Object Surface Correction for Predictive Machined Appearance
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Solution Overview
Problem
Current methods for evaluating the aesthetic quality of machined surfaces based on image data do not allow for precise prediction of how the surface will be perceived by the human eye, making it difficult to achieve a desired aesthetic in advance.
Innovation Solution
A method that predicts how the shape of an object surface will be visually recognized by the human eye by calculating luminance and angular distribution of reflected light, allowing for adjustments in machining parameters to create the desired aesthetic, including changes in tool path, machining conditions, and correction parameters.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If image data obtained by photographing the machined surface is used for evaluation, then the quality of machined surface can be judged after machining, but the aesthetics of the shape of the object surface cannot be precisely predicted in advance
Solution Approach 1:
The patent calculates luminance and spatial frequency from 3D shape data before machining occurs, enabling aesthetic prediction in advance. This preliminary calculation allows the system to determine whether machining will produce acceptable aesthetics without waiting for actual machining and photographing, thus resolving the timing contradiction.
Solution Approach 2:
The patent replaces the mechanical/optical system of photographing and image processing with a computational system that calculates luminance and spatial frequency directly from 3D shape data using human visual system characteristics. This substitution enables precise aesthetic prediction without requiring actual physical measurement after machining.
2Manufacturing precision
If the shape of the machined surface is corrected based on post-machining evaluation, then the desired aesthetic can be achieved, but the machining process becomes less efficient
Solution Approach 1:
The patent performs aesthetic evaluation calculations before machining based on predicted 3D shape data, allowing corrections to be made to the machining program in advance. This prevents unnecessary machining operations and enables the first-pass production of aesthetically acceptable surfaces, thereby improving productivity while maintaining manufacturing precision.
3Manufacturing precision
If the relationship between shape and perceived aesthetics is not understood, then machining parameters cannot be optimized, but understanding this relationship requires complex human visual system modeling
Solution Approach 1:
The patent transforms the complex problem of human visual perception into calculable parameters: luminance (based on surface normal vectors and light sources) and spatial frequency (based on surface curvature variations). By changing the representation from complex visual modeling to these fundamental parameters, the system achieves aesthetic control without excessive complexity.
Solution Approach 2:
The patent applies the concept of visual perception characteristics (analogous to color changes) by incorporating the contrast sensitivity function into the evaluation. This allows the system to weight different spatial frequencies according to human visual sensitivity, achieving accurate aesthetic prediction while maintaining computational simplicity.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables accurate prediction and correction of machined surface aesthetics, allowing for the creation of desired visual appearances during the machining process, improving the efficiency and quality of machined surfaces.
Implementation Method 1
calculating luminance and angular distribution of reflected light
Implementation Method 2
based on the contrast and the spatial frequency, it is determined, using a contrast sensitivity function, whether or not the contrast of the machined surface can be detected by the human eye
Data Source
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AI summary
In the present invention: a plurality of meshes are defined on an object surface; the luminance of the object surface when the object surface is viewed from a viewpoint position is calculated for each of the plurality of meshes on the basis of data concerning a processed shape, a surface roughness curve, the viewpoint position, the direction, angle distribution, and intensity of incident light onto the object surface, and a reflectance and scattering characteristics for each wavelength on the object surface; the shape of the object surface is displayed on the basis of the luminances; and data concerning at least the object shape or the surface roughness curve is corrected so as to obtain a desired appearance of the object surface.