Quantitative and classification analysis of slag samples by laser induced breakdown spectroscopy (LIBS) coupled with support vector machine (SVM) and partial least square (PLS) methods

2015 ◽  
Vol 30 (2) ◽  
pp. 368-374 ◽  
Author(s):  
Tianlong Zhang ◽  
Shan Wu ◽  
Juan Dong ◽  
Jiao Wei ◽  
Kang Wang ◽  
...  

A laser induced breakdown spectroscopy (LIBS) technique coupled with SVM and PLS was proposed to perform quantitative and classification analysis of 20 slag samples.

Sensors ◽  
2019 ◽  
Vol 19 (19) ◽  
pp. 4225 ◽  
Author(s):  
Hao Zhang ◽  
Shun Wang ◽  
Dongxian Li ◽  
Yanyan Zhang ◽  
Jiandong Hu ◽  
...  

Edible gelatin has been widely used as a food additive in the food industry, and illegal adulteration with industrial gelatin will cause serious harm to human health. The present work used laser-induced breakdown spectroscopy (LIBS) coupled with the partial least square–support vector machine (PLS-SVM) method for the fast and accurate estimation of edible gelatin adulteration. Gelatin samples with 11 different adulteration ratios were prepared by mixing pure edible gelatin with industrial gelatin, and the LIBS spectra were recorded to analyze their elemental composition differences. The PLS, SVM, and PLS-SVM models were separately built for the prediction of gelatin adulteration ratios, and the hybrid PLS-SVM model yielded a better performance than only the PLS and SVM models. Besides, four different variable selection methods, including competitive adaptive reweighted sampling (CARS), Monte Carlo uninformative variable elimination (MC-UVE), random frog (RF), and principal component analysis (PCA), were adopted to combine with the SVM model for comparative study; the results further demonstrated that the PLS-SVM model was superior to the other SVM models. This study reveals that the hybrid PLS-SVM model, with the advantages of low computational time and high prediction accuracy, can be employed as a preferred method for the accurate estimation of edible gelatin adulteration.


2017 ◽  
Vol 54 (8) ◽  
pp. 083002 ◽  
Author(s):  
杨晖 Yang Hui ◽  
黄林 Huang Lin ◽  
刘木华 Liu Muhua ◽  
陈添兵 Chen Tianbing ◽  
饶刚福 Rao Gangfu ◽  
...  

2020 ◽  
Vol 10 (7) ◽  
pp. 2617 ◽  
Author(s):  
Shan Lu ◽  
Xinwei Wang ◽  
Tianzheng Wang ◽  
Xinran Qin ◽  
Xilin Wang ◽  
...  

The composition of contamination deposited on transmission line insulators can affect their surface flashover voltage. Currently, there is no rapid on-line method to detect this contamination composition in power grids. In this paper, we applied laser-induced breakdown spectroscopy (LIBS) to analyze contamination on insulator surfaces. Usually, Na and Ca salts are found in contamination along with various sulfate, carbonate, and chloride compounds. As an element’s detection method, LIBS can only measure a certain element content, for example, Ca. The mixture of various compounds with the same cations can influence the LIBS signal. The influence of mixing ratios on the calibration curves and relative spectral intensity was studied via LIBS. Na2CO3, NaHCO3, CaSO4, and CaCO3 samples containing different proportions of Na and Ca were prepared. The linear correlation coefficients (R2) for the Na and Ca calibration curves generated using various mixing ratios were analyzed. The results showed that the mixture ratio did not dramatically affect the linear calibration curves for mixtures containing the same cations. This finding may significantly reduce the difficulty of applying LIBS analysis for complex contamination on insulators. The laser energy density had effects on the spectral characteristics of the measured elements. The partial least-square regression (PLSR) model can improve the accuracy of Na and Ca prediction.


2013 ◽  
Vol 33 (3) ◽  
pp. 0330002 ◽  
Author(s):  
王春龙 Wang Chunlong ◽  
刘建国 Liu Jianguo ◽  
赵南京 Zhao Nanjing ◽  
马明俊 Ma Mingjun ◽  
王寅 Wang Yin ◽  
...  

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