Wood-plastic composite (WPC) is a promising and sustainable material, and refers to a combination of wood and plastic along with some binding (adhesive) materials. In comparison to pure wood material, WPCs are in general have advantages of being cost effective, high durability, moisture resistance, ...
Wood-plastic composite (WPC) is a promising and sustainable material, and refers to a combination of wood and plastic along with some binding (adhesive) materials. In comparison to pure wood material, WPCs are in general have advantages of being cost effective, high durability, moisture resistance, and microbial resistance. The properties of WPCs come directly from the concentration of different components in composite; such as wood flour concentration directly affect mechanical and physical properties of WPCs. In this study, wood powder concentration in WPC was determined by Fourier transform near-infrared (FT-NIR) and Fourier transform infrared (FT-IR) spectroscopy. The reflectance spectra from WPC in both powdered and tableted form with five different concentrations of wood powder were collected and preprocessed to remove noise caused by several factors. To correlate the collected spectra with wood powder concentration, multivariate calibration method of partial least squares (PLS) was applied. During validation with an independent set of samples, good correlations with reference values were demonstrated for both FT-NIR and FT-IR data sets. In addition, high coefficient of determination (${R^2}_p$) and lower standard error of prediction (SEP) was yielded for tableted WPC than powdered WPC. The combination of FT-NIR and FT-IR spectral region was also studied. The results presented here showed that the use of both zones improved the determination accuracy for powdered WPC; however, no improvement in prediction result was achieved for tableted WPCs. The results obtained suggest that these spectroscopic techniques are a useful tool for fast and nondestructive determination of wood concentration in WPCs and have potential to replace conventional methods.
Wood-plastic composite (WPC) is a promising and sustainable material, and refers to a combination of wood and plastic along with some binding (adhesive) materials. In comparison to pure wood material, WPCs are in general have advantages of being cost effective, high durability, moisture resistance, and microbial resistance. The properties of WPCs come directly from the concentration of different components in composite; such as wood flour concentration directly affect mechanical and physical properties of WPCs. In this study, wood powder concentration in WPC was determined by Fourier transform near-infrared (FT-NIR) and Fourier transform infrared (FT-IR) spectroscopy. The reflectance spectra from WPC in both powdered and tableted form with five different concentrations of wood powder were collected and preprocessed to remove noise caused by several factors. To correlate the collected spectra with wood powder concentration, multivariate calibration method of partial least squares (PLS) was applied. During validation with an independent set of samples, good correlations with reference values were demonstrated for both FT-NIR and FT-IR data sets. In addition, high coefficient of determination (${R^2}_p$) and lower standard error of prediction (SEP) was yielded for tableted WPC than powdered WPC. The combination of FT-NIR and FT-IR spectral region was also studied. The results presented here showed that the use of both zones improved the determination accuracy for powdered WPC; however, no improvement in prediction result was achieved for tableted WPCs. The results obtained suggest that these spectroscopic techniques are a useful tool for fast and nondestructive determination of wood concentration in WPCs and have potential to replace conventional methods.
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제안 방법
4 mm. Also, PLS-R was done to determine correlation between status and spectrum.
A single beam spectra before each sample was measured against air as a background. In order to eliminate the influence of residual from preceding sample, both ATR crystal and pointed tip were cleaned before measuring the new sample. The spectra collection was done by using OMNIC software.
In this study, WPC was provided by Ilsam Corporation (Korea) in two different forms: powder and tablet / pellet and with five different volume fraction of wood powder; 40, 45, 50, 55, and 58%. Other than wood powder, the WPC consist of coupling agent (2.
Therefore, preprocessing of spectral data has a great importance in chemometrics modeling. In this work, to correct unwanted signals, both FT-NIR and FT-IR raw spectra were preprocessed with seven different preprocessing methods and can be divided into two categories: scatter correction methods includes normalization (mean, maximum, and range), multiplicative scatter correction (MSC) and standard normal variate (SNV), and smoothing method includes Savitzky-Golay (SG) 1st and 2nd derivatives. The normalization methods generally adopted to suppress the variability in the spectra caused by scattering effect influenced by morphological changes among the sample (Fearn et al.
The aim of the present feasibility study was to evaluate the potential of FT-NIR and FT-IR spectroscopies, in combination with the application of multivariate calibration method of partial lease squares regression analysis to determine the wood powder concentration in WPC. Moreover, joint use of NIR and MIR region was evaluated for developing prediction model with the aim of to improve the prediction accuracy.
The aim of the present feasibility study was to evaluate the potential of FT-NIR and FT-IR spectroscopies, in combination with the application of multivariate calibration method of partial lease squares regression analysis to determine the wood powder concentration in WPC. Moreover, joint use of NIR and MIR region was evaluated for developing prediction model with the aim of to improve the prediction accuracy.
This study is trying to use non-destructive measuring method as like the existing method, and it is focused on improving accuracy and rapidly measurement by using FT-NIR method. Results of FT-NIR was analyzed Partial Least Squares Regression (PLS-R) to determine correlations between spectrum and wood flour contents.
, 2015). Thus, in this study, spectral data are first corrected manually by removing the unnecessary spectral region followed by the different preprocessing treatments, and finally, a multivariate calibration model of partial least square regression (PLS-R) was developed to predict the added plastic concentration in WPC samples. MATLAB software version 7.
대상 데이터
FI-IR measurements were taken with a Nicolet 6700 (Thermo Scientific Co.) FT-IR spectrometer with a resolution of 4 cm-1 and an average of 32 scans. The collected spectral data covers a spectral range from 4,000 - 650 cm-1 and a total of 1738 Variables (wavebands).
) FT-IR spectrometer with a resolution of 4 cm-1 and an average of 32 scans. The collected spectral data covers a spectral range from 4,000 - 650 cm-1 and a total of 1738 Variables (wavebands). The FT-IR spectrometer was equipped with an attenuated total reflectance (ATR) accessory sampling technique which uses the phenomenon of total internal reflection.
데이터처리
This study is trying to use non-destructive measuring method as like the existing method, and it is focused on improving accuracy and rapidly measurement by using FT-NIR method. Results of FT-NIR was analyzed Partial Least Squares Regression (PLS-R) to determine correlations between spectrum and wood flour contents. The wave length of FT-NIR was 1,000 - 2,500 mm, and two different status of samples are used.
The added plastic concentration in WPCs has been evaluated because of the great practical importance of this concern. Spectral data were collected using FT-NIR and FT-IR spectroscopies and evaluated through multivariate analytical method of partial least squares regression (PLS-R) approach to predict plastic concentration in WPCs. The presented results demonstrated that both FT-NIR and FT-IR spectroscopies combined with PLS-R is a useful tool for a rapid and reliable estimation of the plastic contents in WPCs.
이론/모형
The collected spectral data covers a spectral range from 4,000 - 650 cm-1 and a total of 1738 Variables (wavebands). The FT-IR spectrometer was equipped with an attenuated total reflectance (ATR) accessory sampling technique which uses the phenomenon of total internal reflection. The reflectance spectra were collected by placing the sample on diamond crystal sampling plate clamped with a pointed tip.
Before combining the spectra, unwanted regions from both FT-NIR and FT-IR spectra were discarded. Therefore, two PLS-R model, one with powder and another with tableted WPCs samples were developed with combined spectra without using any-preprocessing method. Table 4 shows the calibration and prediction results obtained for combined spectra.
성능/효과
3 plots the data from actual concentration against the PLS-R predicted concentration for plastic content in WPC. PLS-R result obtained for FT-NIR data yield a good relationship (R2p = 0.87) between actual and predicted concentration values for tablet samples; however, a relatively low coefficient of determination (R2p= 0.75) and high standard error of prediction (SEP = 3.4) for powder samples was obtained using PLS-R model. The comparatively lower prediction accuracy for FT-NIR data of powder samples may be because of the fact that the variation in particle size highly influence the spectral data and lead to the missclassification or poor prediction.
참고문헌 (20)
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