Journal ArticleDOI
Rapid classification of plastics by laser-induced breakdown spectroscopy (LIBS) coupled with partial least squares discrimination analysis based on variable importance (VI-PLS-DA)
Reads0
Chats0
TLDR
In this article, an extension of Partial Least Squares Discrimination Analysis (PLS-DA) that uses variable importance to select input variables was presented, which has the highest classification accuracy and shortest classification time.Abstract:
With the extensive use of plastic products, the recycling and reuse of plastics raise more concerns. Laser-induced breakdown spectroscopy (LIBS) and chemometric methods have been applied to classify plastics. However, the methods are prone to fall into over-fitting when predicting unknown samples. Variable importance is the impact of input variables to classification results. Selecting input variables by variable importance can be used to avoid over-fitting, which has been used for improving model performance based on random forest (RF). However, the progress of optimizing the parameters of RF model is complex. Partial least squares discrimination analysis (PLS-DA), most widely used in spectral data, is a simple and stable method in multivariate analysis. To avoid over-fitting phenomenon and acquire stable results, this paper presents an extension of PLS-DA that uses variable importance to select input variables, namely VI-PLS-DA. In order to validate the classification ability of VI-PLS-DA for plastics, VI-PLS-DA was compared with PLS-DA, RF, and VI-RF. VI-PLS-DA has the highest classification accuracy (99.55%) and shortest classification time (0.096 ms), which indicated a good classification performance for plastics analysis.read more
Citations
More filters
Journal ArticleDOI
A review of laser-induced breakdown spectroscopy for plastic analysis
TL;DR: In this article, a review of laser-induced breakdown spectroscopy (LIBS) applications for coal ranks, combustion efficiency, and environmental protection is presented, together with a description of limitations and the potential developing trend for this topic.
Journal ArticleDOI
A review on chemometric techniques with infrared, Raman and laser-induced breakdown spectroscopy for sorting plastic waste in the recycling industry
TL;DR: In this article , a review of the recent works applying chemometric methods to plastic waste sorting is presented, which includes principal component analysis (PCA), linear discriminant analysis (LDA), partial least square (PLS), k-nearest neighbors (k-NN), support vector machines (SVM), random forests (RF), artificial neural networks (ANNs), convolutional neural network (CNNs), and K-means clustering.
Journal ArticleDOI
Femtosecond laser-induced breakdown spectroscopy studies for the identification of plastics
TL;DR: In this article, a femtosecond laser-induced breakdown spectroscopy (fs-LIBS) technique was used for the identification of post-consumer plastics using an ultra-fast amplifier system delivering pulses of ∼50 fs duration.
Journal ArticleDOI
Laser induced breakdown spectroscopy for plastic analysis
Qiang Zeng,Jean-Baptiste Sirven,Jean-Christophe P. Gabriel,Jean-Christophe P. Gabriel,Chor Yong Tay,Jong-Min Lee +5 more
TL;DR: In this paper, a review describes the development and prospect of plastic investigations using LIBS, highlighting the intrinsic advantages of LIBS for plastic recycling, and the selection of hardware components and analysis methods are discussed.
Journal ArticleDOI
A low-cost LIBS detection system combined with chemometrics for rapid identification of plastic waste.
TL;DR: In this paper, a low-cost, compact CCD spectrometer was deployed in laser-induced breakdown spectroscopy (LIBS) technique for the identification of post-consumer plastics obtained from a local recycling unit.
References
More filters
Journal ArticleDOI
Variable importance analysis: A comprehensive review
TL;DR: All the good practices in each discipline of variable importance analysis (VIA) techniques are reviewed and compared, so as to instruct the practitioners to choose the optimal methods to meet different analysis purposes, and to guide current research on VIA.
Journal ArticleDOI
Laser-induced breakdown spectroscopy for polymer identification
TL;DR: It was shown that many polymers could be separated, including PE and PP, despite their similar chemical structures, and aliphatic and aromatic polymerscould be differentiated.
Journal ArticleDOI
Identification and classification of polymer e-waste using laser-induced breakdown spectroscopy (LIBS) and chemometric tools
Vinicius Câmara Costa,Francisco W. B. Aquino,Caio M. Paranhos,Edenir Rodrigues Pereira-Filho +3 more
TL;DR: In this article, a laser-induced breakdown spectrometry (LIBS) technique was used to identify e-waste polymers by using the ratios of the emission lines and molecular band.
Journal ArticleDOI
Identification of polymer materials using laser-induced breakdown spectroscopy combined with artificial neural networks.
TL;DR: A combination of laser-induced breakdown spectroscopy (LIBS) and artificial neural networks (ANNs) has been used for the identification of polymer materials, including polypropylene (PP), polyvinyl chloride (PVC), polytetrafluoroethylene (PTFE), polyoxymethylene(POM), polyethylene or nylon (PA), polycarbonate (PC) and poly(methyl methacrylate) (PMMA) as mentioned in this paper.
Journal ArticleDOI
A chemometric study of chromatograms of tea extracts by correlation optimization warping in conjunction with PCA, support vector machines and random forest data modeling.
Liang Zheng,David G. Watson,Blair F. Johnston,Rachael L. Clark,RuAngelie Edrada-Ebel,W. Elseheri +5 more
TL;DR: PCA, support vector machines and random forest machine learning methods were evaluated comparatively on their ability to predict unknown tea samples using models constructed from a predetermined training set, and the best predictions of identity were obtained by using RF.