机器视觉在线测量复合材料中的颗粒填料含量  

Machine Vision Online Measurement of the Particle Filler Content in Composites

作　　者：李康明 晋刚 Li Kangming;Jin Gang(National Engineering Research Center for New Polymer Forming Equipment,Key Laboratory of Polymer Processing Engineering(Ministry of Education),Guangzhou 510640,China)

机构地区：[1]华南理工大学聚合物新型成型装备国家工程研究中心,聚合物成型加工工程教育部重点实验室,广东广州510640

出　　处：《广东化工》2022年第7期181-183,共3页Guangdong Chemical Industry

基　　金：国家重点研发计划(2019YFB1704902)。

摘　　要：利用单螺杆挤出机在稳定的温度和转速下挤出聚丙烯(Polypropylene,PP)/玻璃微珠(Glassbeads,GB)复合材料,结合目标检算法定义了玻璃微珠的等效粒径,通过数学关系计算出玻璃微珠的实际填料含量,并分析了填料粒径、填料含量对组分含量测量结果的影响。结果表明机器视觉在线测量组分含量结果的平均相对误差为0.054,与离线灰分法测量结果相近,玻璃微珠的填料粒径越大、含量越低,机器视觉测量组分含量的结果越准确。Polypropylene(PP)/glass beads(GB) composites were extruded by single screw extruder at stable temperature and speed. Combined with the target detection model, the equivalent particle size of glass beads was defined, and the real filler content of glass beads was calculated through mathematical relationship.The effects of filler particle size and content on the measurement results of component content are analyzed. The results show that the average relative error of component content on-line measured by machine vision is 0.054, which is similar to that measured by off-line ash method. The larger the filler particle size and the lower the content of glass beads, the more accurate the result of component content measured by machine vision.

关 键 词：复合材料 机器视觉 目标检测 填料含量 填料粒径 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] TB33[自动化与计算机技术—计算机科学与技术]