Research On Numerical Analysis For Textile Dyeing Color Matching Based On Ideal Dye

The color matching for textile dyeing is a complex nonlinear problem. As the neural network is an effective solving tool for nonlinear problem, many researchers have used it in computer color matching and have achieved some result. However, there are still many short comings on using neural network method, such as the neural network easy to fall into local minimum and its generalization ability is relatively low.In order to overcome the deficiencies of the existing color matching methods, some problems related to color matching were analyzed and abstracted in this article on the basis of the matching characteristics in textile dyeing and the color hybrid theory. Extraction of the main factors created a preliminary computer matching model based on textile dyeing.The relationship between the CMY value and the concentration of the simple dye was built by using interpolation methods. Then this paper establishes a computer color matching model based on a kind of ideal dye. And the numerical analysis method was used to get the parameters of this model. Then the model was verified and the errors were analyzed. The result of the verification suggests that the model can reflect a correctly relationship between the concentration of simple dyes and the CMY value of the mixed sample.In order to have a comparison for the model, particle swarm optimization algorithm was applied to the neural network in this paper, and the results of this method were compared with the results of the numerical analysis method. The numerical analysis method was proved to be more effective from the results.The computer color matching method which based on numerical analysis is feasible. This method provides a new theory reference about the problem of color matching in textile dyeing, and it has a certain theoretical and practical application value.