1. 北京服装学院材料设计与工程学院
2. 北京服装学院服装艺术与工程学院
3. 东华大学材料科学与工程学院
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郑佳辉, 杜宇君, 李文霞, 等. 废旧聚酯/棉混纺织物的在线近红外定量分析与自动分选[J]. 分析测试学报, 2020,39(11):1365-1370.
Online Near-infrared Quantitative Analysis and Automatic Sorting of Waste Polyester/Cotton Blend Fabrics[J]. 2020,39(11):1365-1370.
在前期探究的最佳测试条件下,利用自主研制的“纤维制品主体组分高效识别与分选装置”对废旧聚酯/棉混纺织物样品进行在线原始近红外光谱采集。基于在线原始谱图,探讨出最佳光谱预处理方法为S-G平滑+最大最小归一化(MMN)+S-G导数,并利用偏最小二乘法建立了废旧聚酯/棉混纺织物的在线近红外定量分析模型,模型的交互验证均方根误差(RMSECV)为1.47,校正相关系数(RC)、验证相关系数(RV)值均不小于0.99,校正相对预测偏差(RPDC)为18.17,验证相对预测偏差(RPDV)为13.13,交互验证相对预测偏差(RPDCV)为11.76。为验证模型的可靠性,选取30个外部样本进行在线验证,验证结果的线性方程为y=(1.00±0.01)x-(0.88±0.56),预测准确率为93.3%。将模型导入分选装置的“纺织品在线主控程序”后,对设备设定不同聚酯含量织物的分选类别,即可对废旧聚酯/棉混纺织物样本进行含量预测,并通过装置的吹分分选系统将样品自动吹扫到相应的收集框中。每个样品预测并分选的时间小于2 s,机械自动分选结果无误。利用所建模型和分选装置可对废旧聚酯/棉混纺织物进行在线高效测定与自动分选。
Under the optimal test conditions explored in the early stage,the online original near infrared spectrum for the polyester/cotton blend fabrics samples was collected using a self developed “high efficiency identification and sorting device for the main components of fiber products”.Based on the original online spectrogram,an optimal spectral pretreatment method was proposed as S-G smoothing+MMN+S-G derivative.Meanwhile,an online near infrared quantitative analysis model for polyester/cotton blend fabrics was established by partial least square method.The root mean standard error of cross validation(RMSECV) was 1.47,the correlation coefficient of calibration(RC) and correlation coefficient of validation(RV) were not less than 0.99,the relative predictive deviation of calibration(RPDC) was 18.17,the relative predictive deviation of validation(RPDV) was 13.13,and the relative predictive deviation of cross validation(RPDCV) was 1176.To verify the reliability of the model,30 external samples were selected for online verification.The linear equation for the verified results was y=(1.00±0.01)x-(0.88±0.56),with an accurate rate of 93.3%.After importing the model into the “textile online master control program” of the sorting device,the sorting category of the equipment was set for different polyester content fabrics,then the content prediction for the polyester/cotton fabrics samples were performed,and the samples were automatically purged into the corresponding collection frame through the device's blowing and sorting system.The time for each sample to be predicted and sorted was less than 2 s,and the automatic mechanical sorting result was correct.Therefore,the established model and sorting device could be used for efficient online measurement and automatic sorting of waste polyester/cotton blended textiles.
废旧纺织品在线近红外定量分析模型高效识别自动分选
waste textilesonline near infraredquantitative analysis modelefficient identificationautomatic sorting
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