CN115600309B - Method and device for designing mold surface of automobile windshield based on curved surface reconstruction - Google Patents
Method and device for designing mold surface of automobile windshield based on curved surface reconstruction Download PDFInfo
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Abstract
The invention provides a design method and a device for a mold surface of an automobile windshield based on curved surface reconstruction, wherein multiple groups of glass surfaces and mold surfaces are obtained from a historical design scheme, discrete points of each glass surface and geometric characteristic data of the discrete points are extracted, and distances from each discrete point to the corresponding mold surface are extracted. And establishing a mapping model according to the geometric characteristic data of the discrete points and the distances from the discrete points to the corresponding mold surfaces. And extracting discrete points of the required glass profile and geometric characteristic data of the discrete points. And predicting the distance from each discrete point on the required glass profile to the required mold profile according to the geometric feature data of the discrete points of the required glass profile and the mapping model. And acquiring coordinates of the discrete points of the required mold surface according to the geometric characteristic data of the discrete points and the distance between the discrete points and the required mold surface. And acquiring a plurality of reconstruction lines by utilizing coordinates of the discrete points, and establishing the molded surface of the required mold by adopting a geometric modeling engine based on the plurality of reconstruction lines.
Description
Technical Field
The invention belongs to the technical field of glass mold design, and particularly relates to an automobile windshield mold profile design method and device based on curved surface reconstruction.
Background
The production process of the automobile windshield comprises the following steps: firstly, the glass raw sheet is conveyed to a forming chamber after cutting, edging, cleaning, drying and heating. Then, the glass mold is sucked onto the suction surface of the suction mold machine in the molding chamber, and the glass mold below is held as the suction mold surface descends. When the glass raw sheet is heated to reach a softening point, the glass raw sheet is downwards bent and attached to the glass die under the influence of gravity, so that the set profile curvature of the glass die is achieved. Finally, the glass raw sheet formed by hot bending is cooled and subjected to subsequent steps to form the automobile windshield meeting production requirements.
Among them, the glass mold plays a very important role in molding of a glass raw sheet. However, since the glass sheet is subject to springback during the molding process, the geometric characteristics of the glass mold profile are not exactly the same as the design curve of the automobile windshield.
At present, the design of the mold surface of the automobile windshield adopts a trial-and-error method, and the general flow is as follows: (1) determining a desired glass profile; (2) preliminarily designing the molding surface of the glass mold according to the molding surface of the glass; (3) trial-manufacturing a glass finished product according to the molded surface of the glass mold; (4) Detecting deviation between the finished product of the trial-produced glass and the required glass profile; (5) And (3) if the deviation is not qualified, returning to the step (2) to adjust the molding surface of the glass mold. However, trial-and-error requires repeated corrections to the glass mold profile, which is not only long in design cycle, heavy in effort, but also costly, resulting in lower efficiency in the production of automotive windshields.
With the continued development of the automotive industry, automotive windshields are increasingly being patterned, and the design of glass mold profiles is facing new demands and challenges. Trial and error has been difficult to meet the development trend of the automobile windshield manufacturing industry due to its high design cost and long design cycle.
Disclosure of Invention
The embodiment of the invention provides a method and a device for designing the mold surface of an automobile windshield based on curved surface reconstruction, which are used for solving the problems of higher design cost and longer design period in the prior art.
One aspect of the present invention provides a method for designing a mold surface of an automotive windshield based on curved surface reconstruction, which is applied to generating a required mold surface according to a required glass surface, and includes:
obtaining multiple groups of molded surfaces from historical design schemes, wherein each group of molded surfaces comprises a glass molded surface and a corresponding mold molded surface;
discrete points of each glass molded surface are extracted respectively, and geometric characteristic data of each discrete point are obtained;
obtaining the distance from each discrete point to the corresponding mold surface;
establishing a mapping model according to the geometric feature data of all the discrete points and the distances from the discrete points to the corresponding mold surfaces, wherein the input variable of the mapping model is the geometric feature of the discrete points, and the output variable is the distance from the discrete points to the corresponding mold surfaces;
Discrete points of the required glass molded surface are extracted, and geometric feature data of each discrete point are obtained;
according to the geometric feature data of discrete points of the required glass molded surface and the mapping model, predicting the distance from each discrete point on the required glass molded surface to the required mold molded surface;
obtaining coordinates of discrete points of the required mold surface according to geometric characteristic data of the discrete points of the required glass surface and the predicted distance from the discrete points of the required glass surface to the required mold surface;
acquiring a plurality of reconstruction lines by utilizing coordinates of discrete points of the required mold surface, wherein the average distance between each reconstruction line and the corresponding discrete point of the required mold surface is the smallest;
and based on the plurality of reconstruction lines, establishing the profile of the required die by adopting a geometric modeling engine.
Optionally, the extracting discrete points of each glass profile and obtaining geometric feature data of each discrete point respectively includes:
for each glass profile, discrete points are extracted as follows:
determining a minimum bounding box of the glass profile;
establishing a three-dimensional coordinate system of the glass molded surface by taking the central point of the minimum bounding box as an origin, wherein the x-axis of the coordinate system is parallel to the longest side of the minimum bounding box, and the z-axis of the coordinate system is parallel to the shortest side of the minimum bounding box;
Respectively taking the longest two boundary lines on the glass molded surface as an upper boundary line and a lower boundary line of the glass molded surface;
dividing the upper boundary line and the lower boundary line by p+1 equally, and connecting corresponding equally dividing points on the upper boundary line and the lower boundary line to obtain p equally dividing lines;
obtaining p planes which are perpendicular to the XOY plane and pass through any one of p bisectors, wherein the planes are in one-to-one correspondence with the bisectors;
obtaining p intersecting lines intersecting p planes on the glass molded surface;
q+1 aliquoting is carried out on each intersecting line; sequentially connecting the equal division points of the corresponding sequences on the p intersecting lines to obtain q connecting lines; the intersection points of the p intersecting lines and the q connecting lines are discrete points of the glass profile.
Optionally, the extracting discrete points of each glass profile, and obtaining geometric feature data of each discrete point, further includes:
(1) Acquiring the coordinates of each discrete point under a coordinate system corresponding to the glass molded surface;
(2) For each discrete point, a normal vector N is obtained as follows:
obtaining a tangent vector S with discrete points parallel to the x-axis x And a tangent vector S of the discrete point parallel to the y-axis y ；
The normal vector N is obtained by tangential vector cross multiplication: n=s x ×S y ；
(3) For each discrete point, the average curvature H is obtained as follows:
wherein k is 1 Is the maximum radius of curvature through the discrete points; k (k) 2 Is the minimum radius of curvature through the discrete points;
(4) For each discrete point, a gaussian curvature K is obtained as follows:
K＝k 1 *k 2
wherein k is 1 Is the maximum radius of curvature through the discrete points; k (k) 2 Is the minimum radius of curvature through the discrete points;
(5) For each discrete point, arch height AH is obtained according to the following method;
the camber is the distance from the discrete point to the corresponding bisector:
AH＝Dist(P,l i ),P∈l' i ,i＝1,2,…p
wherein the discrete point P is at the intersection line l' i Upper, l i Is equal to l' i Corresponding bisectors.
Optionally, the obtaining the distance from each discrete point to the corresponding mold surface includes:
and respectively acquiring the distance from each discrete point on each glass molded surface to the corresponding mold molded surface in the z-axis direction for each glass molded surface.
Optionally, the establishing a mapping model according to the geometric feature data of all the discrete points and the distances from the discrete points to the corresponding mold surfaces includes:
preprocessing the coordinates of all the discrete points by adopting a MinMax (maximum minimum) normalization mode;
preprocessing normal vectors, average curvatures, gaussian curvatures and camber of all discrete points by adopting a Robust (Robust Normalization ) normalization mode;
Constructing a data set by utilizing the preprocessed geometric feature data of the discrete points and the distances from the discrete points to the corresponding mold surfaces in the z-axis direction, wherein the coordinates, normal vectors, average curvature, gaussian curvature and camber of the discrete points are used as input variables of the data set, and the distances from the discrete points to the corresponding mold surfaces in the z-axis direction are used as output variables of the data set;
a mapping model between the input variable and the output variable is obtained using all the data in the dataset.
Optionally, the preprocessing is performed on the coordinates of all the discrete points in a MinMax normalization mode, including:
the coordinates of each discrete point are preprocessed according to the following method:
wherein f_max is the maximum value of all the discrete point coordinates; f_min is the minimum value in all the discrete point coordinates, and f is the original discrete point coordinate; f' is the preprocessed discrete point coordinates.
Optionally, the preprocessing of the normal vector, the average curvature, the gaussian curvature and the camber of all the discrete points by adopting a Robust normalization mode comprises the following steps:
the normal vector, average curvature, gaussian curvature and camber of each discrete point are all pre-processed as follows:
wherein f is an original geometric feature data value, and the geometric feature data value is a data value of one geometric feature of normal vector, average curvature, gaussian curvature and camber of the discrete points; f' is the preprocessed geometrical characteristic data value corresponding to f; f_mean is the median of the geometric feature data values corresponding to f of all the discrete points on the glass molded surface to which the discrete points belong; IQR is the interval length between the 1 st quartile and the 3 rd quartile in the geometric feature data values corresponding to f and all discrete points on the glass profile to which the discrete points belong.
Optionally, the establishing a mapping model according to the geometric feature data of all the discrete points and the distances from the discrete points to the corresponding mold surfaces includes:
any one of all the glass molded surfaces is selected as a test glass molded surface, and the rest glass molded surfaces are all used as training glass molded surfaces;
constructing a test data set by utilizing the geometric characteristic data of the discrete points after the pretreatment of the test glass molded surface and the distances from the discrete points on the test glass molded surface to the corresponding mold molded surface in the z-axis direction, wherein the coordinates, normal vectors, average curvature, gaussian curvature and camber of the discrete points are used as input variables, and the distances from the discrete points to the corresponding mold molded surface in the z-axis direction are used as output variables;
constructing a training data set by utilizing the geometric characteristic data of the discrete points after the pretreatment of the training glass molded surface and the distances from the discrete points on the training glass molded surface to the corresponding mold molded surface in the z-axis direction, wherein the coordinates, normal vectors, average curvature, gaussian curvature and camber of the discrete points are used as input variables, and the distances from the discrete points to the corresponding mold molded surface in the z-axis direction are used as output variables;
and establishing a regression model between geometric feature data of discrete points of the glass molded surface and distances between the discrete points and the corresponding molded surface of the mold in the z-axis direction by adopting a random forest training algorithm according to the training data set and the testing data set.
Optionally, the extracting discrete points of the required glass profile and acquiring geometric feature data of each discrete point include:
determining a minimum bounding box of a required glass profile;
establishing a three-dimensional coordinate system of the required glass molded surface by taking the central point of the minimum bounding box as an origin, wherein the x-axis of the coordinate system is parallel to the longest side of the minimum bounding box, and the z-axis of the coordinate system is parallel to the shortest side of the minimum bounding box;
respectively taking the longest two boundary lines on the required glass profile as an upper boundary line and a lower boundary line of the required glass profile;
dividing the upper boundary line and the lower boundary line by p+1 equally, and connecting corresponding equally dividing points on the upper boundary line and the lower boundary line to obtain p equally dividing lines;
obtaining p planes which are perpendicular to the XOY plane and pass through any one of p bisectors, wherein the planes are in one-to-one correspondence with the bisectors;
obtaining p intersecting lines intersecting p planes on the required glass profile;
q+1 aliquoting is carried out on each intersecting line; sequentially connecting the equal division points of the corresponding sequences on the p intersecting lines to obtain q connecting lines; the intersection points of the p intersecting lines and the q connecting lines are discrete points of the required glass profile.
Optionally, the predicting, according to the geometric feature data of discrete points of the required glass profile and the mapping model, a distance from each discrete point on the required glass profile to the required mold profile includes:
Preprocessing the coordinates of all discrete points on the required glass molded surface in a MinMax normalization mode;
preprocessing normal vectors, average curvatures, gaussian curvatures and camber of all discrete points on a required glass molded surface in a Robust normalization mode;
substituting the geometric feature data of all the discrete points on the required glass molded surface after pretreatment into a regression model, and calculating to obtain a predicted value of the distance from each discrete point on the required glass molded surface to the required mold molded surface in the z-axis direction;
determining whether there are discrete points on the desired glass profile having a plurality of predicted values,
if so, the maximum value in the plurality of predicted values is taken as the final predicted value of the corresponding discrete point.
Optionally, the obtaining the coordinates of the discrete points of the required mold surface according to the geometric feature data of the discrete points of the required glass mold surface and the predicted distance from the discrete points of the required glass mold surface to the required mold surface includes:
the coordinates of each discrete point of the desired mold profile are obtained as follows:
x′ i ＝x i
y′ i ＝y i
z′ i ＝z i +d i
wherein: (x' i ,y' i ,z' i ) Coordinates of discrete points of the required mold surface; (x) i ,y i ,z i ) Coordinates of corresponding discrete points on the required glass profile; d, d i The distance in the z-axis direction from the corresponding discrete point on the predicted desired glass profile to the desired mold profile.
Optionally, the obtaining a plurality of reconstruction lines by using coordinates of discrete points of the molding surface of the demand mold includes:
constructing a surface to be reconstructed of the demand die by adopting a geometric modeling engine according to the coordinates of each discrete point of the demand die surface;
selecting an optimized area on the profile to be reconstructed, wherein the optimized area does not comprise the edge of the profile to be reconstructed;
acquiring a projection area of the optimized area on a required glass molded surface;
dividing a connecting line obtained when the discrete points of the required glass profile are extracted into an optimizing line and an edge line according to the projection area, wherein the optimizing line is a part of the connecting line positioned in the projection area, and the edge line is a part of the connecting line positioned outside the projection area;
for each optimization line in the projection area, determining a corresponding reconstruction line R according to the following steps:
obtaining the highest point x on the optimization line mid The highest point is the point with the maximum value of the optimization line in the z-axis direction; set the highest point x mid The distance from the corresponding reconstruction line R in the z-axis direction is d mid ；
At the highest point x mid Centered at the highest point x on the optimization line mid N position points x are uniformly arranged on two sides of the frame respectively, and the position points x are as follows in sequence: x is x left_1 ，x left_2 ，…，x left_n ，x right_1 ，x right_2 ，…，x right_n The method comprises the steps of carrying out a first treatment on the surface of the Let the distance between the position point x and the reconstruction line R in the z-axis direction be d in turn left_1 ，d left_2 ，…，d left_n ，d right_1 ，d right_2 ，…，d right_n ；
Will d left_1 ，d left_2 ，…，d left_n ，d right_1 ，d right_2 ，…，d right_n As a design variable;
the following constraint conditions are set for the values of the design variables:
d left_i -d mid ≤0(i＝1,2,…,n)
d right_i -d mid ≤0(i＝1,2,…,n)
0<d left_i+1 -d left_i <d left_i -d left_i-1
d right_i -d right_i-1 <d right_i+1 -d right_i <0
acquiring all discrete points on an optimization line;
obtaining discrete points corresponding to the discrete points on the optimization line of the required mold surface, and taking the discrete points as the optimization discrete points corresponding to the reconstruction line R;
adopting an NSGA3 algorithm, taking the minimum average distance between a reconstruction line R and a corresponding optimized discrete point as an optimization target, and acquiring an initial reconstruction line according to constraint conditions;
and connecting the initial reconstruction line with the edge line corresponding to the optimization line to form a complete reconstruction line R.
Optionally, the obtaining a plurality of reconstruction lines by using coordinates of discrete points of the molding surface of the demand mold further includes:
when a first reconstruction line R is obtained, presetting a reconstruction line, and obtaining the first reconstruction line R according to constraint conditions and an NSGA3 algorithm on the basis of the preset reconstruction line;
when the other reconstruction lines R are reconstructed, respectively setting a preset reconstruction line according to the previous reconstruction line of the reconstruction line R, and obtaining the reconstruction line R according to the constraint condition and NSGA3 algorithm based on the preset reconstruction line.
Another aspect of the present invention provides an apparatus for designing a mold surface of an automotive windshield mold based on curved surface reconstruction, which is applied to generating a desired mold surface according to a desired glass surface, comprising:
The glass profile and mould profile acquisition unit is used for acquiring a plurality of groups of profiles from the historical design scheme, wherein each group of profiles comprises a glass profile and a corresponding mould profile;
the glass profile discrete point data acquisition unit is used for respectively extracting discrete points of each glass profile and acquiring geometric characteristic data of each discrete point;
the distance acquisition unit is used for acquiring the distance from each discrete point to the corresponding mold surface;
the mapping model building unit is used for building a mapping model according to the geometric feature data of all the discrete points and the distances from the discrete points to the corresponding mold surfaces, wherein the input variable of the mapping model is the geometric feature of the discrete points, and the output variable is the distance from the discrete points to the corresponding mold surfaces;
the glass profile discrete point data acquisition unit is also used for extracting discrete points requiring the glass profile and acquiring geometric characteristic data of each discrete point;
the distance prediction unit is used for predicting the distance from each discrete point on the required glass profile to the required mold profile according to the geometric feature data of the discrete points of the required glass profile and the mapping model;
the discrete point coordinate acquisition unit is used for acquiring the coordinates of the discrete points of the required mold surface according to the geometric characteristic data of the discrete points of the required glass mold surface and the predicted distance from the discrete points of the required glass mold surface to the required mold surface;
The reconstruction line acquisition unit is used for acquiring a plurality of reconstruction lines by utilizing the coordinates of the discrete points of the required mold surface, and the average distance between each reconstruction line and the corresponding discrete point of the required mold surface is the smallest;
and the required mold profile establishing unit is used for establishing the profile of the required mold by adopting a geometric modeling engine based on the plurality of reconstruction lines.
As can be seen from the above technical solutions, in the method and the device for designing a mold surface of an automotive windshield based on curved surface reconstruction provided by the embodiments of the present invention, first, multiple sets of corresponding glass mold surfaces and mold surfaces are obtained from a historical design scheme, discrete points of each glass mold surface are respectively extracted, geometric feature data of each discrete point is obtained, and distances from each discrete point to the corresponding mold surface are obtained.
And secondly, establishing a mapping model according to the geometric characteristic data of all the discrete points and the distances from the discrete points to the corresponding mold surfaces. And extracting discrete points of the required glass molded surface, and acquiring geometric characteristic data of each discrete point on the required glass molded surface.
And finally, predicting the distance from each discrete point on the required glass profile to the required mold profile according to the geometric feature data of the discrete points of the required glass profile and the mapping model. And acquiring coordinates of the discrete points of the required mold surface according to the geometric characteristic data of the discrete points of the required glass surface and the predicted distance from the discrete points of the required glass surface to the required mold surface. And acquiring a plurality of reconstruction lines by utilizing coordinates of the discrete points of the required mold surface, wherein the average distance between each reconstruction line and the discrete points of the corresponding required mold surface is the smallest. And based on the plurality of reconstruction lines, establishing the profile of the required die by adopting a geometric modeling engine.
Therefore, the method and the device provided by the embodiment of the invention can greatly improve the design efficiency of the mold surface of the automobile windshield and effectively reduce the iteration cost in the design process.
Drawings
Fig. 1 is a schematic flow chart of a design method of a mold surface of an automobile windshield based on curved surface reconstruction according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating implementation of step S102 in FIG. 1 according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a minimum bounding box of an automobile windshield according to an embodiment of the present invention;
FIG. 4 is a schematic view of discrete points on a glass surface according to one embodiment of the present invention;
FIG. 5 is a flowchart illustrating implementation of step S104 in FIG. 1 according to an embodiment of the present invention;
FIG. 6 is a schematic diagram of an optimization area according to an embodiment of the present invention;
FIG. 7 is a schematic diagram of a reconstruction line and corresponding discrete points according to an embodiment of the present invention;
fig. 8 is a schematic structural diagram of an automotive windshield mold profile design device based on curved surface reconstruction according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail below with reference to the drawings and detailed description for the purpose of better understanding of the technical solution of the present invention to those skilled in the art.
Fig. 1 is a schematic flow chart of an automobile windshield mold profile design method based on curved surface reconstruction, which is provided by the embodiment of the invention and is applied to generating a required mold profile according to a required glass profile. As shown in fig. 1, the method comprises the steps of:
step S101: multiple sets of profiles are obtained from the historical design, each set of profiles including a glass profile and a corresponding mold profile.
The glass molded surfaces in each set of molded surfaces and the mold molded surfaces correspond to each other, and each glass molded surface is manufactured by the corresponding mold molded surface.
Step S102: and respectively extracting discrete points of each glass molded surface, and acquiring geometric characteristic data of each discrete point.
In one embodiment of the present disclosure, for each glass profile, as shown in FIG. 2, discrete points are extracted as follows:
step S1021: a minimum bounding box of the glass profile is determined.
The minimum bounding box is the minimum bounding rectangle of the glass profile, which in the disclosed embodiments of the invention can be obtained using existing algorithms.
Step S1022: and establishing a three-dimensional coordinate system of the glass molded surface by taking the central point of the minimum bounding box as an origin.
As shown in fig. 3, the x-axis of the three-dimensional coordinate system is parallel to the longest side of the minimum bounding box, the z-axis of the coordinate system is parallel to the shortest side of the minimum bounding box, and the y-axis of the coordinate system is parallel to the middle length side of the minimum bounding box.
Step S1023: the longest two borderlines on the glass profile are respectively taken as an upper borderline and a lower borderline of the glass profile.
The glass profile is generally an irregular curved surface of approximately rectangular shape, and the boundary of the glass profile is formed by an outwardly curved curve. When the glass profile is upright, its boundary lines are divided into an upper boundary line, a lower boundary line, a left boundary line, and a right boundary line. Wherein, the upper and lower boundary lines of the glass profile are longest.
Step S1024: and respectively carrying out p+1 equal division on the upper boundary line and the lower boundary line, and connecting corresponding equal division points on the upper boundary line and the lower boundary line to obtain p equal division lines.
Dividing the upper boundary line and the lower boundary line by p+1 equally, thereby obtaining p equally divided points up on the upper boundary line i I=1, 2, … p, and p bisectors lp on the lower boundary line i ,i＝1,2,…p。
Connecting corresponding bisectors on the upper and lower border lines, e.g. up 1 Connection lp 1 ，up 2 Connection lp 2 . After connecting the corresponding p equal-dividing points on the upper and lower boundary lines, obtaining p equal-dividing lines l i ,i＝1,2,…p。
Step S1025: p planes perpendicular to the XOY plane and passing through any of the p bisectors are obtained.
With a bisector line l 1 For example, obtain a line of bisection l 1 At the same time, the plane is perpendicular to the XOY plane on the three-dimensional coordinate system, which plane can intersect the glass profile. In the above manner, p planes are obtained, each plane passing through a bisector l i And perpendicular to the XOY plane. Each plane passing through only one bisector line l i The planes are in one-to-one correspondence with the bisectors.
Step S1026: p intersecting lines on the glass profile intersecting p planes are obtained.
The p planes obtained all intersect the glass profile, so that p intersecting lines l 'on the glass profile can be obtained' i I=1, 2, … p, the intersection line being a curve.
Step S1027: q+1 aliquoting is carried out on each intersection line; sequentially connecting the equal division points of the corresponding sequences on the p intersecting lines to obtain q connecting lines; the intersection of the p intersecting lines and the q connecting lines is a discrete point of the glass profile.
For each intersection line l 'on the glass profile' i Each of i=1, 2, … p was q+1 equally divided to obtain each intersection line l' i I=1, 2, q aliquots on … p.
Sequentially connecting corresponding sequential bisectors of p intersecting lines, e.g. connecting intersecting line l' 1 The first bisecting point on the line of intersection l' 2 The first bisecting point on the first line is connected in turn until it is connected to the intersection line l' p The first of the points of bisection, thereby obtaining a connecting line connecting the first of the points of bisection on each of the intersecting lines. After the connection is completed at the q-th bisector on each intersection line, q connection lines on the glass profile can be obtained.
As shown in fig. 4, the intersections of the p intersecting lines with the q connecting lines are taken as discrete points corresponding to the glass profile.
In the disclosed embodiments, the geometric features required to obtain discrete points are discrete point coordinates, normal vectors, average curvature, gaussian curvature, and camber.
The reason for extracting the characteristic parameters is as follows:
combining the hot bending forming and rebound processes of the glass, and lifting the glass raw sheet and attaching the glass raw sheet to the suction mold under the combined action of vacuum adsorption and blowing of the suction film after the glass raw sheet is heated at high temperature; then the suction mold and the glass descend to press the glass together with the hot ring; the glass falls on the cooling ring after being pressed and formed, and is rapidly supported and delivered to the quenching cold air grid area for quenching tempering.
The glass sheet is formed by pressing a suction mold surface and a hot ring surface, and then falls on a cold ring by means of gravity. The stress distribution conditions at each stage are as follows: when in press forming, the surface of the suction mold is firstly contacted with the middle area of the glass raw sheet, and gradually attached to the boundary, so that the stress is small and uneven. After the glass edge is extruded by the surface of the suction mold and the hot ring surface, boundary stress is increased and the distribution is more uniform. When the mould falls, the glass falls onto the cold ring at a certain speed under the action of self gravity, so that impact load is generated, and the stress at the edge of the glass suddenly increases.
Therefore, the stress distribution of the windshield in different positions during the molding process has a certain difference, which can cause the deviation between the different positions on the molded glass surface and the molded surface of the mold to be different. Based on this, positional information of discrete points on the glass surface, i.e., discrete point coordinates (x/y/z), is extracted.
In the hot bending forming process of the glass raw sheet, when the glass raw sheet is subjected to an external bending moment, the shape of the glass raw sheet is changed. When the glass is bent, the inner glass raw sheet of the deformation zone is subjected to tangential compressive stress to generate compression deformation, the outer glass raw sheet is subjected to tangential tensile stress to generate tensile deformation, and the tangential direction also influences the deformation of the glass profile, so that unit normal vectors (vector_x/vector_y/vector_z) perpendicular to the tangential direction are extracted for characterizing the tangential characteristics of the glass profile.
Meanwhile, the radius of curvature of the mold surface is a main factor determining the glass surface, the degree of curvature of the glass surface depends on the shape of the mold surface, and the degree of rebound is related to the radius of curvature of the mold surface. This is because the smaller the radius of curvature of the mold surface, the deeper the relative degree of bending, and the larger the proportion of elastic deformation in the total deformation increases, and the larger the rebound after the external force is removed. Thus, the curvature characteristics of the glass profile, including the average curvature H and gaussian curvature K, are extracted.
In addition, to characterize the degree of curvature of the glass profile, the camber AH of the discrete points was also extracted.
The data values of each geometrical feature of the discrete points are obtained respectively in the following way:
(1) The coordinates of each discrete point are obtained under the coordinate system of the glass profile.
(2) For each discrete point, a normal vector N is obtained as follows:
obtaining a tangent vector S with discrete points parallel to the x-axis x And a tangent vector S of the discrete point parallel to the y-axis y 。
By tangential vector cross-multiplicationTo normal vector N: n=s x ×S y 。
(3) For each discrete point, the average curvature H is obtained as follows:
wherein k is 1 Is the maximum radius of curvature through the discrete points; k (k) 2 Is the smallest radius of curvature through the discrete points.
(4) For each discrete point, a gaussian curvature K is obtained as follows:
K＝k 1 *k 2
wherein k is 1 Is the maximum radius of curvature through the discrete points; k (k) 2 Is the smallest radius of curvature through the discrete points.
(5) For each discrete point, the arch height AH is obtained according to the following method, wherein the arch height is from the discrete point P to the corresponding bisector l i Distance of (2):
AH＝Dist(P,l i ),P∈l' i ,i＝1,2,…p
wherein the discrete point P is at the intersection line l' i I=1, 2, …, p, l i Is equal to l' i Corresponding bisectors.
Step S103: the distance from each discrete point to the corresponding mold surface is obtained.
In one embodiment of the present disclosure,
for each glass profile, the distance from each discrete point on the glass profile to the corresponding mold profile in the z-axis direction is obtained.
Step S104: and establishing a mapping model according to the geometric characteristic data of all the discrete points and the distances from the discrete points to the corresponding mold surfaces.
The input variable of the mapping model is the geometric characteristic of the discrete point, and the output variable is the distance from the discrete point to the corresponding mold surface.
In one embodiment of the present disclosure, the geometric feature data of the discrete points is preprocessed prior to building the mapping model. As shown in fig. 5, the mapping model may be built using the following steps:
step S1041: and preprocessing the coordinates of all the discrete points by adopting a MinMax normalization mode.
In one embodiment of the present disclosure, the coordinates of each discrete point are pre-processed as follows:
wherein f_max is the maximum value of all the discrete point coordinates; f_min is the minimum value in all the discrete point coordinates, and f is the original discrete point coordinate; f' is the preprocessed discrete point coordinates.
Step S1042: and preprocessing the normal vector, the average curvature, the Gaussian curvature and the camber of all the discrete points by adopting a Robust normalization mode.
In one embodiment of the present disclosure, the normal vector, average curvature, gaussian curvature, and camber of each discrete point are all pre-processed as follows:
wherein f is an original geometric feature data value, and the geometric feature data value is a geometric feature data value of one of normal vector, average curvature, gaussian curvature and camber of discrete points; f' is the preprocessed geometrical characteristic data value corresponding to f; f_mean is the median of the geometric feature data values corresponding to f and all the discrete points on the glass molded surface to which the discrete points belong; IQR is the interval length between the 1 st quartile and the 3 rd quartile in the geometric feature data values corresponding to f and all discrete points on the glass profile to which the discrete points belong. For example, f is the original data value of the camber of the discrete point, f' is the data value of the camber after the pretreatment of the discrete point, f_mean is the median of the camber data values of all the discrete points on the glass surface to which the discrete point belongs, and IQR is the interval length between the 1 st quartile and the 3 rd quartile of the camber data values of all the discrete points on the glass surface to which the discrete point belongs.
Step S1043: and constructing a data set by utilizing the geometric characteristic data of the discrete points after pretreatment and the distances between the discrete points and the corresponding mold surfaces in the z-axis direction.
The discrete point coordinates, normal vectors, average curvature, gaussian curvature and camber are used as input variables in the data set, and the distance from a discrete point to a corresponding mold surface in the z-axis direction is used as an output variable in the data set.
Step S1044: a mapping model between the input variable and the output variable is obtained using all the data in the dataset.
In the embodiment disclosed by the invention, the mapping model can be a regression model, a convolutional neural network model and other learning algorithm models, and in the specific embodiment disclosed by the invention, the mapping model is a regression model. Step S1044 may be implemented by:
(1) Any one of all the glass profiles is selected as a test glass profile, and all the glass profiles except the test glass profile are used as training glass profiles.
(2) And constructing a test data set by utilizing the geometric characteristic data of the discrete points of the test glass molded surface after the pretreatment and the distance from the discrete points on the test glass molded surface to the corresponding mold molded surface in the z-axis direction. The coordinates, normal vector, average curvature, gaussian curvature and camber of the discrete points are used as input variables, and the distance from the discrete points to the corresponding mold surface in the z-axis direction is used as an output variable.
(3) And constructing a training data set by utilizing the geometrical characteristic data of the discrete points of the training glass molded surface after the pretreatment and the distance from the discrete points on the training glass molded surface to the corresponding mold molded surface in the z-axis direction. The coordinates, normal vector, average curvature, gaussian curvature and camber of the discrete points are used as input variables, and the distance from the discrete points to the corresponding mold surface in the z-axis direction is used as an output variable.
(4) And establishing a regression model by adopting a random forest algorithm according to the training data set and the test data set.
In one embodiment of the present disclosure, the regression model may be established in the following manner:
(1) And constructing a plurality of training data sets by utilizing different combination modes of the training glass molded surface.
The training data sets are constructed in a plurality, each training data set can be composed of data corresponding to different training glass molded surfaces, and the data corresponding to the training glass molded surfaces are discrete point geometric characteristic data after glass molded surface pretreatment and the distance between the discrete point and the corresponding mold molded surface. The test dataset contains only data corresponding to the test glass profile.
In a specific embodiment of the present disclosure, the data of 6 groups of glass profiles and corresponding mold profiles are respectively a group a, a group D, a group H, a group K, a group N and a group U, wherein the group U is used as a test group, the glass profiles therein are used as test glass profiles, and the group a, the group D, the group H, the group K and the group N are used as training glass profiles.
The training data sets of 5 different combination forms are constructed by using the 5 groups of training groups, wherein independent training data sets, namely an H training data set, an H+A training data set, an H+A+K training data set, an H+A+K+D training data set and an H+A+K+D+N training data set are respectively constructed according to the 5 different combination forms of H, H + A, H +A+ K, H +A+K+ D, H +A+K+D+N. And constructing a test data set according to the U group.
(2) A regression model is built for each training dataset.
And respectively utilizing different training data sets and the same test data set to establish a plurality of regression models, wherein one training data set corresponds to one regression model.
For example, a regression model M1 is built using the H training dataset and the U-set test dataset; establishing a regression model M2 by using the H+A training data set and the U group test data set; establishing a regression model M3 by using the H+A+K training data set and the U group test data set; establishing a regression model M4 by using the H+A+K+D training data set and the U-group test data set; a regression model M5 was established using the h+a+k+d+n training dataset and the U-set test dataset.
(3) And adopting different regression models to fuse into a new regression model.
And fusing the established regression model into a new regression model. For example, regression models M1 and M2 are fused to obtain a regression model M6, and regression models M1 to M5 are fused to obtain a regression model M7. The fusion method can be to take the average value of the data values of the output variables of the regression models in the fusion combination, namely the average value of the predicted values, as the data value of the output variables of the regression models after fusion, namely the predicted values. For example, the input variable data value of the same discrete point p is substituted into M1 and M2 to obtain predicted values M1-p and M2-p, and the input variable data of the discrete point p is substituted into a regression model M6 fused by M1 and M2 to obtain predicted values M6-p, so that the predicted values M6-p= (M1-p+m2-p)/2 outputted by M6.
(4) And carrying out error test on each regression model and the fused regression model by using the test data set.
In the disclosed embodiment of the invention, for each regression model and the fused regression model, the single point maximum error is calculated as follows:
substituting the geometric feature data of each discrete point in the test data set into a regression model, wherein the regression model predicts the predicted value of each discrete point, namely the distance from the discrete point to the corresponding mold surface. And obtaining the absolute value of the difference between the predicted value and the true value of each discrete point, and taking the largest absolute value as the single-point maximum error of the regression model.
(5) And taking the regression model with the minimum error as the finally established regression model.
After single-point maximum errors of all regression models and the fused regression models are respectively obtained, single-point maximum errors of several regression models are compared, and the regression model corresponding to the minimum single-point maximum error is used as the finally established regression model.
For example, the single point maximum error for M1 is 4.19; the single point maximum error of M2 is 3.25; the single point maximum error of M3 is 3.41; the single point maximum error of M4 is 3.43; the single point maximum error of M5 is 2.18; the single point maximum error of M6 is 2.47; the single point maximum error for M7 is 2.04. The single-point maximum error value of M7 is the smallest, so the regression model M7 is used as the final regression model.
Step S105: and extracting discrete points requiring the glass profile, and acquiring geometric characteristic data of each discrete point.
The required glass profile is a glass profile which is required to be designed corresponding to the mold profile and is a glass profile which is designed in advance.
Discrete points of the desired glass profile are extracted as follows:
(1) Determining a minimum bounding box of a required glass profile;
(2) Establishing a three-dimensional coordinate system of the required glass molded surface by taking the central point of the minimum bounding box as an origin, wherein the x-axis of the coordinate system is parallel to the longest side of the minimum bounding box, and the z-axis of the coordinate system is parallel to the shortest side of the minimum bounding box;
(3) Respectively taking the longest two boundary lines on the required glass profile as an upper boundary line and a lower boundary line of the required glass profile;
(4) Dividing the upper boundary line and the lower boundary line by p+1 equally, and connecting corresponding equally dividing points on the upper boundary line and the lower boundary line to obtain p equally dividing lines;
(5) Obtaining p planes which are perpendicular to the XOY plane and pass through any one of the p bisectors, wherein the planes are in one-to-one correspondence with the bisectors;
(6) Obtaining p intersecting lines intersecting p planes on the required glass profile;
(7) Q+1 aliquoting is carried out on each intersection line; sequentially connecting the equal division points of the corresponding sequences on the p intersecting lines to obtain q connecting lines; the intersection of the p intersecting lines and the q connecting lines is a discrete point of the desired glass profile.
According to the method for acquiring the geometric feature data of each discrete point on the glass surface in the foregoing embodiment, the geometric feature data of each discrete point on the glass surface is acquired, which is not described herein.
Step S106: and predicting the distance from each discrete point on the required glass profile to the required mold profile according to the geometric feature data of the discrete points of the required glass profile and the mapping model.
In one embodiment of the present disclosure, this step may be implemented by the sub-steps of:
(1) And (3) preprocessing the coordinates of all discrete points on the required glass molded surface by adopting a MinMax normalization mode.
(2) And (3) preprocessing the normal vector, the average curvature, the Gaussian curvature and the camber of all discrete points on the required glass molded surface in a Robust normalization mode.
(3) Substituting the geometric characteristic data of all the discrete points on the required glass molded surface after pretreatment into a finally determined regression model, and calculating to obtain a predicted value of the distance from each discrete point on the required glass molded surface to the required mold molded surface in the z-axis direction.
(4) It is determined whether the desired glass profile has discrete points corresponding to a plurality of predicted values.
If so, it is stated that the one or more discrete points have more than two predicted values, and when this occurs, the maximum value of the plurality of predicted values is taken as the final predicted value of the corresponding discrete point.
If not, it is indicated that such an abnormal condition does not exist, a unique predicted value corresponding to each discrete point is normally determined.
Step S107: and acquiring coordinates of the discrete points of the required mold surface according to the geometric characteristic data of the discrete points of the required glass surface and the predicted distance from the discrete points of the required glass surface to the required mold surface.
In one embodiment of the invention, the coordinates of each discrete point of the required mold surface are calculated by utilizing the geometric characteristic data of the discrete points on the required glass surface and the distance between the discrete points of the required glass surface and the required mold surface in the z-axis direction, and the discrete points of the required mold surface are discrete points assumed on the required mold surface in one-to-one correspondence with the discrete points on the required glass surface.
The coordinates of each discrete point of the desired mold profile are obtained as follows:
x′ i ＝x i
y′ i ＝y i
z′ i ＝z i +d i
wherein: (x' i ,y' i ,z' i ) Coordinates of discrete points of the required mold surface; (x) i ,y i ,z i ) Coordinates of corresponding discrete points on the required glass profile; d, d i The distance in the z-axis direction from the corresponding discrete point on the predicted desired glass profile to the desired mold profile.
Step S108: and acquiring a plurality of reconstruction lines by using the coordinates of the discrete points of the required mold surface.
Wherein, the average distance between each reconstruction line and the discrete point of the corresponding required mold surface is minimum.
In the disclosed embodiment, a plurality of reconstruction lines for a desired mold profile are obtained in the following manner:
(1) And constructing a surface to be reconstructed of the demand die by adopting a geometric modeling engine according to the coordinates of each discrete point of the demand die surface.
(2) And selecting an optimization area on the profile to be reconstructed, wherein the optimization area does not comprise the edge of the profile to be reconstructed.
In actual production, the glass profile and the edge region of the mould profile are completely coincident, so that the optimization region ignores the edge portion of the surface to be reconstructed.
As shown in FIG. 6, projections of the optimized region and the desired glass profile in the XOY plane are project_1 and project_2, respectively, with a relative distance d between the four boundary curves of the two projected regions 1 ，d 2 ，d 3 ，d 4 ，d i ∈[0,0.5),i＝1,2,3,4。
In one embodiment of the present disclosure, d1 and d2 are each 4% of the length of the short side of the desired glass profile and d3 and d4 are each 4% of the length of the long side of the desired glass profile.
(3) A projected area of the optimized area onto the desired glass profile is obtained.
(4) And cutting the connecting line obtained when the discrete points of the required glass profile are extracted into an optimizing line and an edge line according to the projection area, wherein the optimizing line is a part of the connecting line positioned in the projection area, and the edge line is a part of the connecting line positioned outside the projection area.
When the discrete points of the required glass profile are extracted, q connecting lines are obtained, and the connecting lines are segmented into an optimization line and an edge line by using a projection area. Taking a connecting line as an example, the connecting line is divided into 3 parts by the projection area, wherein the part located in the projection area is an optimization line, and the two parts located outside the projection area are edge lines. In the above manner, each optimization line within the projection area is acquired.
(5) For each optimization line within the projection area, a corresponding reconstruction line R is determined according to the following steps:
as shown in fig. 7, the solid curve is an optimized line on the required glass profile, the virtual curve is a reconstruction line R of the required mold profile, the square solid point is a predicted discrete point of the required mold profile, that is, an optimized discrete point in the following description, and a straight line between the discrete point and the virtual curve is a distance between the discrete point and the reconstruction line R.
a. Obtaining the highest point x on the optimization line mid The highest point is the point with the maximum value of the optimization line in the z-axis direction; set the highest point x mid The distance from the corresponding reconstruction line R in the z-axis direction is d mid ；
b. At the highest point x mid Centered at the highest point x on the optimization line mid N position points x are uniformly arranged on two sides of the frame respectively, and the position points x are as follows in sequence: x is x left_1 ，x left_2 ，…，x left_n ，x right_1 ，x right_2 ，…，x right_n The method comprises the steps of carrying out a first treatment on the surface of the Let the distance between the position point x and the reconstruction line R in the z-axis direction be d in turn left_1 ，d left_2 ，…，d left_n ，d right_1 ，d right_2 ，…，d right_n ；
c. Will d left_1 ，d left_2 ，…，d left_n ，d right_1 ，d right_2 ，…，d right_n
As a design variable;
d. the following constraint conditions are set for the values of the design variables:
d left_i -d mid ≤0(i＝1,2,…,n)
d right_i -d mid ≤0(i＝1,2,…,n)
0<d left_i+1 -d left_i <d left_i -d left_i-1
d right_i -d right_i-1 <d right_i+1 -d right_i <0
e. all discrete points on the optimization line are acquired.
f. And obtaining discrete points corresponding to the discrete points on the optimization line of the required mold surface, and taking the discrete points as the optimization discrete points corresponding to the reconstruction line R.
g. Adopting NSGA3 algorithm, taking the minimum average distance between the reconstruction line R and the corresponding optimized discrete point as the optimization target, and calculating the final value of each design variable according to constraint conditions, namely the highest point x on the optimization line mid And distances in the z-axis direction between 2n position points x and the corresponding reconstruction lines R.
Under the coordinate system corresponding to the required glass molded surface, the highest point x is obtained mid And coordinates of 2n position points x.
Respectively the highest point x mid And adding the z-direction value in the 2n position point coordinates and the corresponding design variable value to obtain 2n+1 point coordinates, taking the 2n+1 points as reconstruction points on the reconstruction line R, and generating an initial reconstruction line by using the coordinates of all the reconstruction points.
GA (genetic algorithm) in NSGA3 is a genetic algorithm, and its principle is to simulate biological evolution, and there are two important parameters in the process of simulating biological evolution, population size and iteration number: the population scale is the number of organisms in the population, the number of schemes is the number of each generation of schemes in the optimization process of the actual problem, and the number of each generation of schemes in the genetic algorithm is the population scale; the number of times of biological propagation evolution is iteration algebra, namely the number of times of genetic operation (crossover and mutation) of population seeds to generate offspring population in the optimization process of practical problems.
The population size and the iteration number are set before solving the optimization problem, wherein the population size is set to 500, and the iteration number is set to 150.
h. And connecting the edge lines corresponding to the initial reconstruction line and the optimization line to form a complete reconstruction line R.
Each optimization line corresponds to two edge lines, and the optimization lines and the corresponding edge lines form a complete connecting line. And connecting the initial reconstruction line with two edge lines corresponding to the optimization line to form a complete reconstruction line R.
The edge lines on the left side and the right side of the required glass molded surface are connected with the initial reconstruction line in consideration of the overall continuity of the space, and the edge region of the required glass molded surface is completely attached to the edge region of the required mold molded surface in actual production, so that the edge lines on the required glass molded surface can be smoothly connected with the initial reconstruction line.
According to the above steps, each optimization line can obtain a corresponding reconstruction line R.
In the embodiment of the disclosure, when the first reconstruction line R is obtained, a reconstruction line is preset, and in a specific embodiment of the disclosure, a preset number of discrete points may be selected at will from all optimized discrete points corresponding to the first reconstruction line, and a curve is formed according to the preset number of discrete points, and the curve is used as the preset reconstruction line. Based on the preset reconstruction line, adopting an NSGA3 algorithm, taking the minimum average distance between the reconstruction line R and the corresponding optimized discrete point as an optimization target, and obtaining a first reconstruction line R according to constraint conditions;
When the other reconstruction lines R are reconstructed, a preset reconstruction line is set according to the previous reconstruction line of the reconstruction line R, and the reconstruction line R is obtained according to the constraint condition and NSGA3 algorithm based on the preset reconstruction line. For example, when reconstructing the second reconstruction line, the first reconstruction line is translated in the y-axis direction according to the reconstructed first reconstruction line as a preset reconstruction line, so as to obtain the second reconstruction line, wherein the translation distance is the distance between the corresponding connection lines in the y-axis direction.
Step S109: based on the plurality of reconstruction lines, a geometric modeling engine is used to build the profile of the desired mold.
And (3) carrying out curved surface reconstruction on all reconstruction lines by using the existing geometric modeling engine to construct the final required mold surface.
Fig. 8 is a schematic structural diagram of a device for designing a mold surface of an automobile windshield glass mold, which is applied to generating a mold surface according to a required glass mold surface. As shown in fig. 8, the apparatus includes the following units:
a glass profile and mold profile acquiring unit 11 configured to acquire a plurality of sets of profiles each including one glass profile and a corresponding one of the mold profiles from the historical design;
A glass profile discrete point data acquisition unit 12 configured to extract discrete points of each glass profile, respectively, and acquire geometric feature data of each discrete point;
a distance acquisition unit 13 configured to acquire a distance from each discrete point to a corresponding mold surface;
a mapping model establishing unit 14 configured to establish a mapping model according to the geometric feature data of all the discrete points and the distances from the discrete points to the corresponding mold surfaces, wherein the input variable of the mapping model is the geometric feature of the discrete points, and the output variable is the distance from the discrete points to the corresponding mold surfaces;
a glass profile discrete point data acquisition unit 12 further configured to extract discrete points requiring a glass profile and acquire geometric feature data of each discrete point;
a distance predicting unit 15 configured to predict a distance from each discrete point on the required glass profile to the required mold profile according to the geometric feature data of the discrete points of the required glass profile and the mapping model;
a discrete point coordinate acquiring unit 16 configured to acquire coordinates of discrete points of the required mold surface according to geometric feature data of the discrete points of the required glass surface and a predicted distance from the discrete points of the required glass surface to the required mold surface;
A reconstruction line acquisition unit 17 configured to acquire a plurality of reconstruction lines using coordinates of discrete points of the required mold profile, each reconstruction line having a minimum average distance from a corresponding discrete point of the required mold profile;
a demand mold profile creation unit 18 configured to create a profile of the demand mold using the geometric modeling engine based on the plurality of reconstruction lines.
It is to be understood that the above embodiments are merely illustrative of the application of the principles of the present invention, but not in limitation thereof. Various modifications and improvements may be made by those skilled in the art without departing from the spirit and substance of the invention, and are also considered to be within the scope of the invention.
Claims (11)
1. The design method of the mold profile of the automobile windshield based on curved surface reconstruction is applied to generating a required mold profile according to the required glass profile, and is characterized by comprising the following steps:
obtaining multiple groups of molded surfaces from historical design schemes, wherein each group of molded surfaces comprises a glass molded surface and a corresponding mold molded surface;
extracting discrete points of each glass profile, respectively, comprising:
for each glass profile, discrete points are extracted as follows:
Determining a minimum bounding box of the glass profile;
establishing a three-dimensional coordinate system of the glass molded surface by taking the central point of the minimum bounding box as an origin, wherein the x-axis of the coordinate system is parallel to the longest side of the minimum bounding box, and the z-axis of the coordinate system is parallel to the shortest side of the minimum bounding box;
respectively taking the longest two boundary lines on the glass molded surface as an upper boundary line and a lower boundary line of the glass molded surface;
dividing the upper boundary line and the lower boundary line by p+1 equally, and connecting corresponding equally dividing points on the upper boundary line and the lower boundary line to obtain p equally dividing lines;
obtaining p planes which are perpendicular to the XOY plane and pass through any one of p bisectors, wherein the planes are in one-to-one correspondence with the bisectors;
obtaining p intersecting lines intersecting p planes on the glass molded surface;
q+1 aliquoting is carried out on each intersecting line; sequentially connecting the equal division points of the corresponding sequences on the p intersecting lines to obtain q connecting lines; the intersection points of the p intersecting lines and the q connecting lines are discrete points of the glass profile;
obtaining geometric feature data of each discrete point, wherein the geometric feature data comprises coordinates, normal vectors, average curvature, gaussian curvature and camber;
Obtaining the distance from each discrete point to the corresponding mold surface;
establishing a mapping model according to the geometric characteristic data of all the discrete points and the distances from the discrete points to the corresponding mold surfaces, wherein the mapping model comprises the following steps:
preprocessing the coordinates of all the discrete points by adopting a MinMax normalization mode;
preprocessing normal vectors, average curvatures, gaussian curvatures and arch heights of all discrete points by adopting a Robust normalization mode;
constructing a data set by utilizing the preprocessed geometric feature data of the discrete points and the distances from the discrete points to the corresponding mold surfaces in the z-axis direction, wherein the coordinates, normal vectors, average curvature, gaussian curvature and camber of the discrete points are used as input variables of the data set, and the distances from the discrete points to the corresponding mold surfaces in the z-axis direction are used as output variables of the data set;
obtaining a mapping model between an input variable and an output variable by using all data in a data set, wherein the input variable of the mapping model is the geometric characteristic of a discrete point, and the output variable is the distance from the discrete point to a corresponding mold surface;
discrete points of the required glass molded surface are extracted, and geometric feature data of each discrete point are obtained;
according to the geometric feature data of discrete points of the required glass molded surface and the mapping model, predicting the distance from each discrete point on the required glass molded surface to the required mold molded surface;
Obtaining coordinates of discrete points of the required mold surface according to geometric characteristic data of the discrete points of the required glass surface and the predicted distance from the discrete points of the required glass surface to the required mold surface;
obtaining a plurality of reconstruction lines using coordinates of discrete points of a desired mold profile, comprising:
constructing a surface to be reconstructed of the demand die by adopting a geometric modeling engine according to the coordinates of each discrete point of the demand die surface;
selecting an optimized area on the profile to be reconstructed, wherein the optimized area does not comprise the edge of the profile to be reconstructed;
acquiring a projection area of the optimized area on a required glass molded surface;
dividing a connecting line obtained when the discrete points of the required glass profile are extracted into an optimizing line and an edge line according to the projection area, wherein the optimizing line is a part of the connecting line positioned in the projection area, and the edge line is a part of the connecting line positioned outside the projection area;
for each optimization line in the projection area, determining a corresponding reconstruction line R according to the following steps:
obtaining the highest point x on the optimized line mid The highest point is the point with the maximum value of the optimization line in the z-axis direction; set the highest point x mid The distance from the corresponding reconstruction line R in the z-axis direction is d mid ；
At the highest point x mid Centered at the highest point x on the optimization line mid N position points x are uniformly arranged on two sides of the frame respectively, and the position points x are as follows in sequence: x is x left_1 ，x left_2 ，…，x left_n ，x right_1 ，x right_2 ，…，x right_n The method comprises the steps of carrying out a first treatment on the surface of the Let the distance between the position point x and the reconstruction line R in the z-axis direction be d in turn left_1 ，d left_2 ，…，d left_n ，d right_1 ，d right_2 ，…，d right_n ；
Will d left_1 ，d left_2 ，…，d left_n ，d right_1 ，d right_2 ，…，d right_n As a design variable;
the following constraint conditions are set for the values of the design variables:
d left_i -d mid ≤0(i＝1,2,…,n)
d right_i -d mid ≤0(i＝1,2,…,n)
0<d left_i+1 -d left_i <d left_i -d left_i-1
d right_i -d right_i-1 <d right_i+1 -d right_i <0
acquiring all discrete points on the optimization line;
obtaining discrete points of the required mold surface corresponding to the discrete points on the optimization line, and taking the discrete points as the optimization discrete points corresponding to the reconstruction line R;
adopting an NSGA3 algorithm, taking the minimum average distance between a reconstruction line R and a corresponding optimized discrete point as an optimization target, and acquiring an initial reconstruction line according to constraint conditions;
connecting the initial reconstruction line with the edge line corresponding to the optimization line to form a complete reconstruction line R, wherein the average distance between each reconstruction line and the discrete point of the corresponding required mold surface is the smallest;
and based on the plurality of reconstruction lines, establishing the profile of the required die by adopting a geometric modeling engine.
2. The method of claim 1, wherein obtaining geometric feature data for each of the discrete points comprises:
(1) Acquiring the coordinates of each discrete point under a coordinate system corresponding to the glass molded surface;
(2) For each discrete point, a normal vector N is obtained as follows:
obtaining a tangent vector S with discrete points parallel to the x-axis x And a tangent vector S of the discrete point parallel to the y-axis y ；
The normal vector N is obtained by tangential vector cross multiplication: n=s x ×S y ；
(3) For each discrete point, the average curvature H is obtained as follows:
wherein,k 1 is the maximum radius of curvature through the discrete points; k (k) 2 Is the minimum radius of curvature through the discrete points;
(4) For each discrete point, a gaussian curvature K is obtained as follows:
K＝k 1 *k 2
wherein k is 1 Is the maximum radius of curvature through the discrete points; k (k) 2 Is the minimum radius of curvature through the discrete points;
(5) For each discrete point, arch height AH is obtained according to the following method;
the camber is the distance from the discrete point to the corresponding bisector:
AH＝Dist(P,l i ),P∈l′ i ,i＝1,2,…p
wherein the discrete point P is at the intersection line l' i Upper, l i Is equal to l' i Corresponding bisectors.
3. The method of claim 2, wherein the obtaining the distance of each discrete point to the corresponding mold profile comprises:
and respectively acquiring the distance from each discrete point on each glass molded surface to the corresponding mold molded surface in the z-axis direction for each glass molded surface.
4. The method according to claim 1, wherein the preprocessing of the coordinates of all discrete points by MinMax normalization comprises:
the coordinates of each discrete point are preprocessed according to the following method:
wherein f_max is the maximum value of all the discrete point coordinates; f_min is the minimum value in all the discrete point coordinates, and f is the original discrete point coordinate; f' is the preprocessed discrete point coordinates.
5. The method of claim 1, wherein the preprocessing of the normal vector, average curvature, gaussian curvature and camber for all discrete points using Robust normalization comprises:
the normal vector, average curvature, gaussian curvature and camber of each discrete point are all pre-processed as follows:
wherein f is an original geometric feature data value, and the geometric feature data value is a data value of one geometric feature of normal vector, average curvature, gaussian curvature and camber of the discrete points; f' is the preprocessed geometrical characteristic data value corresponding to f; f_mean is the median of the geometric feature data values corresponding to f of all the discrete points on the glass molded surface to which the discrete points belong; IQR is the interval length between the 1 st quartile and the 3 rd quartile in the geometric feature data values corresponding to f and all discrete points on the glass profile to which the discrete points belong.
6. The method of claim 1, wherein the establishing a mapping model from geometric feature data of all discrete points and distances of the discrete points to corresponding mold surfaces comprises:
any one of all the glass molded surfaces is selected as a test glass molded surface, and the rest glass molded surfaces are all used as training glass molded surfaces;
constructing a test data set by utilizing the geometric characteristic data of the discrete points after the pretreatment of the test glass molded surface and the distances from the discrete points on the test glass molded surface to the corresponding mold molded surface in the z-axis direction, wherein the coordinates, normal vectors, average curvature, gaussian curvature and camber of the discrete points are used as input variables, and the distances from the discrete points to the corresponding mold molded surface in the z-axis direction are used as output variables;
constructing a training data set by utilizing the geometric characteristic data of the discrete points after the pretreatment of the training glass molded surface and the distances from the discrete points on the training glass molded surface to the corresponding mold molded surface in the z-axis direction, wherein the coordinates, normal vectors, average curvature, gaussian curvature and camber of the discrete points are used as input variables, and the distances from the discrete points to the corresponding mold molded surface in the z-axis direction are used as output variables;
and establishing a regression model between geometric feature data of discrete points of the glass molded surface and distances between the discrete points and the corresponding molded surface of the mold in the z-axis direction by adopting a random forest training algorithm according to the training data set and the testing data set.
7. The method of claim 6, wherein extracting discrete points of the desired glass profile and obtaining geometric feature data for each of the discrete points comprises:
determining a minimum bounding box of a required glass profile;
establishing a three-dimensional coordinate system of the required glass molded surface by taking the central point of the minimum bounding box as an origin, wherein the x-axis of the coordinate system is parallel to the longest side of the minimum bounding box, and the z-axis of the coordinate system is parallel to the shortest side of the minimum bounding box;
respectively taking the longest two boundary lines on the required glass profile as an upper boundary line and a lower boundary line of the required glass profile;
dividing the upper boundary line and the lower boundary line by p+1 equally, and connecting corresponding equally dividing points on the upper boundary line and the lower boundary line to obtain p equally dividing lines;
obtaining p planes which are perpendicular to the XOY plane and pass through any one of p bisectors, wherein the planes are in one-to-one correspondence with the bisectors;
obtaining p intersecting lines intersecting p planes on the required glass profile;
q+1 aliquoting is carried out on each intersecting line; sequentially connecting the equal division points of the corresponding sequences on the p intersecting lines to obtain q connecting lines; the intersection points of the p intersecting lines and the q connecting lines are discrete points of the required glass profile.
8. The method of claim 7, wherein predicting the distance of each discrete point on the desired glass profile to the desired mold profile based on the geometric feature data of the discrete points of the desired glass profile and the mapping model comprises:
preprocessing the coordinates of all discrete points on the required glass molded surface in a MinMax normalization mode;
preprocessing normal vectors, average curvatures, gaussian curvatures and camber of all discrete points on a required glass molded surface in a Robust normalization mode;
substituting the geometric feature data of all the discrete points on the required glass molded surface after pretreatment into a regression model, and calculating to obtain a predicted value of the distance from each discrete point on the required glass molded surface to the required mold molded surface in the z-axis direction;
determining whether there are discrete points on the desired glass profile having a plurality of predicted values,
if so, the maximum value in the plurality of predicted values is taken as the final predicted value of the corresponding discrete point.
9. The method of claim 8, wherein the obtaining coordinates of discrete points of the desired mold profile based on geometric feature data of discrete points of the desired glass profile and the predicted distance of discrete points of the desired glass profile to the desired mold profile comprises:
The coordinates of each discrete point of the desired mold profile are obtained as follows:
x′ i ＝x i
y′ i ＝y i
z′ i ＝z i +d i
wherein: (x' i ,y′ i ,z′ i ) Coordinates of discrete points of the required mold surface; (x) i ,y i ,z i ) Coordinates of corresponding discrete points on the required glass profile; d, d i The distance in the z-axis direction from the corresponding discrete point on the predicted desired glass profile to the desired mold profile.
10. The method of claim 1, wherein the acquiring a plurality of reconstruction lines using coordinates of discrete points of the desired mold profile further comprises:
when a first reconstruction line R is obtained, presetting a reconstruction line, and obtaining the first reconstruction line R according to constraint conditions and an NSGA3 algorithm on the basis of the preset reconstruction line;
when other reconstruction lines R are obtained, a preset reconstruction line is set according to the previous reconstruction line of the reconstruction line R, and the reconstruction line R is obtained according to constraint conditions and NSGA3 algorithm based on the preset reconstruction line.
11. An automobile windshield mold profile design device based on curved surface reconstruction is applied to and generates demand mold profile according to demand glass profile, which is characterized by comprising:
the glass profile and mould profile acquisition unit is used for acquiring a plurality of groups of profiles from the historical design scheme, wherein each group of profiles comprises a glass profile and a corresponding mould profile;
A glass profile discrete point data acquisition unit for respectively extracting discrete points of each glass profile, comprising:
for each glass profile, discrete points are extracted as follows:
determining a minimum bounding box of the glass profile;
establishing a three-dimensional coordinate system of the glass molded surface by taking the central point of the minimum bounding box as an origin, wherein the x-axis of the coordinate system is parallel to the longest side of the minimum bounding box, and the z-axis of the coordinate system is parallel to the shortest side of the minimum bounding box;
respectively taking the longest two boundary lines on the glass molded surface as an upper boundary line and a lower boundary line of the glass molded surface;
dividing the upper boundary line and the lower boundary line by p+1 equally, and connecting corresponding equally dividing points on the upper boundary line and the lower boundary line to obtain p equally dividing lines;
obtaining p planes which are perpendicular to the XOY plane and pass through any one of p bisectors, wherein the planes are in one-to-one correspondence with the bisectors;
obtaining p intersecting lines intersecting p planes on the glass molded surface;
q+1 aliquoting is carried out on each intersecting line; sequentially connecting the equal division points of the corresponding sequences on the p intersecting lines to obtain q connecting lines; the intersection points of the p intersecting lines and the q connecting lines are discrete points of the glass profile;
The glass profile discrete point data acquisition unit is also used for acquiring geometric feature data of each discrete point, wherein the geometric feature data comprises coordinates, normal vectors, average curvature, gaussian curvature and camber;
the distance acquisition unit is used for acquiring the distance from each discrete point to the corresponding mold surface;
the mapping model building unit is used for building a mapping model according to the geometric characteristic data of all the discrete points and the distances from the discrete points to the corresponding mold surfaces, and comprises the following steps:
preprocessing the coordinates of all the discrete points by adopting a MinMax normalization mode;
preprocessing normal vectors, average curvatures, gaussian curvatures and arch heights of all discrete points by adopting a Robust normalization mode;
constructing a data set by utilizing the preprocessed geometric feature data of the discrete points and the distances from the discrete points to the corresponding mold surfaces in the z-axis direction, wherein the coordinates, normal vectors, average curvature, gaussian curvature and camber of the discrete points are used as input variables of the data set, and the distances from the discrete points to the corresponding mold surfaces in the z-axis direction are used as output variables of the data set;
obtaining a mapping model between an input variable and an output variable by using all data in a data set, wherein the input variable of the mapping model is the geometric characteristic of a discrete point, and the output variable is the distance from the discrete point to a corresponding mold surface;
The glass profile discrete point data acquisition unit is also used for extracting discrete points requiring the glass profile and acquiring geometric characteristic data of each discrete point;
the distance prediction unit is used for predicting the distance from each discrete point on the required glass profile to the required mold profile according to the geometric feature data of the discrete points of the required glass profile and the mapping model;
the discrete point coordinate acquisition unit is used for acquiring the coordinates of the discrete points of the required mold surface according to the geometric characteristic data of the discrete points of the required glass mold surface and the predicted distance from the discrete points of the required glass mold surface to the required mold surface;
a reconstruction line obtaining unit, configured to obtain a plurality of reconstruction lines by using coordinates of discrete points of a required mold surface, including:
constructing a surface to be reconstructed of the demand die by adopting a geometric modeling engine according to the coordinates of each discrete point of the demand die surface;
selecting an optimized area on the profile to be reconstructed, wherein the optimized area does not comprise the edge of the profile to be reconstructed;
acquiring a projection area of the optimized area on a required glass molded surface;
dividing a connecting line obtained when the discrete points of the required glass profile are extracted into an optimizing line and an edge line according to the projection area, wherein the optimizing line is a part of the connecting line positioned in the projection area, and the edge line is a part of the connecting line positioned outside the projection area;
For each optimization line in the projection area, determining a corresponding reconstruction line R according to the following steps:
obtaining the highest point x on the optimized line mid The highest point is the point with the maximum value of the optimization line in the z-axis direction; set the highest point x mid The distance from the corresponding reconstruction line R in the z-axis direction is d mid ；
At the highest point x mid Centered at the highest point x on the optimization line mid N position points x are uniformly arranged on two sides of the frame respectively, and the position points x are as follows in sequence: x is x left_1 ，x left_2 ，…，x left_n ，x right_1 ，x right_2 ，…，x right_n The method comprises the steps of carrying out a first treatment on the surface of the Let the distance between the position point x and the reconstruction line R in the z-axis direction be d in turn left_1 ，d left_2 ，…，d left_n ，d right_1 ，d right_2 ，…，d right_n ；
Will d left_1 ，d left_2 ，…，d left_n ，d right_1 ，d right_2 ，…，d right_n As a design variable;
the following constraint conditions are set for the values of the design variables:
d left_i -d mid ≤0(i＝1,2,…,n)
d right_i -d mid ≤0(i＝1,2,…,n)
0<d left_i+1 -d left_i <d left_i -d left_i-1
d right_i -d right_i-1 <d right_i+1 -d right_i <0
acquiring all discrete points on the optimization line;
obtaining discrete points of the required mold surface corresponding to the discrete points on the optimization line, and taking the discrete points as the optimization discrete points corresponding to the reconstruction line R;
adopting an NSGA3 algorithm, taking the minimum average distance between a reconstruction line R and a corresponding optimized discrete point as an optimization target, and acquiring an initial reconstruction line according to constraint conditions;
connecting the initial reconstruction line with the edge line corresponding to the optimization line to form a complete reconstruction line R, wherein the average distance between each reconstruction line and the discrete point of the corresponding required mold surface is the smallest;
And the required mold profile establishing unit is used for establishing the profile of the required mold by adopting a geometric modeling engine based on the plurality of reconstruction lines.
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