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双组分织物含水率的微波谐振腔法测量技术

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针对染整过程中多组分织物含水率准确检测问题,提出了一套基于微波谐振腔法的织物含水率检测系统.首先,基于Bruggeman-Hanai介电混合模型,结合织物结构特征建立了单组分织物含水率与介电常数的关系模型;通过考虑织物厚度与多组分织物组分配比的影响,建立了双组分织物含水率介电常数模型.接着,开展湿度均匀的纯棉、涤纶、混纺织物的介电常数测量实验,采用贝塞尔拟合方法,得到双组分织物介电常数模型的系数,从而获得了不同材质、厚度、组分配比下织物含水率与介电常数的关系模型.通过比较实验织物样品含水率与理论模型预测结果发现,二者吻合较好,均方根误差小于5%,从而验证了双组分织物含水率介电模型的可行性,为后续纺织品含水率检测提供技术支撑.
Moisture content measurement technology of two-component fabrics by microwave resonant cavity method
Objective For detecting the moisture content of fabric accurately,it is critical to understanding the relationship between moisture content and dielectric constant of fabrics.The objective of this study is to establish the relationship between moisture content and dielectric constant for two-component fabrics with different materials,thicknesses and component ratios,aiming for accurate measurement of moisture content in different types of textiles.Method Based on the Bruggeman-Hanai dielectric mixing model,the relationship between the dielectric constant model of water content of two-component fabric was developed by considering the influence of fabric thickness and the pro-portion of multi-component fabric components under different material,thickness and component ratio was obtained.The dielectric constant measurement experiments of cotton,chemical fiber and blended fabric with uniform humidity were carried out,and the coefficient of the dielectric constant model of the two-component fabric was obtained.Results For the theoretical prediction model,when the depolarization factor coefficient of pure cotton fabric L1=0.35 and the depolarization factor coefficient of chemical fiber fabric L2=0.23,the comparison results of the moisture content prediction model of pure cotton and chemical fiber cloth and experimental data were able to be obtained.The root mean square error(RMSE)calculation was carried out and it was found that the theoretical model RMSE of different fabric materials was less than 3%,and hence the prediction on the relationship between moisture content and dielectric constant,for pure cotton and chemical fiber fabrics,was proven reliable.When the cotton fabric coefficient C1(the ratio of the thickness coefficient of pure cotton fabric to its thickness)was 1.475,B1(the correction factor for pure cotton fabric)was 0.683 3;and when polyester fiber fabric C2(the ratio of the thickness coefficient of blending textiles to their thickness)was 1.567,and B2(the correction factor for synthetic fabrics)was 0.743 2.For cotton fabrics,the RMSE ≤4.6%.Comparison of the prediction results of the model to the experimental results showed that the model enabled a good prediction on the permittivity related to the thickness of cotton fabrics.For chemical fiber fabrics where RMSE ≤ 3.8%,the prediction of fabrics with larger thickness and lower moisture content was not as good.However,when the moisture content of the fabric was greater than 3%,the prediction was generally better.When the determinant of blended fabric α=0.67,for fabrics with cotton content between 20%-35%,the prediction results of the two-component fabric theoretical model were close to the experimental results,and the prediction was better.Conclusion In order to accurately measure the moisture content of fabrics with different materials,varying thickness and diversified components,this research explores the influence of changes in fabric material,thickness and composition ratio on moisture content and permittivity based on the microwave resonator method,and then establishes a theoretical model of fabric moisture content permittivity.After comparing and analyzing the predicted value of the model and the experimental value,results show that the model has good prediction accuracy,the RMSE is less than 5%.

fabricmoisture contentresonant cavitydielectric constantmathematical model

向忠、赵唯、何仕伟、王宇航、钱淼

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浙江理工大学浙江省现代纺织装备技术重点实验室,浙江杭州 310018

织物 含水率 微波谐振腔技术 介电常数 数学模型

国家自然科学基金项目浙江省"尖兵""领雁"研发攻关计划项目浙江省"尖兵领雁+X"研发攻关计划项目浙江省"尖兵领雁+X"研发攻关计划项目浙江理工大学基本科研业务费专项资金资助项目

516054432023C011582024C012222024C0311822242298-Y

2024

纺织学报
中国纺织工程学会

纺织学报

CSTPCD北大核心
影响因子:0.699
ISSN:0253-9721
年,卷(期):2024.45(4)
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