Visibility graph analysis of fluid flow signals
Visibility graphs have established themselves in recent years as being particularly suitable and flexible for analyzing signals measured from complex natural and artificial systems. Oil-water two-phase flow as a complicated fluid flow is one of the most complex systems. In this paper, we employ visi...
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creator | Zhongke Gao Lingchao Ji |
description | Visibility graphs have established themselves in recent years as being particularly suitable and flexible for analyzing signals measured from complex natural and artificial systems. Oil-water two-phase flow as a complicated fluid flow is one of the most complex systems. In this paper, we employ visibility graph to analyze the signals measured from experiment two-phase flow. We first introduce the inclined oil-water two-phase flow experiment and data acquisition. Then we present the algorithm for constructing visibility graphs from signals. Finally, we infer and analyze visibility graphs from signals measured under different fluid flow conditions. The results indicate that the combination parameters of network degree are sensitive to the transition among different flow patterns, which can be used to distinguish and characterize different oil-water two-phase flow patterns. In this regard, visibility graph could be a useful tool for processing experimental signals. |
doi_str_mv | 10.1109/ICACI.2012.6463119 |
format | Conference Proceeding |
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Oil-water two-phase flow as a complicated fluid flow is one of the most complex systems. In this paper, we employ visibility graph to analyze the signals measured from experiment two-phase flow. We first introduce the inclined oil-water two-phase flow experiment and data acquisition. Then we present the algorithm for constructing visibility graphs from signals. Finally, we infer and analyze visibility graphs from signals measured under different fluid flow conditions. The results indicate that the combination parameters of network degree are sensitive to the transition among different flow patterns, which can be used to distinguish and characterize different oil-water two-phase flow patterns. In this regard, visibility graph could be a useful tool for processing experimental signals.</description><identifier>ISBN: 9781467317436</identifier><identifier>ISBN: 1467317438</identifier><identifier>EISBN: 146731742X</identifier><identifier>EISBN: 9781467317443</identifier><identifier>EISBN: 9781467317429</identifier><identifier>EISBN: 1467317446</identifier><identifier>DOI: 10.1109/ICACI.2012.6463119</identifier><language>eng</language><publisher>IEEE</publisher><subject>Complex networks ; Data acquisition ; Dispersion ; Educational institutions ; Fluid flow measurement ; Time series analysis ; Voltage measurement</subject><ispartof>2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI), 2012, p.44-47</ispartof><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/6463119$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>309,310,776,780,785,786,2052,27902,54895</link.rule.ids><linktorsrc>$$Uhttps://ieeexplore.ieee.org/document/6463119$$EView_record_in_IEEE$$FView_record_in_$$GIEEE</linktorsrc></links><search><creatorcontrib>Zhongke Gao</creatorcontrib><creatorcontrib>Lingchao Ji</creatorcontrib><title>Visibility graph analysis of fluid flow signals</title><title>2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI)</title><addtitle>ICACI</addtitle><description>Visibility graphs have established themselves in recent years as being particularly suitable and flexible for analyzing signals measured from complex natural and artificial systems. Oil-water two-phase flow as a complicated fluid flow is one of the most complex systems. In this paper, we employ visibility graph to analyze the signals measured from experiment two-phase flow. We first introduce the inclined oil-water two-phase flow experiment and data acquisition. Then we present the algorithm for constructing visibility graphs from signals. Finally, we infer and analyze visibility graphs from signals measured under different fluid flow conditions. The results indicate that the combination parameters of network degree are sensitive to the transition among different flow patterns, which can be used to distinguish and characterize different oil-water two-phase flow patterns. In this regard, visibility graph could be a useful tool for processing experimental signals.</description><subject>Complex networks</subject><subject>Data acquisition</subject><subject>Dispersion</subject><subject>Educational institutions</subject><subject>Fluid flow measurement</subject><subject>Time series analysis</subject><subject>Voltage measurement</subject><isbn>9781467317436</isbn><isbn>1467317438</isbn><isbn>146731742X</isbn><isbn>9781467317443</isbn><isbn>9781467317429</isbn><isbn>1467317446</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2012</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNo1j81KAzEUhSMiqHVeQDd5gZnm5uZ3KYPaQsGNiruSztzUyGjLpCLz9kasm_NxONyfw9g1iAZA-PmyvW2XjRQgG6MMAvgTdgnKWASr5Ospq7x1_x7NOatyfhdClGEDRl2w-UvKaZOGdJj4dgz7Nx4-wzDllPku8jh8pb7o7pvntC1BvmJnsYCqI2fs-f7uqV3Uq8eH8syqTmD1oe47MBsnqTfGQwxEYGL4PaudVqSR0KFTZJ3UqERAdF300lnlOyoGccZu_vYmIlrvx_QRxml97Ig_XG9DlA</recordid><startdate>201210</startdate><enddate>201210</enddate><creator>Zhongke Gao</creator><creator>Lingchao Ji</creator><general>IEEE</general><scope>6IE</scope><scope>6IL</scope><scope>CBEJK</scope><scope>RIE</scope><scope>RIL</scope></search><sort><creationdate>201210</creationdate><title>Visibility graph analysis of fluid flow signals</title><author>Zhongke Gao ; Lingchao Ji</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i175t-dc16b82ed6691faee16fa00115854e53e38384e7825340a338cf928749ce33833</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Complex networks</topic><topic>Data acquisition</topic><topic>Dispersion</topic><topic>Educational institutions</topic><topic>Fluid flow measurement</topic><topic>Time series analysis</topic><topic>Voltage measurement</topic><toplevel>online_resources</toplevel><creatorcontrib>Zhongke Gao</creatorcontrib><creatorcontrib>Lingchao Ji</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Zhongke Gao</au><au>Lingchao Ji</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Visibility graph analysis of fluid flow signals</atitle><btitle>2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI)</btitle><stitle>ICACI</stitle><date>2012-10</date><risdate>2012</risdate><spage>44</spage><epage>47</epage><pages>44-47</pages><isbn>9781467317436</isbn><isbn>1467317438</isbn><eisbn>146731742X</eisbn><eisbn>9781467317443</eisbn><eisbn>9781467317429</eisbn><eisbn>1467317446</eisbn><abstract>Visibility graphs have established themselves in recent years as being particularly suitable and flexible for analyzing signals measured from complex natural and artificial systems. Oil-water two-phase flow as a complicated fluid flow is one of the most complex systems. In this paper, we employ visibility graph to analyze the signals measured from experiment two-phase flow. We first introduce the inclined oil-water two-phase flow experiment and data acquisition. Then we present the algorithm for constructing visibility graphs from signals. Finally, we infer and analyze visibility graphs from signals measured under different fluid flow conditions. The results indicate that the combination parameters of network degree are sensitive to the transition among different flow patterns, which can be used to distinguish and characterize different oil-water two-phase flow patterns. In this regard, visibility graph could be a useful tool for processing experimental signals.</abstract><pub>IEEE</pub><doi>10.1109/ICACI.2012.6463119</doi><tpages>4</tpages></addata></record> |
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subjects | Complex networks Data acquisition Dispersion Educational institutions Fluid flow measurement Time series analysis Voltage measurement |
title | Visibility graph analysis of fluid flow signals |
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