Chemical, acoustic and optical response profiling for analysing burning patterns
Improved data processing algorithms along with modelling techniques were employed in order to profile the responses and to assess the analytical capabilities of a system consisting of a mass spectrometer, a camera and a microphone for synchronized chemical, optical and acoustic monitoring of lab-sca...
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Veröffentlicht in: | Sensors and actuators. B, Chemical Chemical, 2013-01, Vol.176, p.290-298 |
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container_title | Sensors and actuators. B, Chemical |
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creator | Mikedi, K. Stavrakakis, P. Agapiou, A. Moirogiorgou, K. Karma, S. Pallis, G.C. Pappa, A. Statheropoulos, M. Zervakis, M. |
description | Improved data processing algorithms along with modelling techniques were employed in order to profile the responses and to assess the analytical capabilities of a system consisting of a mass spectrometer, a camera and a microphone for synchronized chemical, optical and acoustic monitoring of lab-scale fires. The combustion of cotton textile, inkjet white paper and oak wood was monitored by this system in a laboratory based environment under controlled conditions. Signal processing enabled the identification of modalities of different material burning, through the modelling and curve fitting techniques. For the chemical and optical responses, the temporal models with curve fitting were used, whereas for the acoustic signal, spectral analysis was applied for quantifying harmonics. The synergy of the three sensing technologies, augmented by signal processing and modelling, resulted in initial models, characteristic for the fire pattern for each material studied. The potentials emerged by this exploratory work needs further elaboration and elucidation, since the analytical prospective of the proposed approach is considerable and auspicious. |
doi_str_mv | 10.1016/j.snb.2012.07.103 |
format | Article |
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The combustion of cotton textile, inkjet white paper and oak wood was monitored by this system in a laboratory based environment under controlled conditions. Signal processing enabled the identification of modalities of different material burning, through the modelling and curve fitting techniques. For the chemical and optical responses, the temporal models with curve fitting were used, whereas for the acoustic signal, spectral analysis was applied for quantifying harmonics. The synergy of the three sensing technologies, augmented by signal processing and modelling, resulted in initial models, characteristic for the fire pattern for each material studied. 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B, Chemical</title><description>Improved data processing algorithms along with modelling techniques were employed in order to profile the responses and to assess the analytical capabilities of a system consisting of a mass spectrometer, a camera and a microphone for synchronized chemical, optical and acoustic monitoring of lab-scale fires. The combustion of cotton textile, inkjet white paper and oak wood was monitored by this system in a laboratory based environment under controlled conditions. Signal processing enabled the identification of modalities of different material burning, through the modelling and curve fitting techniques. For the chemical and optical responses, the temporal models with curve fitting were used, whereas for the acoustic signal, spectral analysis was applied for quantifying harmonics. The synergy of the three sensing technologies, augmented by signal processing and modelling, resulted in initial models, characteristic for the fire pattern for each material studied. The potentials emerged by this exploratory work needs further elaboration and elucidation, since the analytical prospective of the proposed approach is considerable and auspicious.</description><subject>Acoustics</subject><subject>algorithms</subject><subject>burning</subject><subject>Burning pattern</subject><subject>Combustion</subject><subject>cotton</subject><subject>Curve fitting</subject><subject>Fires</subject><subject>Indoor fires</subject><subject>Mathematical analysis</subject><subject>Modelling</subject><subject>monitoring</subject><subject>Pulsed sampling system-mass spectrometer (PSS-MS)</subject><subject>Sensor integration</subject><subject>Signal processing</subject><subject>Signal waveform modelling</subject><subject>spectral analysis</subject><subject>spectrometers</subject><subject>Volatile organic compounds (VOCs)</subject><subject>wood</subject><issn>0925-4005</issn><issn>1873-3077</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><recordid>eNp9kEtLxDAUhYMoOD5-gCu7dGFrXk1aXMngCwYUdNYhzWPM0Elq0hHm35tS164O9_Ddw70HgCsEKwQRu9tWyXcVhghXkGeLHIEFajgpCeT8GCxgi-uSQlifgrOUthBCShhcgPfll9k5JfvbQqqwT6NThfS6CMM4uUU0aQg-mWKIwbre-U1hQ8yI7A9pmrp99JMOchxN9OkCnFjZJ3P5p-dg_fT4uXwpV2_Pr8uHValITceScNRyKjVVhOoWS8tYrRUjjcasqTmWvGtJx1hjia47YqXkliFGG6Ul4ZiTc3Az5-bDvvcmjWLnkjJ9L73JfwhEUM0ow4hmFM2oiiGlaKwYotvJeBAIiqk9sRW5PTG1JyDPFsk71_OOlUHITXRJrD8yUEOIEMNtk4n7mTD5yx9nokjKGa-MdtGoUejg_sn_BSVugSY</recordid><startdate>201301</startdate><enddate>201301</enddate><creator>Mikedi, K.</creator><creator>Stavrakakis, P.</creator><creator>Agapiou, A.</creator><creator>Moirogiorgou, K.</creator><creator>Karma, S.</creator><creator>Pallis, G.C.</creator><creator>Pappa, A.</creator><creator>Statheropoulos, M.</creator><creator>Zervakis, M.</creator><general>Elsevier B.V</general><scope>FBQ</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TB</scope><scope>7U5</scope><scope>8FD</scope><scope>FR3</scope><scope>L7M</scope></search><sort><creationdate>201301</creationdate><title>Chemical, acoustic and optical response profiling for analysing burning patterns</title><author>Mikedi, K. ; Stavrakakis, P. ; Agapiou, A. ; Moirogiorgou, K. ; Karma, S. ; Pallis, G.C. ; Pappa, A. ; Statheropoulos, M. ; Zervakis, M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c354t-371974ad4c34d92af665dc638d268572a7b93b668f3d5b3faa7f61648cda37273</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Acoustics</topic><topic>algorithms</topic><topic>burning</topic><topic>Burning pattern</topic><topic>Combustion</topic><topic>cotton</topic><topic>Curve fitting</topic><topic>Fires</topic><topic>Indoor fires</topic><topic>Mathematical analysis</topic><topic>Modelling</topic><topic>monitoring</topic><topic>Pulsed sampling system-mass spectrometer (PSS-MS)</topic><topic>Sensor integration</topic><topic>Signal processing</topic><topic>Signal waveform modelling</topic><topic>spectral analysis</topic><topic>spectrometers</topic><topic>Volatile organic compounds (VOCs)</topic><topic>wood</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Mikedi, K.</creatorcontrib><creatorcontrib>Stavrakakis, P.</creatorcontrib><creatorcontrib>Agapiou, A.</creatorcontrib><creatorcontrib>Moirogiorgou, K.</creatorcontrib><creatorcontrib>Karma, S.</creatorcontrib><creatorcontrib>Pallis, G.C.</creatorcontrib><creatorcontrib>Pappa, A.</creatorcontrib><creatorcontrib>Statheropoulos, M.</creatorcontrib><creatorcontrib>Zervakis, M.</creatorcontrib><collection>AGRIS</collection><collection>CrossRef</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Solid State and Superconductivity Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Sensors and actuators. 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B, Chemical</jtitle><date>2013-01</date><risdate>2013</risdate><volume>176</volume><spage>290</spage><epage>298</epage><pages>290-298</pages><issn>0925-4005</issn><eissn>1873-3077</eissn><abstract>Improved data processing algorithms along with modelling techniques were employed in order to profile the responses and to assess the analytical capabilities of a system consisting of a mass spectrometer, a camera and a microphone for synchronized chemical, optical and acoustic monitoring of lab-scale fires. The combustion of cotton textile, inkjet white paper and oak wood was monitored by this system in a laboratory based environment under controlled conditions. Signal processing enabled the identification of modalities of different material burning, through the modelling and curve fitting techniques. For the chemical and optical responses, the temporal models with curve fitting were used, whereas for the acoustic signal, spectral analysis was applied for quantifying harmonics. The synergy of the three sensing technologies, augmented by signal processing and modelling, resulted in initial models, characteristic for the fire pattern for each material studied. The potentials emerged by this exploratory work needs further elaboration and elucidation, since the analytical prospective of the proposed approach is considerable and auspicious.</abstract><pub>Elsevier B.V</pub><doi>10.1016/j.snb.2012.07.103</doi><tpages>9</tpages></addata></record> |
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subjects | Acoustics algorithms burning Burning pattern Combustion cotton Curve fitting Fires Indoor fires Mathematical analysis Modelling monitoring Pulsed sampling system-mass spectrometer (PSS-MS) Sensor integration Signal processing Signal waveform modelling spectral analysis spectrometers Volatile organic compounds (VOCs) wood |
title | Chemical, acoustic and optical response profiling for analysing burning patterns |
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