1.东北林业大学机电工程学院，黑龙江哈尔滨 150040
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管雪梅,李文峰,黄静一.基于Stearns-Noechel优化模型的木材单板染色配方预测[J].木材科学与技术,2021,35(05):18-23.
GUAN Xue-mei,LI Wen-feng,HUANG Jing-yi.Prediction of Wood Veneer Staining Formulations Based on Stearns-Noechel Optimization Model[J].Chinese Journal of Wood Science and Technology,2021,35(05):18-23.
以樟子松单板为染色基材，采用活性染料对其进行染色，获取3组单色染料染色样本与8组混合染料染色样本。将自适应权值粒子群算法（APSO）与Stearns-Noechel模型结合，对8组混合染料染色样本进行染色配方预测。结果表明：采用APSO预测的配方绝对偏差均小于0.1，约为最小二乘法和传统粒子群算法的1/2；迭代次数约为传统粒子群算法的60%，寻优速度较快。优化模型获得三种珍贵材的R-Y-B染色配方分别为：花梨木—0.192%，0.419%，0.082%；鸡翅木—0.137%，0.284%，0.193%；黑酸枝—0.336%，0.581%，0.204%。采用该配方对樟子松单板进行染色，染色拟合样与标准样间的色差均小于2，且两者光谱反射率间的误差小，染色效果较好。
Pinus sylvestris, veneer was used as the staining base material, which was stained with reactive dyes. Three groups of single-dyed samples and eight groups of mixed-dyed samples were obtained. Using the adaptive particle swarm algorithm (APSO) combining with the Stearns-Noechel model, the dyeing formula were predicted for eight groups of mixed-dyed samples. The results showed that the absolute deviation of formula obtained by APSO was less than 0.1, which was about 1/2 of the least square method and the traditional particle swarm algorithm. The optimization speed was efficient, and the number of iterations was about 60% of that of the traditional particle swarm optimization algorithm. The R-Y-B dyeing formulas of the three precious wood species obtained through by the optimized model were 0.192%, 0.419%, 0.082% for rosewood; 0.137%, 0.284%, 0.193% for wenge wood; and 0.336%, 0.581%, 0.204% for black rosewood. Using this formula of dyeing camphor pine veneer, the color difference between the dye fitting sample and the control sample were less than 2, and the error between the spectral reflectance of both was small. The performance of dyeing was fine.
Stearns-Noechel模型自适应权值粒子群算法木材单板配方预测配方绝对偏差
Stearns-Noechel modeladaptive particle swarm algorithm (APSO)wood veneerformula predictionabsolute deviation of formula
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