its plane. Gridding; further, equal spacing 0.01 times the maximum width of the skin to be tested.

[0138] S32, generating seed points at the grid intersections; wherein the total number of horizontal seed points is , the total number of vertical seed points is .

[0139] S33, generate a seed point coordinate set in the digital model coordinate system ; Among them, the seed point coordinate set The expression is as follows: ; ; .

[0140] in, Indicates horizontal , vertical The X-axis coordinate value of each seed point in the digital-analog coordinate system; Indicates horizontal , vertical The Y-axis coordinate value of a seed point in the digital-analog coordinate system.

[0141] S4, combined with the digital-analog envelope prism and the seed point coordinate set , obtain the surface intersection coordinate set of the skin model to be tested . Among them, get the surface intersection coordinate set The following steps are involved:

[0142] S41, through the seed point, generates a series of straight lines parallel to the side edges of the digital model envelope prism ;in, Indicates the straight line, ;

[0143] S42, calculate straight line series The surface intersection points with the skin to be measured and its stiffeners and edges are obtained to obtain the surface intersection coordinate set ; Among them, the surface intersection coordinate set The expression is as follows:

[0144]

[0145] ;

[0146] in, Indicates the seed point The first on the straight line The X-axis coordinate value of the intersection point of each surface in the digital-analog coordinate system; Indicates the seed point The first on the straight line The Y-axis coordinate value of the intersection point of each surface in the digital-analog coordinate system; Indicates the seed point The first on the straight line The Z-axis coordinate value of the intersection point of each surface in the digital-analog coordinate system; Indicates the seed point The number of intersections between the straight line and the skin structure features to be measured.

[0147] S5, based on surface intersection coordinate sets Get the skin local center of gravity matrix . Among them, get the skin local center of gravity matrix The following steps are involved:

[0148] S51, Design Intersection Matrix Specifically, the intersection matrix ; wherein The expression of the seed point

[0149] ;

[0150] wherein, represents the number module projection thickness at the seed point , , and minute straight line on the represents the X-axis, Y-axis and Z-axis coordinate values of the first surface corner point on the straight line passing through the seed point , , , and respectively represent the X-axis, Y-axis and Z-axis coordinate values of the surface corner point on the straight line passing through the seed point minute straight line on the .

[0151] In addition, the expression of the seed point is to calculate the length of the intersection part of the straight line generated by the intersection of the seed point and the number module, which represents the number module projection thickness at the seed point, for the distribution of discrete weight.

[0152] S52, based on the intersection matrix obtain the mark matrix .

[0153] S53, based on the mark matrix obtain the support feasible region matrix .

[0154] S54, combined with the mark matrix and the feasible region matrix obtain the local barycenter matrix .

[0155] S6, based on the skin local barycenter matrix obtain the corresponding actual support force matrix .

[0156] S7, according to the local barycenter matrix and the actual support force matrix determine the support point position and the support force size, and support the measured skin without stress according to the support point position and the support force size.

[0157] S8, use the skin shape detection device to measure the shape of the measured skin.

[0158] Embodiment 6

[0159] The embodiment discloses a large-size skin shape detection method, as a basic implementation of the technical solution, comprising the following steps:

[0160] S1, an arbitrary selected skin is selected as a to-be-detected object, and a to-be-detected skin model is established.

[0161] S2, according to the to-be-detected skin model, a model envelope prism is generated according to the minimum envelope principle, and the total weight of the skin is calculated .

[0162] S3, the bottom surface of the model envelope prism is meshed, and a bottom surface seed point coordinate set is obtained . Wherein, the bottom surface seed point coordinate set is obtained by the following steps:

[0163] S31, the bottom surface of the model envelope prism is meshed in its plane according to an equal interval ; further, the equal interval is 0.01 times the maximum width of the to-be-detected skin.

[0164] S32, seed points are generated at the intersection points of the meshes; wherein the total number of transverse seed points is , and the total number of longitudinal seed points is .

[0165] S33, in the model coordinate system, a seed point coordinate set is generated; wherein the expression of the seed point coordinate set is as follows: ; ; .

[0166] Wherein, represents the X-axis coordinate value of the transverse th and longitudinal th seed point in the model coordinate system; represents the Y-axis coordinate value of the transverse th and longitudinal th seed point in the model coordinate system.

[0167] S4, combined with the model envelope prism and the seed point coordinate set , a surface intersection point coordinate set of the to-be-detected skin model is obtained. Wherein, the surface intersection point coordinate set is obtained by the following steps:

[0168] S41, a series of straight lines are generated through the seed points, and the directions of the straight lines are parallel to the side edges of the model envelope prism ; wherein, represents the first straight line, .

[0169] S42, calculate the straight line series and the surface intersection point coordinate set of the skin and its reinforcing rib and edge strip to be measured ; wherein the expression of the surface intersection point coordinate set is as follows:

[0170]

[0171] ;

[0172] wherein, represents the X-axis coordinate value of the first surface intersection point on the straight line passing through the seed point in the numerical model coordinate system; represents the Y-axis coordinate value of the first surface intersection point on the straight line passing through the seed point in the numerical model coordinate system; represents the Z-axis coordinate value of the first surface intersection point on the straight line passing through the seed point in the numerical model coordinate system; represents the number of intersection points of the straight line passing through the seed point and the skin structure feature to be measured.

[0173] S5, obtain the skin local barycentric matrix based on the surface intersection point coordinate set . Wherein, the skin local barycentric matrix obtaining method comprises the following steps:

[0174] S51, design the intersection matrix . Specifically, the intersection matrix ; wherein the expression of the intersection matrix

[0175] ;

[0176] wherein, represents the numerical model projection thickness at the seed point , , and minute straight line on the represents the X-axis, Y-axis and Z-axis coordinate values of the first surface corner point on the straight line passing through the seed point , , and Represents the seed points minute straight line on the The coordinate values ​​of each surface corner point in the X-axis, Y-axis and Z-axis in the digital coordinate system.

[0177] S52, based on the intersection matrix Get the label matrix Specifically, the label matrix ;in The expression is as follows:

[0178] ;

[0179] in, Represents the label matrix Middle OK Elements of a column.

[0180] Furthermore, the above The purpose of this expression is to build a label matrix , the size and shape of the matrix are the same as the intersection matrix Same, each element corresponds to the intersection matrix The zero element is 0 and the non-zero element is 1.

[0181] S53, based on the marker matrix Get the support feasible area matrix .

[0182] S54, combined with marker matrix and the feasible region matrix Get the local center of gravity matrix .

[0183] S6, based on the skin local center of gravity matrix Get the corresponding actual support force matrix .

[0184] S7, based on the local center of gravity matrix and actual support force matrix Determine the support points and support force, and provide stress-free support for the skin to be tested based on the support points and support force.

[0185] S8, measuring the shape of the skin to be measured using a skin shape detection device.

[0186] Example 7

[0187] This embodiment discloses a large-scale skin shape detection method, which, as a basic implementation scheme of this technical solution, includes the following steps:

[0188] S1, randomly select a skin as the object to be tested and establish a digital model of the skin to be tested.

[0189] S2, based on the digital model of the skin to be tested, generate the digital model envelope prism according to the minimum envelope principle, and calculate the total weight of the skin at the same time .

[0190] S3, meshing the bottom surface of the digital model envelope prism and obtaining the bottom surface seed point coordinate set . Among them, get the bottom seed point coordinate set The following steps are involved:

[0191] S31, the bottom surface of the digital-analog envelope prism is evenly spaced in its plane. Gridding; further, equal spacing 0.01 times the maximum width of the skin to be tested.

[0192] S32, generating seed points at the grid intersections; wherein the total number of horizontal seed points is , the total number of vertical seed points is .

[0193] S33, generate a seed point coordinate set in the digital model coordinate system ; Among them, the seed point coordinate set The expression is as follows: ; ; .

[0194] in, Indicates horizontal , vertical The X-axis coordinate value of each seed point in the digital-analog coordinate system; Indicates horizontal , vertical The Y-axis coordinate value of a seed point in the digital-analog coordinate system.

[0195] S4, combined with the digital-analog envelope prism and the seed point coordinate set , obtain the surface intersection coordinate set of the skin model to be tested . Among them, get the surface intersection coordinate set The following steps are involved:

[0196] S41, through the seed point, generates a series of straight lines parallel to the side edges of the digital model envelope prism ;in, Indicates the straight line, .

[0197] S42, calculate straight line series The surface intersection point coordinate set is obtained by intersecting the surface of the to-be-tested skin and the stringers and the beads thereof ; wherein, the expression of the surface intersection point coordinate set is as follows:

[0198]

[0199] ;

[0200] wherein, represents the X-axis coordinate value of the i-th surface intersection point on the straight line passing through the seed point in the numerical model coordinate system; represents the Y-axis coordinate value of the i-th surface intersection point on the straight line passing through the seed point in the numerical model coordinate system; represents the Z-axis coordinate value of the i-th surface intersection point on the straight line passing through the seed point in the numerical model coordinate system; represents the number of intersection points of the straight line passing through the seed point and the structure feature of the to-be-tested skin.

[0201] S5, obtaining a skin local barycentric matrix based on the surface intersection point coordinate set . Wherein, obtaining the skin local barycentric matrix includes the following steps:

[0202] S51, designing an intersection matrix . Specifically, the intersection matrix ; wherein the expression of the intersection matrix is as follows:

[0203] ;

[0204] wherein, represents the numerical model projection thickness at the seed point , , and minute straight line on the respectively represent the X-axis, Y-axis and Z-axis coordinate values of the i-th surface corner point on the straight line passing through the seed point in the numerical model coordinate system, , and respectively represent the X-axis, Y-axis and Z-axis coordinate values of the i-th surface corner point on the straight line passing through the seed point minute straight line on the in the numerical model coordinate system.​​​

[0205] S52, based on the intersection matrix Get the label matrix Specifically, the label matrix ;in The expression is as follows:

[0206] ;

[0207] in, Represents the label matrix Middle OK Elements of a column.

[0208] S53, based on the marker matrix Get the support feasible area matrix Specifically, obtain the support feasible area matrix The following steps are involved:

[0209] S531, marking matrix Perform convolution operation to obtain matrix , that is, ;in, Representation matrix Middle Rank The elements of the column, where the convolution step is , The elements are all 1 Convolution kernel. Specifically, the matrix is the label matrix The feature matrix obtained after the convolution operation plays a role in reducing the label matrix role.

[0210] S532, let the support feasible area matrix ,in The expression is as follows:

[0211] ;

[0212] in, Represents the support feasible area matrix Middle Rank Elements of a column.

[0213] Support feasible area matrix With the matrix The same number of rows and columns, used to label the matrix Element size, matrix The element is equal to The square value of the corresponding support feasible area matrix The element is 1, indicating matrix calculation When all elements of the convolution calculation are non-zero values, the subsequent formula uses this to determine that the parts in this area are points that should be supported, that is, support is feasible.

[0214] S54, combined with marker matrix and the feasible region matrix Get the local center of gravity matrix .

[0215] S6, based on the skin local center of gravity matrix Get the corresponding actual support force matrix .

[0216] S7, based on the local center of gravity matrix and actual support force matrix Determine the support points and support force, and provide stress-free support for the skin to be tested based on the support points and support force.

[0217] S8, measuring the shape of the skin to be measured using a skin shape detection device.

[0218] Example 8

[0219] This embodiment discloses a large-scale skin shape detection method, which, as a basic implementation scheme of this technical solution, includes the following steps:

[0220] S1, randomly select a skin as the object to be tested and establish a digital model of the skin to be tested.

[0221] S2, based on the digital model of the skin to be tested, generate the digital model envelope prism according to the minimum envelope principle, and calculate the total weight of the skin at the same time .

[0222] S3, meshing the bottom surface of the digital model envelope prism and obtaining the bottom surface seed point coordinate set . Among them, get the bottom seed point coordinate set The following steps are involved:

[0223] S31, the bottom surface of the digital-analog envelope prism is evenly spaced in its plane. Gridding; further, equal spacing 0.01 times the maximum width of the skin to be tested.

[0224] S32, generating seed points at the grid intersections; wherein the total number of horizontal seed points is , the total number of vertical seed points is .

[0225] S33, generate a seed point coordinate set in the digital model coordinate system ; Among them, the seed point coordinate set The expression is as follows: ; ; .

[0226] in, Indicates horizontal , vertical The X-axis coordinate value of each seed point in the digital-analog coordinate system; Indicates horizontal , vertical The Y-axis coordinate value of a seed point in the digital-analog coordinate system.

[0227] S4, combined with the digital-analog envelope prism and the seed point coordinate set , obtain the surface intersection coordinate set of the skin model to be tested . Among them, get the surface intersection coordinate set The following steps are involved:

[0228] S41, through the seed point, generates a series of straight lines parallel to the side edges of the digital model envelope prism ;in, Indicates the straight line, .

[0229] S42, calculate straight line series The surface intersection points with the skin to be measured and its stiffeners and edges are obtained to obtain the surface intersection coordinate set ; Among them, the surface intersection coordinate set The expression is as follows:

[0230]

[0231] ;

[0232] in, Indicates the seed point The first on the straight line The X-axis coordinate value of the intersection point of each surface in the digital-analog coordinate system; Indicates the seed point The first on the straight line The Y-axis coordinate value of the intersection point of each surface in the digital-analog coordinate system; Indicates the seed point The first on the straight line The Z-axis coordinate value of the intersection point of each surface in the digital-analog coordinate system; Indicates the seed point The number of intersections between the straight line and the skin structure features to be measured.

[0233] S5, based on surface intersection coordinate sets obtaining a skin local barycenter matrix . In the method, the skin local barycenter matrix is obtained by The method comprises the following steps:

[0234] S51, designing an intersection matrix . Specifically, the intersection matrix is designed by ; wherein The expression of the intersection matrix is as follows:

[0235] ;

[0236] wherein, represents the number module projection thickness at the seed point , , and ​ respectively represent the coordinate values of the first surface corner point on the X-axis direction, the Y-axis direction and the Z-axis direction in the number module coordinate system of the straight line passing through the seed point , , and respectively represent the coordinate values of the first surface corner point on the X-axis direction, the Y-axis direction and the Z-axis direction in the number module coordinate system of the straight line passing through the seed point ​ .

[0237] S52, obtaining a marking matrix based on the intersection matrix . Specifically, the marking matrix is obtained by ; wherein The expression of the marking matrix is as follows:

[0238] ; wherein,

[0239] represents the element in the marking matrix .

[0240] S53, obtaining a support feasible region matrix based on the marking matrix . Specifically, the support feasible region matrix is obtained by comprising the following steps: S531, performing convolution operation on the marking matrix

[0241] to obtain a matrix , that is, ; wherein, represents the element in the matrix . ​​​​​Row , where the convolution step is , , and is a convolution kernel with elements

[0242] S532, the support feasible region matrix is obtained, where The expression of

[0243] ;

[0244] where, represents the element in the th row and the th column of the support feasible region matrix .

[0245] S54, the local barycenter matrix is obtained by combining the label matrix and the feasible region matrix . Wherein, the local barycenter matrix ; Wherein, The expression of

[0246] ;

[0247] ;

[0248] where, represents the matrix barycenter point in the th row and the th column of the local barycenter matrix ; represents the X-axis coordinate of the matrix barycenter point in the th row and the th column; represents the Y-axis coordinate of the matrix barycenter point in the th row and the th column; represents the X-axis coordinate of the th horizontal and the th vertical seed point in the seed point coordinate set in the digital-analog coordinate system; represents the Y-axis coordinate of the th horizontal and the th vertical seed point in the seed point coordinate set in the digital-analog coordinate system.

[0249] S6, the corresponding actual support force matrix is obtained based on the skin local barycenter matrix .

[0250] S7, determining the support point position and the support force size according to the local barycenter matrix and the actual support force matrix S7, determining the support point position and the support force size according to the local barycenter matrix and the actual support force matrix

[0251] S8, measuring the shape of the to-be-tested skin by using a skin shape detection device.

[0252] Embodiment 9

[0253] The embodiment discloses a large-size skin shape detection method, and as a basic implementation scheme of the technical solution, comprises the following steps:

[0254] S1, selecting a skin as a to-be-tested object at random, and establishing a to-be-tested skin numerical model.

[0255] S2, generating a numerical model envelope prism according to the to-be-tested skin numerical model and the minimum envelope principle, and calculating the total weight of the skin .

[0256] S3, meshing the bottom surface of the numerical model envelope prism and obtaining a bottom surface seed point coordinate set . Wherein, the bottom surface seed point coordinate set comprises the following steps:

[0257] S31, meshing the bottom surface of the numerical model envelope prism in its plane at an equal interval ; further, the equal interval is 0.01 times the maximum width of the to-be-tested skin.

[0258] S32, generating seed points at the intersection points of the meshes; wherein the total number of transverse seed points is , and the total number of longitudinal seed points is .

[0259] S33, generating a seed point coordinate set in the numerical model coordinate system; wherein the expression of the seed point coordinate set is as follows: ; ; .

[0260] Wherein, represents the X-axis coordinate value of the transverse th and longitudinal th seed point in the numerical model coordinate system; represents the Y-axis coordinate value of the transverse th and longitudinal th seed point in the numerical model coordinate system.

[0261] ​S4, obtaining the intersection point coordinate set of the surface of the skin model to be measured based on the digital envelope prism and the seed point coordinate set The intersection point coordinate set of the surface is obtained by the following steps: The intersection point coordinate set of the surface is obtained by the following steps:

[0262] S41, generating a series of straight lines passing through the seed point and parallel to the side edges of the digital envelope prism The i-th straight line is represented as:

[0263] S42, calculating the intersection points of the series of straight lines and the surface of the skin model to be measured and the stiffeners and the stringers thereof, to obtain the intersection point coordinate set of the surface The expression of the intersection point coordinate set of the surface is as follows:

[0264]

[0265] ;

[0266] The expression of the intersection point coordinate set of the surface is as follows: The X-axis coordinate value of the i-th intersection point on the straight line passing through the seed point in the digital envelope coordinate system is represented as: The Y-axis coordinate value of the i-th intersection point on the straight line passing through the seed point in the digital envelope coordinate system is represented as: The Z-axis coordinate value of the i-th intersection point on the straight line passing through the seed point in the digital envelope coordinate system is represented as: The number of intersection points of the straight line passing through the seed point and the structural features of the skin model to be measured is represented as: S5, obtaining the local barycentric matrix of the skin based on the intersection point coordinate set of the surface The local barycentric matrix of the skin is obtained by the following steps:

[0267] The local barycentric matrix of the skin is obtained by the following steps: S51, designing the intersection matrix The expression of the intersection matrix is as follows:

[0268] The expression of the intersection matrix is as follows: The expression of the intersection matrix is as follows:

[0269] ; The expression of the intersection matrix is as follows:

[0270] The seed point is represented as: The seed point is represented as:​​​​​​​​​​​​​ The projection thickness of the digital model, , and ​ The coordinates of the i-th surface corner point on the X-axis, Y-axis and Z-axis of the digital model coordinate system, , and The coordinates of the i-th surface corner point on the X-axis, Y-axis and Z-axis of the digital model coordinate system. ​ The coordinates of the i-th surface corner point on the X-axis, Y-axis and Z-axis of the digital model coordinate system.

[0271] S52, obtaining a marking matrix based on the intersection matrix . Specifically, the marking matrix ; wherein The expression of is as follows:

[0272] ;

[0273] wherein, represents the element in the i-th row and j-th column of the marking matrix . S53, obtaining a support feasible region matrix based on the marking matrix . Specifically, obtaining the support feasible region matrix

[0274] includes the following steps: S531, performing convolution operation on the marking matrix to obtain a matrix , that is,

[0275] ; wherein, represents the element in the i-th row and j-th column of the matrix , wherein the convolution step is , and is a convolution kernel with all elements being 1. S532, setting the support feasible region matrix , wherein The expression of is as follows:

[0276] ;

[0277] ;

[0278] wherein, represents the element in the i-th row and j-th column of the support feasible region matrix​​​​​​​ In the first In the first In the first

[0279] S54, combined with the label matrix and the feasible region matrix get the local barycenter matrix . Wherein, the local barycenter matrix ; Wherein, The expression is as follows:

[0280] ;

[0281] ;

[0282] Wherein, indicates the matrix barycenter point in the first In the first In the first In the first row and column of the local barycenter matrix ; indicates the X-axis coordinate of the matrix barycenter point in the first In the first In the first In the first row and column; indicates the X-axis coordinate of the seed point in the seed point coordinate set in the horizontal direction and the vertical direction ; indicates the Y-axis coordinate of the seed point in the seed point coordinate set in the horizontal direction and the vertical direction .

[0283] S6, based on the skin local barycenter matrix get the corresponding actual support force matrix . Get the actual support force matrix includes the following steps:

[0284] S61, the intersection matrix Convolution operation is performed to obtain the local weight matrix , that is, ; Wherein, indicates the element in the first In the first In the first In the first row and column of the matrix , wherein the convolution step is , ,​​​​​​​​​​​​​​ the number of rows of the local weight matrix after convolution , , the number of columns of the local weight matrix after convolution .

[0285] S62, the local weight matrix has the same matrix size as the local barycenter matrix , the actual support force matrix is set as

[0286] ;

[0287] wherein, the support force of the point where the local barycenter matrix element is located.

[0288] S7, the support point and the support force size are determined according to the local barycenter matrix and the actual support force matrix , and the measured skin is unstressed supported according to the support point and the support force size.

[0289] S8, the shape of the measured skin is measured by using a skin shape detection device.

Claims

1. A large-scale skin shape detection method, characterized in that: The following steps are involved: S1, randomly select a skin as the object to be tested and establish a digital model of the skin to be tested; S2, based on the digital model of the skin to be tested, generate the digital model envelope prism according to the minimum envelope principle, and calculate the total weight of the skin at the same time ; S3, meshing the bottom surface of the digital model envelope prism and obtaining the bottom surface seed point coordinate set , including the following steps: S31, the bottom surface of the digital-analog envelope prism is evenly spaced in its plane. Gridding S32, generating seed points at the grid intersections; wherein the total number of horizontal seed points is , the total number of vertical seed points is ; S33, generate a seed point coordinate set in the digital model coordinate system ; Among them, the seed point coordinate set The expression is as follows: ; ; ; in, Indicates horizontal , vertical The X-axis coordinate value of each seed point in the digital-analog coordinate system; Indicates horizontal , vertical The Y-axis coordinate value of each seed point in the digital-analog coordinate system; S4, combined with the digital-analog envelope prism and the seed point coordinate set , obtain the surface intersection coordinate set of the skin model to be tested , including the following steps: S41, through the seed point, generates a series of straight lines parallel to the side edges of the digital model envelope prism ;in, Indicates the straight line, ; S42, calculate straight line series The surface intersection points with the skin to be measured and its stiffeners and edges are obtained to obtain the surface intersection coordinate set ; Among them, the surface intersection coordinate set The expression is as follows: ； in, Indicates the seed point The first on the straight line The X-axis coordinate value of the intersection point of each surface in the digital-analog coordinate system; Indicates the seed point The first on the straight line The Y-axis coordinate value of the intersection point of each surface in the digital-analog coordinate system; Indicates the seed point The first on the straight line The Z-axis coordinate value of the intersection point of each surface in the digital-analog coordinate system; Indicates the seed point The number of intersections between the straight line and the structural features of the skin to be measured; S5, based on surface intersection coordinate sets Get the skin local center of gravity matrix , including the following steps: S51, Design Intersection Matrix ; S52, based on the intersection matrix Get the label matrix ; S53, based on the marker matrix Get the support feasible area matrix ; S54, combined with marker matrix and the feasible region matrix Get the local center of gravity matrix ; S6, based on the skin local center of gravity matrix Get the corresponding actual support force matrix ; S7, based on the local center of gravity matrix and actual support force matrix Determine the support points and support force, and provide stress-free support for the skin to be tested based on the support points and support force; S8, measuring the shape of the skin to be measured using a skin shape detection device.

2. A large-scale skin shape detection method as claimed in claim 1, characterized in that: In step S51, the intersection matrix ;in The expression is as follows: ； in, Represents the seed point The projection thickness of the digital model is 、 and Represents the seed points On the straight line The coordinate values ​​of each surface corner point in the X-axis, Y-axis and Z-axis in the digital coordinate system, 、 and Represents the seed points On the straight line The coordinate values ​​of each surface corner point in the X-axis, Y-axis and Z-axis in the digital coordinate system.

3. A large-scale skin shape detection method as claimed in claim 2, characterized in that: In step S52, the marking matrix ;in The expression is as follows: ； in, Represents the label matrix Middle OK Elements of a column.

4. A large-scale skin shape detection method as claimed in claim 3, characterized in that: In step S53, the support feasible area matrix is ​​obtained. The following steps are involved: S531, marking matrix Perform convolution operation to obtain matrix , that is, ;in, Representation matrix Middle Rank The elements of the column, where the convolution step is , The elements are all 1 Convolution kernel; S532, let the support feasible area matrix ,in The expression is as follows: ； in, Represents the support feasible area matrix Middle Rank Elements of a column.

5. A large-scale skin shape detection method as claimed in claim 4, characterized in that: In step S54, the local center of gravity matrix ;in, The expression is as follows: ； ； in, is the local barycenter matrix element, indicating the local barycenter matrix Middle Rank The matrix centroid of the column; Indicates the Rank The X-axis coordinate of the centroid of the column matrix; Indicates the Rank The Y-axis coordinate of the center of gravity of the column matrix; Represents the seed point coordinate set Middle horizontal , vertical The X-axis coordinate of each seed point in the digital-analog coordinate system; Represents the seed point coordinate set Horizontal , vertical The Y-axis coordinates of the seed points in the digital-analog coordinate system; equally spaced 0.01 times the maximum width of the skin to be tested.

6. A large-scale skin shape detection method as claimed in claim 5, characterized in that: In step S6, the actual support force matrix is ​​obtained. The following steps are involved: S61, intersection matrix Perform convolution operation to obtain the local weight matrix , that is, ;in, Representation matrix Middle Rank The elements of the column, where the convolution step is , The elements are all 1 Convolution kernel; , Represents the local weight matrix after convolution number of rows; , Represents the local weight matrix after convolution The number of columns; S62, local weight matrix and the local centroid matrix Have the same matrix size, then let the actual support matrix , the expression for calculating the actual support force corresponding to the local center of gravity is as follows: ； in, Represents the local centroid matrix element The support force of the point where the coordinates are located.

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