Identification of parameters in the torsional dynamics of a drilling process through Bayesian statistics
Mec\'anica Computacional, vol. 32, pp. 763-773, 2013 This work presents the estimation of the parameters of an experimental setup, which is modeled as a system with three degrees of freedom, composed by a shaft, two rotors, and a DC motor, that emulates a drilling process. A Bayesian technique...
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext bestellen |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | |
|---|---|
| container_issue | |
| container_start_page | |
| container_title | |
| container_volume | |
| creator | Sandoval, Mario Germán CunhaJr, Americo Sampaio, Rubens |
| description | Mec\'anica Computacional, vol. 32, pp. 763-773, 2013 This work presents the estimation of the parameters of an experimental setup,
which is modeled as a system with three degrees of freedom, composed by a
shaft, two rotors, and a DC motor, that emulates a drilling process. A Bayesian
technique is used in the estimation process, to take into account the
uncertainties and variabilities intrinsic to the measurement taken, which are
modeled as a noise of Gaussian nature. With this procedure it is expected to
check the reliability of the nominal values of the physical parameters of the
test rig. An estimation process assuming that nine parameters of the
experimental apparatus are unknown is conducted, and the results show that for
some quantities the relative deviation with respect to the nominal values is
very high. This deviation evidentiates a strong deficiency in the mathematical
model used to describe the dynamic behavior of the experimental apparatus. |
| doi_str_mv | 10.48550/arxiv.2107.13535 |
| format | Article |
| fullrecord | <record><control><sourceid>arxiv_GOX</sourceid><recordid>TN_cdi_arxiv_primary_2107_13535</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2107_13535</sourcerecordid><originalsourceid>FETCH-LOGICAL-a675-eb005e6bb25a9641e7eadfd9c65d6b2ed2e82f894cfbe30628cd599d63050afb3</originalsourceid><addsrcrecordid>eNotj71OwzAUhb0woMIDMOEXSHDs2ElGqPipVImle3RtXzeWEieyDSJvT1qYznDO-aSPkIeKlXUrJXuC-OO_S16xpqyEFPKWDAeLIXvnDWQ_Bzo7ukCECTPGRH2geUCa55i2EkZq1wCTN-myA2qjH0cfznSJs8GUtnGcv84DfYEVk4dAU96wKW-PO3LjYEx4_587cnp7Pe0_iuPn-2H_fCxANbJAzZhEpTWX0Km6wgbBOtsZJa3SHC3Hlru2q43TKJjirbGy66wSTDJwWuzI4x_2qtov0U8Q1_6i3F-VxS_uwlSB</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype></control><display><type>article</type><title>Identification of parameters in the torsional dynamics of a drilling process through Bayesian statistics</title><source>arXiv.org</source><creator>Sandoval, Mario Germán ; CunhaJr, Americo ; Sampaio, Rubens</creator><creatorcontrib>Sandoval, Mario Germán ; CunhaJr, Americo ; Sampaio, Rubens</creatorcontrib><description>Mec\'anica Computacional, vol. 32, pp. 763-773, 2013 This work presents the estimation of the parameters of an experimental setup,
which is modeled as a system with three degrees of freedom, composed by a
shaft, two rotors, and a DC motor, that emulates a drilling process. A Bayesian
technique is used in the estimation process, to take into account the
uncertainties and variabilities intrinsic to the measurement taken, which are
modeled as a noise of Gaussian nature. With this procedure it is expected to
check the reliability of the nominal values of the physical parameters of the
test rig. An estimation process assuming that nine parameters of the
experimental apparatus are unknown is conducted, and the results show that for
some quantities the relative deviation with respect to the nominal values is
very high. This deviation evidentiates a strong deficiency in the mathematical
model used to describe the dynamic behavior of the experimental apparatus.</description><identifier>DOI: 10.48550/arxiv.2107.13535</identifier><language>eng</language><subject>Computer Science - Computational Engineering, Finance, and Science ; Physics - Data Analysis, Statistics and Probability ; Statistics - Applications ; Statistics - Methodology</subject><creationdate>2021-07</creationdate><rights>http://arxiv.org/licenses/nonexclusive-distrib/1.0</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>228,230,778,883</link.rule.ids><linktorsrc>$$Uhttps://arxiv.org/abs/2107.13535$$EView_record_in_Cornell_University$$FView_record_in_$$GCornell_University$$Hfree_for_read</linktorsrc><backlink>$$Uhttps://doi.org/10.48550/arXiv.2107.13535$$DView paper in arXiv$$Hfree_for_read</backlink></links><search><creatorcontrib>Sandoval, Mario Germán</creatorcontrib><creatorcontrib>CunhaJr, Americo</creatorcontrib><creatorcontrib>Sampaio, Rubens</creatorcontrib><title>Identification of parameters in the torsional dynamics of a drilling process through Bayesian statistics</title><description>Mec\'anica Computacional, vol. 32, pp. 763-773, 2013 This work presents the estimation of the parameters of an experimental setup,
which is modeled as a system with three degrees of freedom, composed by a
shaft, two rotors, and a DC motor, that emulates a drilling process. A Bayesian
technique is used in the estimation process, to take into account the
uncertainties and variabilities intrinsic to the measurement taken, which are
modeled as a noise of Gaussian nature. With this procedure it is expected to
check the reliability of the nominal values of the physical parameters of the
test rig. An estimation process assuming that nine parameters of the
experimental apparatus are unknown is conducted, and the results show that for
some quantities the relative deviation with respect to the nominal values is
very high. This deviation evidentiates a strong deficiency in the mathematical
model used to describe the dynamic behavior of the experimental apparatus.</description><subject>Computer Science - Computational Engineering, Finance, and Science</subject><subject>Physics - Data Analysis, Statistics and Probability</subject><subject>Statistics - Applications</subject><subject>Statistics - Methodology</subject><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>GOX</sourceid><recordid>eNotj71OwzAUhb0woMIDMOEXSHDs2ElGqPipVImle3RtXzeWEieyDSJvT1qYznDO-aSPkIeKlXUrJXuC-OO_S16xpqyEFPKWDAeLIXvnDWQ_Bzo7ukCECTPGRH2geUCa55i2EkZq1wCTN-myA2qjH0cfznSJs8GUtnGcv84DfYEVk4dAU96wKW-PO3LjYEx4_587cnp7Pe0_iuPn-2H_fCxANbJAzZhEpTWX0Km6wgbBOtsZJa3SHC3Hlru2q43TKJjirbGy66wSTDJwWuzI4x_2qtov0U8Q1_6i3F-VxS_uwlSB</recordid><startdate>20210726</startdate><enddate>20210726</enddate><creator>Sandoval, Mario Germán</creator><creator>CunhaJr, Americo</creator><creator>Sampaio, Rubens</creator><scope>AKY</scope><scope>EPD</scope><scope>GOX</scope></search><sort><creationdate>20210726</creationdate><title>Identification of parameters in the torsional dynamics of a drilling process through Bayesian statistics</title><author>Sandoval, Mario Germán ; CunhaJr, Americo ; Sampaio, Rubens</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-a675-eb005e6bb25a9641e7eadfd9c65d6b2ed2e82f894cfbe30628cd599d63050afb3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Computer Science - Computational Engineering, Finance, and Science</topic><topic>Physics - Data Analysis, Statistics and Probability</topic><topic>Statistics - Applications</topic><topic>Statistics - Methodology</topic><toplevel>online_resources</toplevel><creatorcontrib>Sandoval, Mario Germán</creatorcontrib><creatorcontrib>CunhaJr, Americo</creatorcontrib><creatorcontrib>Sampaio, Rubens</creatorcontrib><collection>arXiv Computer Science</collection><collection>arXiv Statistics</collection><collection>arXiv.org</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Sandoval, Mario Germán</au><au>CunhaJr, Americo</au><au>Sampaio, Rubens</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Identification of parameters in the torsional dynamics of a drilling process through Bayesian statistics</atitle><date>2021-07-26</date><risdate>2021</risdate><abstract>Mec\'anica Computacional, vol. 32, pp. 763-773, 2013 This work presents the estimation of the parameters of an experimental setup,
which is modeled as a system with three degrees of freedom, composed by a
shaft, two rotors, and a DC motor, that emulates a drilling process. A Bayesian
technique is used in the estimation process, to take into account the
uncertainties and variabilities intrinsic to the measurement taken, which are
modeled as a noise of Gaussian nature. With this procedure it is expected to
check the reliability of the nominal values of the physical parameters of the
test rig. An estimation process assuming that nine parameters of the
experimental apparatus are unknown is conducted, and the results show that for
some quantities the relative deviation with respect to the nominal values is
very high. This deviation evidentiates a strong deficiency in the mathematical
model used to describe the dynamic behavior of the experimental apparatus.</abstract><doi>10.48550/arxiv.2107.13535</doi><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext_linktorsrc |
| identifier | DOI: 10.48550/arxiv.2107.13535 |
| ispartof | |
| issn | |
| language | eng |
| recordid | cdi_arxiv_primary_2107_13535 |
| source | arXiv.org |
| subjects | Computer Science - Computational Engineering, Finance, and Science Physics - Data Analysis, Statistics and Probability Statistics - Applications Statistics - Methodology |
| title | Identification of parameters in the torsional dynamics of a drilling process through Bayesian statistics |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-01-16T12%3A29%3A54IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-arxiv_GOX&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Identification%20of%20parameters%20in%20the%20torsional%20dynamics%20of%20a%20drilling%20process%20through%20Bayesian%20statistics&rft.au=Sandoval,%20Mario%20Germ%C3%A1n&rft.date=2021-07-26&rft_id=info:doi/10.48550/arxiv.2107.13535&rft_dat=%3Carxiv_GOX%3E2107_13535%3C/arxiv_GOX%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_id=info:pmid/&rfr_iscdi=true |