TWI789702B - Lens construction method - Google Patents

Abstract

Lens construction method includes loading cloud data to a machining program; processing a core by a processing machine based on the machining program; and forming a cavity by using the core, and inject the liquid in the cavity to form a lens.

Description

Lens Construction Method

The disclosure relates to a lens construction method, especially a lens construction method using point cloud data.

Most of the current lens construction methods use processing machines to process lens mold cores. However, the parameter setting of the processing machine is limited, and it is difficult to meet different wearing requirements. For example, the current processing method will have problems such as poor stability of astigmatism lenses, time-consuming lens positioning, insufficient smoothness of the lens surface, and poor wearing comfort.

In view of this, how to provide a lens construction method that can improve the above problems is still one of the goals that the industry needs to study urgently.

An embodiment of the present disclosure is a lens construction method.

In an embodiment of the present disclosure, the lens construction method includes importing point cloud data into the processing formula; using the processing machine to process the mold core according to the processing formula; and forming a mold through the mold core, and injecting liquid medicine into the mold Form lenses.

In an embodiment of the present disclosure, the point cloud data is obtained through a 3D model.

In an embodiment of the present disclosure, the point cloud data is obtained through function operations.

In an embodiment of the present disclosure, the point cloud data includes a plurality of three-dimensional coordinate points, the lens includes a convex surface and a concave surface, each of which has a plurality of curvatures, and the plurality of curvatures are defined by the three-dimensional coordinate points.

In an embodiment of the present disclosure, the lens includes multiple regions, and the lens construction method further includes combining multiple 3D models to obtain point cloud data corresponding to the multiple regions.

In an embodiment of the present disclosure, the lens includes multiple regions, and the lens construction method further includes obtaining point cloud data corresponding to the multiple regions through different function calculations.

In an embodiment of the present disclosure, the lens construction method further includes defining the optical characteristics of the optical zone by point cloud data for correcting the refractive error of the eyeball.

In an embodiment of the present disclosure, the lens includes a peripheral area, and the lens construction method further includes defining a thickness distribution of the peripheral area by point cloud data.

In an embodiment of the present disclosure, the lens construction method further includes adjusting smoothness of connecting surfaces of multiple regions of the lens by using point cloud data.

In an embodiment of the present disclosure, the lens construction method further includes defining the directionality of the lens by point cloud data.

In the above-mentioned embodiment, the lens construction method can form a processing file through the point cloud data type, avoiding the mold core processing being limited by the parameters that can be defined by the processing machine, and can more accurately adjust the optical characteristics of the lens. Therefore, with the lens construction method of the present disclosure, the stability of the astigmatic lens can be improved, and the time required for positioning the astigmatic lens can be reduced. In addition, constructing lenses based on point cloud data can improve the surface smoothness of the lenses and enhance wearing comfort.

Several embodiments of the present invention will be disclosed in the following figures. For the sake of clarity, many practical details will be described together in the following description. It should be understood, however, that these practical details should not be used to limit the invention. That is, in some embodiments of the present invention, these practical details are unnecessary. In addition, for the sake of simplifying the drawings, some well-known structures and components will be shown in a simple and schematic manner in the drawings. Also, the thicknesses of layers and regions in the drawings may be exaggerated for clarity, and the same reference numerals denote the same elements in the description of the drawings.

FIG. 1 is a flowchart of a lens construction method 100 according to an embodiment of the present disclosure. The lens construction method 100 starts at step S11 , constructing a three-dimensional model through software to simulate the surface curvature of the mold core. Next, step S12 of the lens construction method 100 includes converting the 3D model into point cloud data. Next, step S13 of the lens construction method 100 includes importing the point cloud data into the processing program. Next, step S14 of the lens construction method 100 includes generating a plurality of processing files according to the point cloud data. Next, step S15 of the lens construction method 100 includes processing the mold core by a processing machine according to a processing formula. Finally, next, the step S16 of the lens construction method 100 includes forming a mold with a mold core, and injecting a liquid medicine into the mold to form a lens.

FIG. 2A is a three-dimensional model 110A of a lens convex mold core according to an embodiment of the present disclosure. FIG. 2B is a three-dimensional model 110B of a lens concave mold core according to an embodiment of the present disclosure. Also refer to step S11 in FIG. 1 and FIG. 2A and FIG. 2B. Both the 3D model 110A of the lens convex mold core and the 3D model 110B of the lens concave mold core include the optical zone 112 and the peripheral zone 114 . The three-dimensional model 110A of the lens convex mold core has a convex surface 116 and the three-dimensional model 110B of the lens concave mold core has a concave surface 118 . Each of the convex surface 116 and the concave surface 118 includes a plurality of regions (such as the region R1 , the region R2 and the region R3 shown in FIG. 2A ), and the plurality of regions have different curvatures. In other words, the 3D model 110A of the lens convex mold core and the 3D model 110B of the lens concave mold core are used to construct the free-form lens. For example, the diopter (Power) and center thickness (Center Thickness) of the optical zone 112 can be adjusted by adjusting the curvature of the central area corresponding to the convex surface 116 of the three-dimensional model 110A of the convex mold core and the concave surface 118 of the three-dimensional model 110B of the concave mold core. And decided. The back curve of the optical zone 112 can be determined by adjusting the curvature of different regions on the concave surface 118 . The thickness distribution of the peripheral region 114 can also be determined by adjusting the curvature of the region of the convex surface 116 corresponding to the peripheral region 114 and the region of the concave surface 118 corresponding to the peripheral region 114 .

FIG. 3 is a schematic diagram of a lens construction method using point cloud data 120 according to an embodiment of the present disclosure. Refer to step S12 in FIG. 1 and FIG. 3 at the same time. The 3D models 110A, 110B can be converted into point cloud data 120 . The step of converting the 3D model 110A of the lens convex mold core and the 3D model 110B of the lens concave mold core into the point cloud data 120 can be executed by drawing software. The point cloud data 120 includes a plurality of three-dimensional coordinate points. In this embodiment, rectangular coordinates (XYZ coordinates) are taken as an example, but the disclosure is not limited thereto. The curvatures of the regions of the convex surface 116 and the concave surface 118 can be defined by three-dimensional coordinate points. For example, as shown in FIG. 2A , the surface curvatures of the regions R1 , R2 and R3 on the convex surface 116 of the 3D lens convex mold 110A can be defined by a plurality of 3D coordinate points. For example, the surface curvature of the region R1 can be defined by the three-dimensional coordinate point P1, the three-dimensional coordinate point P2, the three-dimensional coordinate point P3, and the three-dimensional coordinate point P4. After the 3D model 110A of the lens convex mold core is converted into point cloud data 120, the 3D coordinate points P1, 3D coordinate point P2, 3D coordinate point P3, and 3D coordinate point P4 all have corresponding X coordinates, Y coordinates, and Z coordinates. Similarly, the surface curvatures of the region R2 and the region R3 can also be defined by the corresponding three-dimensional coordinate points in the point cloud data 120 . Similarly, the three-dimensional model 110B of the lens concave mold core shown in FIG. 2B also has many regions and corresponding three-dimensional coordinate points. The three-dimensional model 110B of the lens concave mold core can be converted into point cloud data 120 by the above method.

Refer to step S13 to step S15 in Fig. 1 and Fig. 3 at the same time. The lens construction method 100 also includes importing the point cloud data 120 into a processing formula 130 . Then, a plurality of processing files are generated according to the point cloud data 120, and the concave mold core and the convex mold core are respectively processed by the processing machine 140 according to the processing formula. The processing file recording the point cloud data 120 can define multiple processing paths of the processing machine 140 to respectively construct the curvature of multiple areas defined on the 3D model 110A of the lens convex mold core and the 3D model 110B of the lens concave mold core . In Fig. 3, only the convex surface of the lens is illustrated. The concave and convex surfaces of the lens are processed according to the point cloud data 120 obtained from the three-dimensional models 110A and 110B shown in Fig. 2A and Fig. 2B respectively.

Refer to step S16 in Fig. 1 . A mold is formed by the mold core completed in step S15, and a liquid medicine is injected into the mold to form a lens. According to the above steps, the smoothness of the connection surfaces of multiple regions of the lens can be adjusted by using the point cloud data converted from the 3D model. In addition, the 3D models 110A and 110B can also define curvatures of different regions by a combination of multiple 3D models. In other words, as long as the point cloud data converted from the 3D model can define the curvature relationship between the convex and concave surfaces of the lens and achieve the required optical characteristics.

The lenses constructed by the present disclosure based on point cloud data can be used to correct refractive errors, such as myopia, hyperopia, astigmatism, and the like. The lens constructed by the method of the present disclosure can be applied to contact lenses, glasses, or optical lenses. In other words, forming a processing file by means of the point cloud data type can prevent the mold core processing from being limited by the parameters that can be defined by the processing machine, so that the optical characteristics of the lens can be adjusted more precisely.

In addition, constructing lenses from point cloud data can define the vertical weight ratio of contact lenses for correcting astigmatism, thereby improving the stability of astigmatic lenses and reducing the time required for positioning astigmatic lenses. In addition, constructing lenses based on point cloud data can improve the surface smoothness of the lenses and enhance wearing comfort.

FIG. 4 is a flowchart of a lens construction method 200 according to another embodiment of the present disclosure. The lens construction method 200 starts at step S21, and obtains point cloud data through function calculation. Steps S22 to S25 of the lens construction method 200 are substantially the same as steps S13 to S16 of the lens construction method 100 , and will not be repeated here.

FIG. 5 is a schematic diagram of a lens construction method 200 using point cloud data according to another embodiment of the present disclosure. Refer to step S21 of FIG. 4 and FIG. 5 at the same time. In step S21, the point cloud data corresponding to the mold core to be processed can be constructed by using software with function calculation functions, such as MATLAB, EXCEL, etc.

For example, in one embodiment, the curvature of the connection line S between the three-dimensional coordinate point P5 and the three-dimensional coordinate point P6 can be calculated according to a spherical function with a single curvature radius. In other embodiments, it can also be obtained by aspheric function operations, such as conic sections or aspheric surfaces established by polynomials. In other embodiments, the curvature between the three-dimensional coordinate points in different areas in the point cloud data may also be composed of a plurality of the aforementioned curvature radius gradients. Alternatively, in other embodiments, the curvature F between 3D coordinate points in different regions in the point cloud data can also be formed by a spline function and nodes (such as shown by the 3D coordinate point P7 and the 3D coordinate point P8).

In addition, as shown by the vector A1 and the vector A2, the three-dimensional coordinate point P9 and the three-dimensional coordinate point P10 in the point cloud data can also be matched according to the normal function of the relative position of the space vector, or according to the known two-dimensional or three-dimensional configuration sampling It is obtained by adjusting the function operation. According to the above, it can be seen that the curvatures of multiple regions used to construct the lens mold core can be constructed by obtaining point cloud data of corresponding regions through different function operations.

Then, the point cloud data obtained in step S21 of the lens construction method 200 (for example, three-dimensional coordinate points expressed in an orthogonal coordinate system) can be manufactured through processing formulas and processing machines according to steps S22-step S25 of the lens construction method 200 Moren's program.

According to the above, the lens construction method of the present disclosure can form a processing file through the point cloud data type, avoiding the mold core processing being limited by the definable parameters of the processing machine, and can adjust the optical characteristics of the lens more accurately. Therefore, with the lens construction method of the present disclosure, the stability of the astigmatic lens can be improved, and the time required for positioning the astigmatic lens can be reduced. In addition, constructing lenses based on point cloud data can improve the surface smoothness of the lenses and enhance wearing comfort.

Although this disclosure has been disclosed as above in the form of implementation, it is not intended to limit this disclosure. Anyone who is familiar with this technology can make various changes and modifications without departing from the spirit and scope of this disclosure. Therefore, the protection of this disclosure The scope shall be defined by the appended patent application scope.

100,200: lens construction method 110A, 110B: 3D model 112: optical zone 114: Outer area 116: Convex 118: Concave 120: Point cloud data 130: Processing formula 140: Processing machine P1, P2, P3, P4, P5, P6, P7, P8, P9, P10: three-dimensional coordinate points S: connect F: Curvature A1,A2: vector S11, S12, S13, S14, S15, S16, S21, S22, S23, S24, S25: steps

FIG. 1 is a flowchart of a lens construction method according to an embodiment of the present disclosure. FIG. 2A is a three-dimensional convex model of a lens mold core according to an embodiment of the present disclosure. FIG. 2B is a three-dimensional model of a lens concave mold core according to an embodiment of the present disclosure. FIG. 3 is a schematic diagram of a lens construction method using point cloud data according to an embodiment of the present disclosure. FIG. 4 is a flowchart of a lens construction method according to another embodiment of the present disclosure. FIG. 5 is a schematic diagram of a lens construction method using point cloud data according to another embodiment of the present disclosure.

100: Lens Construction Methods

S11, S12, S13, S14, S15, S16: steps

Claims (8)

A lens construction method, comprising: importing a little cloud data into a processing formula: using a processing machine to process a mold core according to the processing formula; and forming a mold with the mold core, and injecting medicine into the mold The lens is formed from a liquid, wherein the lens includes a plurality of regions, and the point cloud data corresponding to the regions are obtained through a combination of a plurality of three-dimensional models. The lens construction method as described in Claim 1, wherein the point cloud data is obtained through function calculation. The lens construction method as described in any one of claims 1 to 2, wherein the point cloud data includes a plurality of three-dimensional coordinate points, the lens includes a convex surface and a concave surface, and the convex surface and the concave surface each have a plurality of curvatures, and these The curvature is defined by the three-dimensional coordinate points. The lens construction method as described in any one of Claims 1-2, wherein the lens includes a plurality of areas, and the method further includes obtaining the point cloud data corresponding to these areas through different function calculations. The lens construction method according to any one of Claims 1-2, wherein the lens includes an optical zone, and the method further includes defining an optical characteristic of the optical zone by the point cloud data for correcting eyeball ametropia. The lens construction method according to any one of claims 1-2, wherein the lens includes a peripheral area, and the method further includes defining a thickness distribution of the peripheral area by using the point cloud data. The lens construction method according to any one of claims 1-2, further comprising adjusting the smoothness of the connection surfaces of the multiple regions of the lens by using the point cloud data. The lens construction method as described in Claim 1 further includes defining the directionality of the lens by the point cloud data.

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