ON-LINE FLOW PROTON MAGNETIC RESONANCE ANALYSERS FOR OIL-WELL LIQUID CONTROL ON GОSТ Р 8.615-2005 GSI

In the work described flow analyzer on the base of proton magnetic-resonance (PMR) allowing on-line, without sample preparation automatically perform express-control and analysis of oil-well liquid control. Presented elaborated control methods, corresponding to GОSТ Р 8.615-2005 GSI and their automatic realization using program LabView

The impulse power unit for a portable proton magnet resonance relaxometer

In this paper described the switching power supply (SPS) unit and represented its importance for electronic circuits in electronic devices. SPS directly affect the operation of electrical circuits and electronic equipment. In particular, this paper describes its use in a portable proton-magnetic resonance (PMR) relaxometer. Especial attention is to the method of constructing the circuit, and also deals with the comparense of the SPS with a transformer power source. This article presents the structure of schematic diagram of the SPS. The SPS structure works without a transformer, which reduces the size of the system and increases overall efficiency. The proposed circuit structure is based on a push-pull controller, a high- frequency converter with an amplifier and a voltage multiplier circuit and a voltage stabilizer. The simulation and experiments confirm the proposed configuration of SPS

Automatic control of rotary pump using measurements of oil-well liquid by on-line proton magnetic resonance analyzer

In the paper described system of automotive control of installation of rotary pump of oil-mining using parameters of oil-well liquid, measured by on-line proton magnetic resonance analyzer. Described theoretical basis of the system and its practical use. Mathematically modeled system tooling tuning) at changing moment of strength from features of oil-well liquid

INSTRUMENTS AND METHODS OF CONTROL OF THE CONCENTRATION OF PARAFIN IN OIL

Made ananalysis of contemporary laboratory devices and methods of control and analysis of paraffin ’s concentration in oils and oil products. Obtined NMR-spectra of standard and natural oil samples. Made an analysis of spectra line parameters. Established correlations between paraffin ’s concentrations, densities and relaxation times. Suggested for aim of of express-analysis to use method of nuclear magnetic resonance relaxometry (NMRR) and Portable relaxometer NMR-NP1

Analysis of Efficiency of the Bioinspired Method for Decoding Algebraic Convolutional Codes

It has been shown that convolutional codes are widely used, along with various decoding methods, to improve the reliability of information transmission in wireless telecommunication systems. The general principles of synthesis and the parameters and algebraic non-systematic convolutional codes with arbitrary coding rate and maximum achievable code distance have been shown.The basic stages of the bioinspired method for decoding algebraic convolutional codes using a random shift mechanism have been presented. It has been shown that the essence of the presented decoding method implies applying the procedure of differential evolution with the heuristically determined parameters. In addition, this method uses information about the reliability of the adopted symbols to find the most reliable basis for the generalized generator matrix. The mechanism of random shift for the modification of the accepted sequence is additionally applied for the bioinspired search based on various most reliable bases of a generalized generator matrix.The research results established that the bioinspired method for decoding algebraic convolutional codes ensures greater efficiency compared with the algebraic decoding method in the communication channel with additive white Gaussian noise. Depending on the parameters of the algebraic convolutional code and the necessary error coefficient, the energy gain from encoding ranges from 1.6 dB to 3 dB. It was shown that the presented bioinspired decoding method can be used for convolutional codes with a large code constraint length.In doing so, the presented method for decoding algebraic convolutional codes is less efficient than the Viterbi decoding method and turbo codes at a sufficient number of decoding iteration