Abstract
A method for gas–solid two-phase flow pattern identification in horizontal pneumatic conveying pipelines is proposed based on an electrostatic sensor array (ESA) and artificial neural network (ANN). The ESA contains eight identical arc shaped electrodes. Numerical simulation is conducted to discuss the contributions of the electrostatic signals to the flow patterns according to the error recognition rate, and the results show that the amplitudes of the output signals from each electrode of the ESA can give important information on the particle distribution and further infer the flow patterns. In experiments, the average values and standard deviations of the eight output signals’ amplitudes are respectively extracted as the inputs of the ANN to identify four kinds of flow patterns in a pneumatic conveying pipeline, which are fully suspended flow, stratified flow, dune flow and slug flow. Results show that for any one of those two input values, the correct rates of the ANN model are all 100%.
Highlights
Flow pattern identification of gas–solid two-phase flow in pneumatic conveying pipelines is significant for the optimized design and operation of a pneumatic conveying system
electrical capacitance tomography (ECT) can becan used identify gas-solid flow flow patterns, this paper focuses on an identification method based on an patterns, this paper focuses on an identification method based on an artificial neural networks (ANN) and electrostatic sensor array (ESA))
To identify flow patterns of gas-solid two-phase flow in pneumatic conveying pipelines, this paper proposes an identification method based on an ESA and ANN
Summary
Flow pattern identification of gas–solid two-phase flow in pneumatic conveying pipelines is significant for the optimized design and operation of a pneumatic conveying system. Particle charging of the gas‒solid two-phase flow could contain lots of information specify the reliability of the inputs of an ANN for representing flow patterns. (ESA) asFor a novel type of electrostatic sensor has been applied to detect particle concentration particle charging of the gas-solid two-phase flow could contain lots of information distribution in a cross section of pneumatic conveying pipeline, for that the sensing field of ESA is regarding particle dynamics and particle properties [7,8,9,10]. The concentration distribution of charged particles over the array (ESA) as a novel type of electrostatic sensor has been applied to detect particle concentration crossdistribution section of the pipeline has a significant the sensing gas‒solid flow in aconveying cross section of pneumatic conveyingrelationship pipeline, forwith that the field of patterns.
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