Neural Network Coating Sparkle Prediction
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Solution Overview
Problem
The traditional method for matching the color and appearance of coatings containing effect pigments, such as metallic flakes, is labor-intensive and inefficient, requiring repeated spraying and visual comparison of test panels to achieve satisfactory color and sparkle matching at various angles of illumination and viewing.
Innovation Solution
A process utilizing an artificial neural network trained with data on color characteristics and sparkle values of training coatings to predict and produce target sparkle values for a target coating composition, allowing for the automated generation of matching coatings without the need for repetitive testing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional manual method with repeated spraying and visual comparison is used, then color and sparkle matching can be achieved, but labor time and processing time are excessive
Solution Approach 1:
The patent replaces the manual mechanical process of spraying and visual comparison with an automated optical measurement system using a spectrophotometer to measure color values (L*, a*, b*) and sparkle values, and a neural network algorithm to calculate flake parameters, thereby eliminating the need for repeated manual spraying and visual assessment
Solution Approach 2:
The patent creates a digital model (neural network) that learns from training data the relationship between coating formulation and appearance properties, allowing the system to predict and match sparkle appearance without physically creating multiple test panels through repeated spraying cycles
2Measurement precision
If traditional manual selection of effect pigments is used, then expertise-based matching can be achieved, but the process requires experienced shaders and is not scalable
Solution Approach 1:
The patent replaces the human expert's manual selection process with an automated neural network system that objectively measures color and sparkle values and calculates optimal flake parameters based on learned relationships from training data, eliminating dependence on individual shader expertise
Solution Approach 2:
The patent transforms the subjective expert judgment process into an objective parameter-based system that measures and optimizes specific quantifiable parameters (L*, a*, b* color values, sparkle values, flake size distribution, flake concentration) through automated measurement and calculation
3Manufacturing precision
If repeated test panel spraying is performed to achieve satisfactory match, then color and appearance matching can be improved, but material waste and cost increase
Solution Approach 1:
The patent performs preliminary measurement and calculation using the neural network model to predict the optimal coating formulation and sparkle appearance before actual production spraying, thereby avoiding the need for multiple test panel sprays that waste coating materials
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
This approach significantly reduces the labor and time required for matching coatings by enabling the prediction of sparkle values, allowing for precise formulation adjustments and eliminating the need for laborious spray-out and drying cycles, while improving the accuracy of color and sparkle matching across different angles.
Implementation Method 1
a spectrophotometer to measure the spectral reflectance of a standard panel and a plurality of coating samples
Implementation Method 2
The sparkle appearance of a coating can be enhanced by the addition of a fluorescent brightener to the coating formulation
Data Source
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Figure 3A
AI summary
This disclosure is directed to a process for producing one or more predicted target sparkle values of a target coating composition. An artificial neural network can be used in the process. The process disclosed herein can be used for color and appearance matching in the coating industry including vehicle original equipment manufacturing (OEM) coatings and refinish coatings. A system for producing one or more predicted target sparkle values of a target coating composition is also disclosed.