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Ultrasonic Transmission Tomography Sensor Design for Bubble Identification in Gas-Liquid Bubble Column Reactors

Scientists require methods to monitor the distribution of gas bubbles in gas-liquid bubble column reactors. One non-destructive method that can potential satisfy this requirement in industrial situations is ultrasonic transmission tomography (UTT). In this paper, an ultrasonic transmission tomograph...

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Autores principales: Li, Nan, Cao, Mingchen, Xu, Kun, Jia, Jiabin, Du, Hangben
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308999/
https://www.ncbi.nlm.nih.gov/pubmed/30518058
http://dx.doi.org/10.3390/s18124256
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author Li, Nan
Cao, Mingchen
Xu, Kun
Jia, Jiabin
Du, Hangben
author_facet Li, Nan
Cao, Mingchen
Xu, Kun
Jia, Jiabin
Du, Hangben
author_sort Li, Nan
collection PubMed
description Scientists require methods to monitor the distribution of gas bubbles in gas-liquid bubble column reactors. One non-destructive method that can potential satisfy this requirement in industrial situations is ultrasonic transmission tomography (UTT). In this paper, an ultrasonic transmission tomography sensor is designed for measuring bubble distribution in a reactor. Factors that influence the transducer design include transmission energy loss, the resonance characteristics and vibration modes of the transducer, and diffusion angles of the transducers, which are discussed. For practical application, it was found that an excitation frequency of 300 kHz could identify the location and size of gas bubbles. The vibration mode and diffusion also directly affect the quality of the imaging. The geometric parameters of the transducer (a cylinder transducer with a 10 mm diameter and 6.7 mm thickness) are designed to achieve the performance requirements. A UTT system, based on these parameters, was built in order to verify the effectiveness of the designed ultrasonic transducer array. A Sector-diffusion-matrix based Linear Back Projection (SLBP) was used to reconstruct the gas/liquid two-phase flow from the obtained measurements. Two other image processing methods, based on SLBP algorithm named SLBP-HR (SLBP-Hybrid Reconstruction) and SLBP-ATF (SLBP-Adaptive Threshold Filtering), were introduced, and the imaging results are presented. The imaging results indicate that a gas bubble with a 3 mm radius can be identified from reconstructed images, and that three different flow patterns, namely, single gas bubble, double gas bubble with different diameters, and eccentric flow, can be identified from reconstructed images. This demonstrates that the designed UTT sensor can effectively measure bubble distribution in gas-liquid bubble column reactors.
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spelling pubmed-63089992019-01-04 Ultrasonic Transmission Tomography Sensor Design for Bubble Identification in Gas-Liquid Bubble Column Reactors Li, Nan Cao, Mingchen Xu, Kun Jia, Jiabin Du, Hangben Sensors (Basel) Article Scientists require methods to monitor the distribution of gas bubbles in gas-liquid bubble column reactors. One non-destructive method that can potential satisfy this requirement in industrial situations is ultrasonic transmission tomography (UTT). In this paper, an ultrasonic transmission tomography sensor is designed for measuring bubble distribution in a reactor. Factors that influence the transducer design include transmission energy loss, the resonance characteristics and vibration modes of the transducer, and diffusion angles of the transducers, which are discussed. For practical application, it was found that an excitation frequency of 300 kHz could identify the location and size of gas bubbles. The vibration mode and diffusion also directly affect the quality of the imaging. The geometric parameters of the transducer (a cylinder transducer with a 10 mm diameter and 6.7 mm thickness) are designed to achieve the performance requirements. A UTT system, based on these parameters, was built in order to verify the effectiveness of the designed ultrasonic transducer array. A Sector-diffusion-matrix based Linear Back Projection (SLBP) was used to reconstruct the gas/liquid two-phase flow from the obtained measurements. Two other image processing methods, based on SLBP algorithm named SLBP-HR (SLBP-Hybrid Reconstruction) and SLBP-ATF (SLBP-Adaptive Threshold Filtering), were introduced, and the imaging results are presented. The imaging results indicate that a gas bubble with a 3 mm radius can be identified from reconstructed images, and that three different flow patterns, namely, single gas bubble, double gas bubble with different diameters, and eccentric flow, can be identified from reconstructed images. This demonstrates that the designed UTT sensor can effectively measure bubble distribution in gas-liquid bubble column reactors. MDPI 2018-12-04 /pmc/articles/PMC6308999/ /pubmed/30518058 http://dx.doi.org/10.3390/s18124256 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Li, Nan
Cao, Mingchen
Xu, Kun
Jia, Jiabin
Du, Hangben
Ultrasonic Transmission Tomography Sensor Design for Bubble Identification in Gas-Liquid Bubble Column Reactors
title Ultrasonic Transmission Tomography Sensor Design for Bubble Identification in Gas-Liquid Bubble Column Reactors
title_full Ultrasonic Transmission Tomography Sensor Design for Bubble Identification in Gas-Liquid Bubble Column Reactors
title_fullStr Ultrasonic Transmission Tomography Sensor Design for Bubble Identification in Gas-Liquid Bubble Column Reactors
title_full_unstemmed Ultrasonic Transmission Tomography Sensor Design for Bubble Identification in Gas-Liquid Bubble Column Reactors
title_short Ultrasonic Transmission Tomography Sensor Design for Bubble Identification in Gas-Liquid Bubble Column Reactors
title_sort ultrasonic transmission tomography sensor design for bubble identification in gas-liquid bubble column reactors
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308999/
https://www.ncbi.nlm.nih.gov/pubmed/30518058
http://dx.doi.org/10.3390/s18124256
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