Synthesis of compact patterns for NMR relaxation decay in intelligent "electronic tongue" for analyzing heavy oil composition

The article is devoted to the problem of pattern creation of the NMR sensor signal for subsequent recognition by the artificial neural network in the intelligent device "the electronic tongue". The specific problem of removing redundant data from the spin-spin relaxation signal pattern that is used as a source of information in analyzing the composition of oil and petroleum products is considered. The method is proposed that makes it possible to remove redundant data of the relaxation decay pattern but without introducing additional distortion. This method is based on combining some relaxation decay curve intervals that increment below the noise level such that the increment of the combined intervals is above the noise level. In this case, the relaxation decay curve samples that are located inside the combined intervals are removed from the pattern. This method was tested on the heavy-oil NMR signal patterns that were created by using the Carr-Purcell-Meibum-Gill (CPMG) sequence for recording the relaxation process. Parameters of CPMG sequence are: 100 μs - time interval between 180° pulses, 0.4s - duration of measurement. As a result, it was revealed that the proposed method allowed one to reduce the number of samples 15 times (from 4000 to 270), and the maximum detected root mean square error (RMS error) equals 0.00239 (equivalent to signal-to-noise ratio 418). (paper)