棉织物染色配方工艺优化方法研究  

Cotton Fabric Dyeing Formulation Optimization

作　　者：汪岚[1] 汤仪平[1] 陈海洋[1] Wang Lan;Tang Yiping;Chen Haiyang(College of Intelligent Manufacturing Engineering,Liming Vocational University,Quanzhou,Fujian 362000,China)

机构地区：[1]黎明职业大学智能制造工程学院,福建泉州362000

出　　处：《针织工业》2020年第3期48-52,共5页Knitting Industries

基　　金：泉州市高层次人才创新创业项目(2019C045R).

摘　　要：为了实现棉织物染色配方和工艺参数的优化设计,研究了一种应用智能混合算法优化求解的新方法。首先构建棉织物染色配方工艺优化的数学模型,再利用自适应调整和相似度判别策略等关键手段对基本遗传算法进行了改进并融合了模拟退火算法形成智能混合算法,最终将智能混合算法应用到优化模型的求解中,以达到配方和工艺优化的目的。结果表明,优化模型可靠有效,智能混合算法的收敛速度、寻优能力和稳定性都得到了改善。应用智能混合算法求解的配方和工艺参数染色,其效果明显优于传统遗传算法,不仅与样布的色差值缩小了6.47%且成本降低2.16%以上。该方法可为棉织物染色过程中的质量控制以及工艺参数快速优化设计提供理论指导。In order to achieve the optimal design for cotton fabric dyeing formulation and its technological parameter, a new method with IHA(intelligent hybrid algorithm) was introduced. Firstly, a mathematical model of optimal fabric dyeing formulation was established. And then GA(genetic algorithm) was improved by the essential operations such as self-adaptive adjustment and fitness similarity discrimination strategy. Finally, combining the improved GA with the simulated annealing algorithm, IHA was applied into the solution of the optimal model. The results show that the model is reliable and efficient. The convergence rate, and the search capability and stability of IHA are improved. The dyeing formulation and technological parameter obtained by IHA are better than GA: the chromatism decreases by more than 6.47%;and the cost reduces by more than 2.16%. This method provides theoretical guidance for quality control and rapid parameter setting of dyeing production process.

关 键 词：棉织物 染色配方工艺 自适应调整 相似度判别策略 改进遗传算法 模拟退火算法 智能混合算法 

分 类 号：TS193[轻工技术与工程—纺织化学与染整工程]