Research On Data Correlation Analysis Method For Color Matching In Textile Dyeing Based On Polynomial Curve Fitting

The theory of numerical analysis and polynomial fitting is introduced into the process of dyed sample and dye concentration in order to overcome the defects of the traditional dyeing process and to improve the speed and accuracy. Based on the theory of color mixing, a large number of experimental data are analyzed and processed in the paper, with the Matlab mathematical toolbox as the modeling aided tool to elaborate the mathematical relationship between the different concentrations of dyeing sample and tristimulus values CMY. By a number of mathematical verification, error of the mathematical model researched in this paper is small, which can be applied to the production of actual dyeing with more accurate result.The first chapter introduces the background and significance, historical review, development direction and current status, focusing on the analysis of innovation for the paper. The second chapter outlines the basic theory of optics and chromatics, which is involved in textile color matching theory. The chapter introduces different technologies and methods of computer color matching, and basic knowledge and the selecting criteria of dye used in the theoretical research. The third chapter introduces the mathematical theory in the experiment, including mathematical modeling, numerical analysis and regression analysis. The fourth chapter is the realization process of the research. The chapter introduces the sources of experimental data, as well as indicators and results of data processing. Consequently, mathematical relation between data is found. After establishing a suitable model and its solution, the final results are obtained.Through this study, the mathematical model of data correlation analysis and polynomial fitting can resolve textile color matching problem very well. Based on different numerical analysis, specific relationship between data is found, which provides more powerful foundation for establishing the mathematical model. With less error, the mathematical model is more accurate and has great guiding significance on theoretical study and actual production.