基于NIR混合废塑料识别仪分选效率的模型

通过对近红外光谱（NIRS）识别分选混合废塑料的过程建立数学模型，将经过预处理的废塑料在传送带上的分布分为密集区和稀疏区两大类。以降低分选时间，提高分选效率为研究目的，对影响分选效率的因素进行分析，如分选机所能承受物料密集度上限值θ以及传送带的传输速度V等因素。比较不同θ和V的组合对总分选时间T的影响，通过数值计算并验证，求得最优组合解。研究结果表明：θ的大小影响密集区和稀疏区的面积在总面积中占有量的变化；分选总时间T在θ和V共同变化过程中存在极小值。

Model of mixed waste plastics about identification and sorting method based on the near-infrared

In this research,a mathematical model was established for NIRS identification and the separation process of mixed waste plastics.The distribution of pretreated waste plastics on the conveyor belt was divided into the dense area and the sparse area.Aiming at reducing the separation time and improving the efficiency of the separation,the research analyzed the effects of the upper limit value θ of the material intensity on the sorting machine,and the transmission speed V of the conveyor belt,and other factors.Moreover,the influence of different combinations of θ and V on the total separation time T was compared.The optimal combination solution was finally obtained by numerical calculation and verification.The results show that the size of θ can affect the occupancy changes of the dense area and the sparse area of the total area,respectively.There is a minimum value to total time T during the process of the simultaneous change of θ and V.