Quantitative Inversion Model Design of Mine Water Characteristic Ions Based on Hyperspectral Technology

Abstract

In view of the problems of low measurement accuracy and repeated calibration during the use of coal mine water quality analysis, the hyperspectral reflection noncontact measurement technology was proposed to solve the existing problems. KCl, NaCl, pH, NaHCO3, and CaCl2were used to indicate the characteristic ion information of Na+, K+, Ca2+, Cl−, HCO3−, and pH mine water in the laboratory, and 2220 spectral data were obtained by spectral determination. Savitzky–Golay convolution smoothing was used to smooth and denoise the original spectral data of each ion, and the relationship between the spectrum and the concentration of each reagent was obvious after smoothing and denoising pretreatment. The principal component regression method was used to build the inversion model of each ion content, and through the modeling study, the prediction set of KCl was found: the coefficient R∧2 reaches 0.907, RPD is up to 2.7; the prediction set of NaCl was found: the coefficient R∧2 reaches 0.957, RPD is up to 3.1; the PH prediction set was found: the coefficient R∧2 reaches 0.785, RPD is up to 2.1; the prediction set of NaHCO3 was found: the coefficient R∧2 reaches 0.137, RPD is up to 1.2; the prediction set of CaCl2 was found: the coefficient R∧2 reaches 0.622, and RPD is up to 1.7. The results show that the hyperspectral method can play a better role in the extraction of K+, Cl−, Na+, Ca2+, and pH. It is difficult to extract HCO3− ions.

Experimental Study on the Inversion of Coal Concentration in Mine Water by Visible-Near Infrared Spectroscopy

“…Ilaria Frau [17]uses electromagnetic sensors operating at microwave frequencies to monitor Pb concentrations in mine water in real time by generating a PB-specific EM spectrum. Yunbo Li [18] measured the spectral data of mine water, and established a quantitative inversion model for water quality parameters such as pH value, hardness, ratio of magnesium ion to alkalinity by using the principal component regression method. S. Chander [19] used AVIRIS-NG's semi analytical simulation method for hyperspectral reflectance data to model and monitor turbidity, suspended sediment concentration and chlorophyll concentration in River Ganga of Buxar (Bihar), Howrah (West Bengal) and Chilika lagoon (odrisha).…”