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Analysis The Flow Characteristics And Flow Mechanism Of Gas-liquid Two Phase Flow Based On The Acoustic Emission

Posted on:2015-01-25Degree:MasterType:Thesis
Country:ChinaCandidate:Y ZhangFull Text:PDF
GTID:2180330422469966Subject:Measuring and Testing Technology and Instruments
Abstract/Summary:PDF Full Text Request
In recent years, with the increasingly rate of the petroleum industrial during the nationaleconomy. experts also gradually study importantly and pay more attention into the multiphaseflow detection. The flow character of gas-liquid two-phase flow is the basic for multiphaseflow detection and the key factor reveals the flow mechanism of multiphase flow. For thegas-liquid two-phase flow detection, the traditional detection method(direct observation andinstrumentation)always ignore the internal flow in the pipe.This paper proposes a new method in detecting the gas-liquid two-phase flowcharacteristics with the technology of acoustic emission. And built the gas-liquid two-phaseflow noise signal experimental system. Using the principle of acoustic emission to collect theliquid two-phase flow noise and analysis. The advantage of acoustic emission to detect themethod is non-contact, non-interference internal flow field and online testing.Collect the noise signal from the multiphase flow experiment system and analysis theinternal characterization of flow signal, through processing the signal of flow noise andextract the signal features in vertical and horizontal experiment pipe about differentexperimental flow patterns. Then distinguish the flow pattern with these features, with theseparameters directly reveals the gas-liquid two-phase Flow characteristics and flowmechanism.Take all the patterns characteristic parameters into a multi-dimensional feature vector indifferent flow conditions, use the concept of pattern recognition to identify the flow pattern.From euclidean distance equation finally get the results which the same flow pattern resultsget the shortest value.
Keywords/Search Tags:Gas-liquid two-phase flow, Flow pattern, Vertical experiment, Information entropy, Pattern recognition
PDF Full Text Request
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