Content measurement of textile mixture by Fourier transform near infrared spectroscopy

Li Liu; Li Yan; Yaocheng Xie; Songzhang Li; Ge Xia; Libin Zhou

doi:10.1117/12.838029

20 November 2009 Content measurement of textile mixture by Fourier transform near infrared spectroscopy

Li Liu, Li Yan, Yaocheng Xie, Songzhang Li, Ge Xia, Libin Zhou

Proceedings Volume 7511, 2009 International Conference on Optical Instruments and Technology: Optoelectronic Measurement Technology and Systems; 75110G (2009) https://doi.org/10.1117/12.838029
Event: International Conference on Optical Instrumentation and Technology, 2009, Shanghai, China

Abstract

A new method for accurate measurement of content of textile mixture based on Fourier transform near infrared spectroscopy is put forward. The near infrared spectra of 56 samples with different cotton and polyester contents were obtained, in which 41 samples, 10 samples and 5 samples were used for the calibration set, validation set and prediction set respectively. The wavelet transform (WT) was utilized for the spectra data compression. From the linear and nonlinear perspective, multivariable linear regression (MLR) model based on the Lambert - Beer's law and back propagation (BP) neural network model based on WT were developed. It indicates that the prediction accuracy of WT-ca3-BP network model is 2% for calibration sample and 4% for validation sample, which is much higher than the MLR model and is suitable for the prediction of unknown samples. On the basis of not changing the structure of the WT-ca3-BP network model, calibration and validation samples were utilized fully to be re-set to new calibration samples, which upgraded this model. The upgraded WT-ca3-BP network model was applied to predict unknown samples. Experimental results show that this approach based on Fourier transform Near Infrared Spectroscopy can be used to quantitative analysis for textile fiber.

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Li Liu, Li Yan, Yaocheng Xie, Songzhang Li, Ge Xia, and Libin Zhou "Content measurement of textile mixture by Fourier transform near infrared spectroscopy", Proc. SPIE 7511, 2009 International Conference on Optical Instruments and Technology: Optoelectronic Measurement Technology and Systems, 75110G (20 November 2009); https://doi.org/10.1117/12.838029

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KEYWORDS

Statistical modeling

Calibration

Neural networks

Near infrared

Near infrared spectroscopy

Fourier transforms

Photovoltaics

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