Bayesian models for the determination of resonant frequencies in a DI diesel engine
A time series method for the determination of combustion chamber resonant frequencies is outlined. This technique employs the use of Markov-chain Monte Carlo (MCMC) to infer parameters in a chosen model of the data. The development of the model is included and the resonant frequency is characterised...
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| Veröffentlicht in: | Mechanical systems and signal processing 2012, Vol.26 (JAN), p.305-314 |
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| container_title | Mechanical systems and signal processing |
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| creator | Bodisco, Timothy Reeves, Robert Situ, Rong Brown, Richard |
| description | A time series method for the determination of combustion chamber resonant frequencies is outlined. This technique employs the use of Markov-chain Monte Carlo (MCMC) to infer parameters in a chosen model of the data. The development of the model is included and the resonant frequency is characterised as a function of time. Potential applications for cycle-by-cycle analysis are discussed and the bulk temperature of the gas and the trapped mass in the combustion chamber are evaluated as a function of time from resonant frequency information.
► Propose the use of Bayesian statistics in engine research. ► Demonstrate Bayesian model development to analyse in-cylinder pressure signals. ► Locate the resonant frequency of in-cylinder pressure signals. ► Establish a connection between frequency, temperature and trapped mass. ► Confirm the importance of considering inter-cycle variability. |
| doi_str_mv | 10.1016/j.ymssp.2011.06.014 |
| format | Article |
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► Propose the use of Bayesian statistics in engine research. ► Demonstrate Bayesian model development to analyse in-cylinder pressure signals. ► Locate the resonant frequency of in-cylinder pressure signals. ► Establish a connection between frequency, temperature and trapped mass. ► Confirm the importance of considering inter-cycle variability.</description><identifier>ISSN: 0888-3270</identifier><identifier>EISSN: 1096-1216</identifier><identifier>DOI: 10.1016/j.ymssp.2011.06.014</identifier><language>eng</language><publisher>Kidlington: Elsevier Ltd</publisher><subject>Applied sciences ; Combustion chambers ; Computer simulation ; Diesel engines ; Engines and turbines ; Exact sciences and technology ; Inter-cycle variability ; Internal combustion engines: gazoline engine, diesel engines, etc ; Mathematical models ; MCMC ; Mechanical engineering. Machine design ; Mechanical systems ; Monte Carlo methods ; Resonant frequencies ; Resonant frequency ; Statistical inference ; Time series</subject><ispartof>Mechanical systems and signal processing, 2012, Vol.26 (JAN), p.305-314</ispartof><rights>2011 Elsevier Ltd</rights><rights>2015 INIST-CNRS</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c410t-43b13582cc91255437a5693c42e1cd1e30971c044778a9ce6fc72c1a7930dc33</citedby><cites>FETCH-LOGICAL-c410t-43b13582cc91255437a5693c42e1cd1e30971c044778a9ce6fc72c1a7930dc33</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.ymssp.2011.06.014$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,780,784,3550,4024,27923,27924,27925,45995</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=24707183$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Bodisco, Timothy</creatorcontrib><creatorcontrib>Reeves, Robert</creatorcontrib><creatorcontrib>Situ, Rong</creatorcontrib><creatorcontrib>Brown, Richard</creatorcontrib><title>Bayesian models for the determination of resonant frequencies in a DI diesel engine</title><title>Mechanical systems and signal processing</title><description>A time series method for the determination of combustion chamber resonant frequencies is outlined. This technique employs the use of Markov-chain Monte Carlo (MCMC) to infer parameters in a chosen model of the data. The development of the model is included and the resonant frequency is characterised as a function of time. Potential applications for cycle-by-cycle analysis are discussed and the bulk temperature of the gas and the trapped mass in the combustion chamber are evaluated as a function of time from resonant frequency information.
► Propose the use of Bayesian statistics in engine research. ► Demonstrate Bayesian model development to analyse in-cylinder pressure signals. ► Locate the resonant frequency of in-cylinder pressure signals. ► Establish a connection between frequency, temperature and trapped mass. ► Confirm the importance of considering inter-cycle variability.</description><subject>Applied sciences</subject><subject>Combustion chambers</subject><subject>Computer simulation</subject><subject>Diesel engines</subject><subject>Engines and turbines</subject><subject>Exact sciences and technology</subject><subject>Inter-cycle variability</subject><subject>Internal combustion engines: gazoline engine, diesel engines, etc</subject><subject>Mathematical models</subject><subject>MCMC</subject><subject>Mechanical engineering. Machine design</subject><subject>Mechanical systems</subject><subject>Monte Carlo methods</subject><subject>Resonant frequencies</subject><subject>Resonant frequency</subject><subject>Statistical inference</subject><subject>Time series</subject><issn>0888-3270</issn><issn>1096-1216</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><recordid>eNp9kE9v1DAQxS1UJLaFT8DFF8QpYSb22vGBA_0DVKrEgd4t40xarxJ78aSV9tuTZSuOnEYjvffmzU-I9wgtAppPu_YwM-_bDhBbMC2gfiU2CM402KE5Exvo-75RnYU34px5BwBOg9mIn5fhQJxClnMZaGI5liqXR5IDLVTnlMOSSpZllJW45JAXOVb6_UQ5JmKZsgzy-lYO60KTpPyQMr0Vr8cwMb17mRfi_uvN_dX35u7Ht9urL3dN1AhLo9UvVNu-i9Fht91qZcPWOBV1RxgHJAXOYgStre2Di2TGaLuIwToFQ1TqQnw8xe5rWQvx4ufEkaYpZCpP7J1RvUGn9KpUJ2WshbnS6Pc1zaEePII_AvQ7_xegPwL0YPwKcHV9eMkPHMM01rD-zP-snbZgsT_2-HzSrfjoOVH1vLLJkYZUKS5-KOm_d_4A_ryG6w</recordid><startdate>2012</startdate><enddate>2012</enddate><creator>Bodisco, Timothy</creator><creator>Reeves, Robert</creator><creator>Situ, Rong</creator><creator>Brown, Richard</creator><general>Elsevier Ltd</general><general>Elsevier</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>2012</creationdate><title>Bayesian models for the determination of resonant frequencies in a DI diesel engine</title><author>Bodisco, Timothy ; Reeves, Robert ; Situ, Rong ; Brown, Richard</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c410t-43b13582cc91255437a5693c42e1cd1e30971c044778a9ce6fc72c1a7930dc33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Applied sciences</topic><topic>Combustion chambers</topic><topic>Computer simulation</topic><topic>Diesel engines</topic><topic>Engines and turbines</topic><topic>Exact sciences and technology</topic><topic>Inter-cycle variability</topic><topic>Internal combustion engines: gazoline engine, diesel engines, etc</topic><topic>Mathematical models</topic><topic>MCMC</topic><topic>Mechanical engineering. Machine design</topic><topic>Mechanical systems</topic><topic>Monte Carlo methods</topic><topic>Resonant frequencies</topic><topic>Resonant frequency</topic><topic>Statistical inference</topic><topic>Time series</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bodisco, Timothy</creatorcontrib><creatorcontrib>Reeves, Robert</creatorcontrib><creatorcontrib>Situ, Rong</creatorcontrib><creatorcontrib>Brown, Richard</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Mechanical systems and signal processing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Bodisco, Timothy</au><au>Reeves, Robert</au><au>Situ, Rong</au><au>Brown, Richard</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Bayesian models for the determination of resonant frequencies in a DI diesel engine</atitle><jtitle>Mechanical systems and signal processing</jtitle><date>2012</date><risdate>2012</risdate><volume>26</volume><issue>JAN</issue><spage>305</spage><epage>314</epage><pages>305-314</pages><issn>0888-3270</issn><eissn>1096-1216</eissn><abstract>A time series method for the determination of combustion chamber resonant frequencies is outlined. 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► Propose the use of Bayesian statistics in engine research. ► Demonstrate Bayesian model development to analyse in-cylinder pressure signals. ► Locate the resonant frequency of in-cylinder pressure signals. ► Establish a connection between frequency, temperature and trapped mass. ► Confirm the importance of considering inter-cycle variability.</abstract><cop>Kidlington</cop><pub>Elsevier Ltd</pub><doi>10.1016/j.ymssp.2011.06.014</doi><tpages>10</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0888-3270 |
| ispartof | Mechanical systems and signal processing, 2012, Vol.26 (JAN), p.305-314 |
| issn | 0888-3270 1096-1216 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_963861934 |
| source | Elsevier ScienceDirect Journals Complete |
| subjects | Applied sciences Combustion chambers Computer simulation Diesel engines Engines and turbines Exact sciences and technology Inter-cycle variability Internal combustion engines: gazoline engine, diesel engines, etc Mathematical models MCMC Mechanical engineering. Machine design Mechanical systems Monte Carlo methods Resonant frequencies Resonant frequency Statistical inference Time series |
| title | Bayesian models for the determination of resonant frequencies in a DI diesel engine |
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