ИСТИНА

Determination of salt composition of mineral waters and control of technical and waste waters containing (in toxic quantities) salts of heavy metals, nitrates, nitrites, sulfates, sulfides etc. is an extremely urgent problem. For the solution of this problem one needs express non-contact methods of diagnostics of water with possibility of their realization in real-time mode. For this purpose, in this work laser Raman spectroscopy was used. The fundamental possibility of using Raman spectroscopy for the diagnostics of water media is caused by high sensitivity of characteristics of spectral Raman bands to the type and concentration of the compounds dissolved in water. However, even high sensitivity of Raman bands to dissolved ions cannot provide the solution of the multi-parametrical inverse problem of the identification of ions and the determination of concentrations of each ion in multi-component water solutions, for example, in mineral waters. To resolve this problem artificial neural networks were used. Earlier, neural networks have shown the high efficiency in the solution of similar problems for five-component water solutions of salts. A successful solution of such multi-parametrical inverse problem of laser Raman spectroscopy is provided by the application of artificial neural networks. “Experimental-based” approach was used, optimal architecture and network parameters were found. The authors demonstrated that suggested method allows to determine a concentration of complex ions in water with accuracy 10-4 M, a concentration of simple ions – with accuracy 10-3 M. The method was tested on natural mineral waters.