IWDTF; LIBS; Animal manure composts; Cu; Zn;HEAVY-METAL CONTENTS; MULTIELEMENT ANALYSIS; ACCURACY IMPROVEMENT; MINERAL FERTILIZERS; LIVESTOCK FEEDS; TRACE-ELEMENTS; SPECTROMETRY; LIBS; CONTAMINANTS; TRANSFORM

Spectral denoising offers a basis for effective and accurate quantitative modeling of laser-induced breakdown spectroscopy (LIBS). To provide a solution for the defects of the traditional hard threshold function (HTF) and the soft threshold function (STF) for wavelet denoising methods, an improved wavelet dual threshold function (IWDTF) has been developed. Simulation analyses proved that the IWDTF could provide abetter denoising performance than the traditional functions. The IWDTF was applied to LIBS denoising and quantitative modeling of the Cu and Zn contents in representative Chinese aerobic composting samples. The results showed that the best spectral denoising effects for the Cu and Zn models were achieved when the adjustment parameters k(0), a, and theta were 0.9, 0.7 x lambda(1), and 0.1 x pi, and 0.2, 0.2 x lambda(1), and 0.1 x pi, respectively, and corresponding models' performances for Cu and Zn were both greatly improved, yielding R-p(2) of 0.9807 and 0.9177, RMSEP of 67.49 mg/kg and 84.92 mg/kg, and RPD of 3.12 and 3.07, respectively. (C) 2017 Published by Elsevier B.V.

INDUCED BREAKDOWN SPECTROSCOPY; TRANSFORM; IDENTIFICATION; CALIBRATION; SIGNALS; ALLOYS

Laser-induced breakdown spectroscopy (LIBS) is becoming a rapid and easy technique for quantitative elemental analysis. However, the implementation of accurate quantitative LIBS analysis is always subject to noise interference. In this work, in order to improve LIBS analysis performance for trace elements in aluminium alloys, a modified trade-off soft and hard threshold method is proposed based on the wavelet theory, where optimal parameters are deduced to eliminate noise interference. By using the modified algorithm combined with an Al I line at 308.215 nm as an internal standard, the statistical parameters including the determination coefficient (R-2), the root mean square error (RMSE) and the relative standard deviation (RSD) of magnesium (Mg), manganese (Mn) and cuprum (Cu) in aluminium alloys are all significantly improved. The most significant improvement of R-2 is 0.066 for Cu. The maximum RMSE reduction value is 0.583 for Mg, and the mean value of RMSE reduction is 0.261 for all three trace elements. And after de-noising, the value of RSD gets smaller for each trace element. Such results indicate that the optimized algorithm is valid for the effective improvement of the accuracy of quantitative LIBS analysis in the trace element determination of aluminium alloys.