BP神经网络优化Stearns-Noechel模型的羊毛色纺纱配色  

BP neural network optimization of Stearns-Noechel model for color matching of wool color spinning yarns

作　　者：史帅杰 李启正[1] 裘柯槟 朱杰 张斌 纪乐福 陈维国 SHI Shuaijie;LI Qizheng;QIU Kebin;ZHU Jie;ZHANG Bin;JI Lefu;CHEN Weiguo(College of Textile Science and Engineering,Zhejiang Sci-Tech University,Hangzhou,Zhejiang 310018,China;Jiaxing South Lake College,Jiaxing,Zhejiang 314001,China;Zhejiang Zhongding Textile Technology Co.,Ltd.,Jiaxing,Zhejiang 314511,China;Tongxiang Research Institute of Zhejiang Sci-Tech University Co.,Ltd.,Jiaxing,Zhejiang 314599,China)

机构地区：[1]浙江理工大学纺织科学与工程学院,浙江杭州310018 [2]嘉兴南湖学院,浙江嘉兴314001 [3]浙江中鼎纺织科技有限公司,浙江嘉兴314511 [4]浙江理工大学桐乡研究院有限公司,浙江嘉兴314599

出　　处：《毛纺科技》2024年第4期111-117,共7页Wool Textile Journal

基　　金：中国纺织工业联合会科技指导性计划项目(2023028)。

摘　　要：为了提升羊毛色纺纱配色的精确度,通过数理统计方法研究颜色特征中的色相、明度、饱和度与Stearns-Noechel模型参数M值之间的关系,采用BP神经网络对Stearns-Noechel模型参数M值进行优化,并与传统的最优平均M值和波长优化M值等方法进行对比。结果表明:采用BP神经网络优化Stearns-Noechel模型的配色方法比其他2种传统优化方法在颜色预测精确度上都有提高。在99个羊毛混色纱试验样本中,BP神经网络优化方法得到的平均色差最小,为1.1773,其中色差小于1的样本占54%,结合颜色特征采用BP神经网络优化的Stearns-Noechel模型参数具有较好的效果,对羊毛色纺纱的颜色预测精确度有较大的提高。In order to improve the accuracy of color matching of wool color spinning yarns,the relationship between hue,brightness,saturation in color characteristics,and the parameter M value of the Stearns-Noechel model was investigated by mathematical and statistical methods.The parameter M value of the Stearns-Noechel model was optimized by using the backpropagation(BP)neural network,and compared with the traditional methods such as the optimal average M value and the wavelength-optimized M value.The results show that the optimization of color matching methods of the Stearns-Noechel model using the BP neural network has some improvement in color prediction accuracy than the other two traditional optimization methods.Among 99 samples of wool color-blended yarns,the BP neural network optimization method obtained the smallest average color difference of 1.1773.In addition,54%of these samples had a color difference of less than 1.This indicates that the use of combining color features and the optimization of parameters of the Stearns-Noechel model using the BP neural network has good results and significantly improves the accuracy of color prediction accuracy of wool color-blended yarns.

关 键 词：色纺纱 Stearns-Noechel模型 BP神经网络 颜色预测 颜色特征 

分 类 号：TS193.1[轻工技术与工程—纺织化学与染整工程]