Research On Fabric Intelligent Color Matching System Based On Intelligent Optimization Algorithm

The research of fabric intelligent color matching system occupies an important place in the textile field.The quality of dyed fabrics is largely determined by the accuracy of the color matching process.The most widely used color matching method is based on the color tristimulus value,but this color matching method has unavoidable shortcomings.The predicted result may show metamerism after dyeing the fabric.In addition,modern dyeing technology and equipment also have great limitations.The fabric color matching is not accurate,efficient,and the process is cumbersome.Now the textile industry uses cutting-edge intelligent optimization algorithms to complete the research on efficient and accurate color matching of fabrics.Under the trend of optimization of existing color matching algorithms and technologies,this paper proposes the use of genetic algorithms for intelligent color matching of fabrics.The relevant color matching algorithms proposed in this paper can predict the corresponding formula very well according to the experimental results,and the color difference is small,which improves the success rate of a proofing.It not only improves the process of fabric color matching,but also improves the color matching quality and cost.The main research contents of this paper are as follows:1.The color matching model based on genetic algorithm and K/M single constant theory is studied.Then the least square method and the K/M single constant theory are combined to solve the K/S value and the fabric formula intelligent prediction based on the genetic algorithm,and the corresponding experiment based on the proposed method is completed.2.The method of fabric intelligent color matching based on the combination of BP neural network and genetic algorithm is studied.The thesis first introduces the color matching model based on BP neural network,and then proposes the combination of BP neural network and genetic algorithm,using BP neural network as the fitness function of genetic algorithm,and finally uses the proposed algorithm to achieve the prediction experiment of smart color matching of fabrics is carried out.3.The fabric intelligent color matching prediction based on simulated annealing algorithm and improved genetic algorithm is studied.Analyze the simulated annealing algorithm,and then proposed the method of the GA algorithm improved by SA algorithm to fabric intelligent color matching.The mutation probability of the genetic algorithm is uncertain,so we use the simulated annealing algorithm to adjust it.Based on this algorithm,the related experimental research of fabric intelligent color matching is completed.4.The fabric intelligent color matching model based on KNN classification multi-path optimization genetic algorithm is studied.It is proposed to use the KNN algorithm to classify the basic data with large differences,and then the multi-path genetic algorithm is used to simultaneously predict the color matching according to the different sets of data classified,and the intelligent color matching prediction experiment of the fabric based on the multi-path genetic algorithm based on the KNN classification is completed.5.The multi-cloth intelligent color matching prediction model combining adaptive genetic algorithm and SA algorithm is studied.This chapter proposes the simulated annealing algorithm to optimize the adaptive genetic algorithm.Considering the different effects of dyeing different fabrics with the same formula concentration,the fitness function of the adaptive genetic simulation algorithm is optimized so that it can adapt to the cloth,and finally realize the intelligent color matching prediction of multiple cloths based on the adaptive genetic simulated annealing algorithm.And completed the design and development of the fabric intelligent color matching system based on this algorithm.