The proper production process control is possible only if there is an information-measuring system equipped with a large set of measuring transducers of physical quantities. Currently, measuring transducers with semiconductor sensors are widely used. Along with high sensitivity to the measured value and repeatability of parameters, these transducers are sensible to stray quantities, which leads to additional errors. One way to reduce the additional errors of measuring transducers with an integrated sensor is to apply algorithmic correction, which involves a multifactorial calibration experiment, the processing of the results of which allows obtaining the conversion function. Algorithmic correction solves the issue of linearizing the conversion function and minimizes the effect of influencing factors on the measurement results. The conversion function quality and, consequently, the accuracy of further measurements largely depend on the correctness of the calibration experiment results. Random outliers (spurious errors) in the calibration results inevitably cause a distortion of the conversion function and the further erroneous measurement results. This paper proposes a theoretical justification for the possibility of generating the conversion function of a measuring transducer with an integrated sensor by processing the results of a multifactorial calibration experiment including random parasitic errors. Experimental results are provided to illustrate the effectiveness of the proposed calibration results processing technique, which allows obtaining the correct conversion function in the conditions of distorted initial data.
During the production of gas in the Far North and the Arctic, the formation of hydrate and ice plugs in intrafield flowlines is a major concern. The existing methods for determining the onset of hydrate formation are mostly based on the analysis of pressure-and-temperature conditions and therefore they only allow to detect the occurrence of conditions for hydrate formation. They do not allow to localize the specific place where hydrates start to form. The recently developed methods based on echolocation technology have a number of limitations due to the physical nature of the radiation used in them. The proposed method for the monitoring of hydrate formation processes in intrafield flowlines is based on a combination of analysis of pressure-and-temperature conditions in the flowline and the results of flowlines echolocation obtained by means of periodic generation of scanning pressure waves at the end of the flowline (from the side of the switching valve building). The flowlines are divided into characteristic sections bound by characteristic points linked to the structure of the flowline. The propagation speed of the scanning pressure wave is determined in each measuring cycle within the reference section. This can be any section between the characteristic points to which the distance is precisely known and which produce well-defined waveforms and time-stable reflections of scanning pressure waves, for example, the first section located adjacent to the switching valve building. The obtained echograms are compared with the model echogram, which is obtained from a flowline, which is known to be unclogged. Any abnormal change in the signal amplitude is indicative of an onset of the formation of a new local resistance. The proposed recursion formula makes it possible to calculate the temperature in the proximity of this local resistance and, taking into account the pressure value using the diagram of three-phase equilibria for hydrate-forming gases, to diagnose the possibility of existence of crystalline hydrates at a given point. Since pressure-and-temperature conditions for the formation of ice and hydrates are different, the proposed method is selective and enables accurate prediction of the nature of potential buildups.
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