On the Application of Image Processing Methods for Bubble Recognition to the Study of Subcooled Flow Boiling of Water in Rectangular Channels
This work introduces the use of machine vision in the massive bubble recognition process, which supports the validation of boiling models involving bubble dynamics, as well as nucleation frequency, active site density and size of the bubbles. The two algorithms presented are meant to be run employin...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2017-06-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | http://www.mdpi.com/1424-8220/17/6/1448 |
| _version_ | 1798041792572030976 |
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| author | Concepción Paz Marcos Conde Jacobo Porteiro Miguel Concheiro |
| author_facet | Concepción Paz Marcos Conde Jacobo Porteiro Miguel Concheiro |
| author_sort | Concepción Paz |
| collection | DOAJ |
| description | This work introduces the use of machine vision in the massive bubble recognition process, which supports the validation of boiling models involving bubble dynamics, as well as nucleation frequency, active site density and size of the bubbles. The two algorithms presented are meant to be run employing quite standard images of the bubbling process, recorded in general-purpose boiling facilities. The recognition routines are easily adaptable to other facilities if a minimum number of precautions are taken in the setup and in the treatment of the information. Both the side and front projections of subcooled flow-boiling phenomenon over a plain plate are covered. Once all of the intended bubbles have been located in space and time, the proper post-process of the recorded data become capable of tracking each of the recognized bubbles, sketching their trajectories and size evolution, locating the nucleation sites, computing their diameters, and so on. After validating the algorithm’s output against the human eye and data from other researchers, machine vision systems have been demonstrated to be a very valuable option to successfully perform the recognition process, even though the optical analysis of bubbles has not been set as the main goal of the experimental facility. |
| first_indexed | 2024-04-11T22:26:34Z |
| format | Article |
| id | doaj.art-6abd8be2879c42b79a9d0d96707dbed8 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-04-11T22:26:34Z |
| publishDate | 2017-06-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-6abd8be2879c42b79a9d0d96707dbed82022-12-22T03:59:38ZengMDPI AGSensors1424-82202017-06-01176144810.3390/s17061448s17061448On the Application of Image Processing Methods for Bubble Recognition to the Study of Subcooled Flow Boiling of Water in Rectangular ChannelsConcepción Paz0Marcos Conde1Jacobo Porteiro2Miguel Concheiro3School of Industrial Engineering, University of Vigo, Lagoas-Marcosende, Vigo 36310, SpainSchool of Industrial Engineering, University of Vigo, Lagoas-Marcosende, Vigo 36310, SpainSchool of Industrial Engineering, University of Vigo, Lagoas-Marcosende, Vigo 36310, SpainSchool of Industrial Engineering, University of Vigo, Lagoas-Marcosende, Vigo 36310, SpainThis work introduces the use of machine vision in the massive bubble recognition process, which supports the validation of boiling models involving bubble dynamics, as well as nucleation frequency, active site density and size of the bubbles. The two algorithms presented are meant to be run employing quite standard images of the bubbling process, recorded in general-purpose boiling facilities. The recognition routines are easily adaptable to other facilities if a minimum number of precautions are taken in the setup and in the treatment of the information. Both the side and front projections of subcooled flow-boiling phenomenon over a plain plate are covered. Once all of the intended bubbles have been located in space and time, the proper post-process of the recorded data become capable of tracking each of the recognized bubbles, sketching their trajectories and size evolution, locating the nucleation sites, computing their diameters, and so on. After validating the algorithm’s output against the human eye and data from other researchers, machine vision systems have been demonstrated to be a very valuable option to successfully perform the recognition process, even though the optical analysis of bubbles has not been set as the main goal of the experimental facility.http://www.mdpi.com/1424-8220/17/6/1448machine visionflow visualizationbubble recognitionbubble trackingsubcooled flow boiling |
| spellingShingle | Concepción Paz Marcos Conde Jacobo Porteiro Miguel Concheiro On the Application of Image Processing Methods for Bubble Recognition to the Study of Subcooled Flow Boiling of Water in Rectangular Channels Sensors machine vision flow visualization bubble recognition bubble tracking subcooled flow boiling |
| title | On the Application of Image Processing Methods for Bubble Recognition to the Study of Subcooled Flow Boiling of Water in Rectangular Channels |
| title_full | On the Application of Image Processing Methods for Bubble Recognition to the Study of Subcooled Flow Boiling of Water in Rectangular Channels |
| title_fullStr | On the Application of Image Processing Methods for Bubble Recognition to the Study of Subcooled Flow Boiling of Water in Rectangular Channels |
| title_full_unstemmed | On the Application of Image Processing Methods for Bubble Recognition to the Study of Subcooled Flow Boiling of Water in Rectangular Channels |
| title_short | On the Application of Image Processing Methods for Bubble Recognition to the Study of Subcooled Flow Boiling of Water in Rectangular Channels |
| title_sort | on the application of image processing methods for bubble recognition to the study of subcooled flow boiling of water in rectangular channels |
| topic | machine vision flow visualization bubble recognition bubble tracking subcooled flow boiling |
| url | http://www.mdpi.com/1424-8220/17/6/1448 |
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