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1. Identity statement
Reference TypeConference Paper (Conference Proceedings)
Sitesibgrapi.sid.inpe.br
Holder Codeibi 8JMKD3MGPEW34M/46T9EHH
Identifier8JMKD3MGPEW34M/43BD8EH
Repositorysid.inpe.br/sibgrapi/2020/09.30.01.28
Last Update2020:09.30.01.28.55 (UTC) administrator
Metadata Repositorysid.inpe.br/sibgrapi/2020/09.30.01.28.55
Metadata Last Update2022:06.14.00.00.13 (UTC) administrator
DOI10.1109/SIBGRAPI51738.2020.00045
Citation KeyDuarteCoDiBoDuDr:2020:ThNoIn
TitleThermographic Non-Invasive Inspection Modelling of Fertilizer Pipelines Using Neural Networks
FormatOn-line
Year2020
Access Date2024, Oct. 15
Number of Files1
Size1158 KiB
2. Context
Author1 Duarte, Marta
2 Coch, Victor
3 Dias, Jovania
4 Botelho, Silvia
5 Duarte, Nelson
6 Drews Jr, Paulo
Affiliation1 Federal University of Rio Grande (FURG), Brazil
2 Federal University of Rio Grande (FURG), Brazil
3 Federal University of Rio Grande (FURG), Brazil
4 Federal University of Rio Grande (FURG), Brazil
5 Federal University of Rio Grande (FURG), Brazil
6 Federal University of Rio Grande (FURG), Brazil
EditorMusse, Soraia Raupp
Cesar Junior, Roberto Marcondes
Pelechano, Nuria
Wang, Zhangyang (Atlas)
e-Mail Addressmarta.anjosduarte@gmail.com
Conference NameConference on Graphics, Patterns and Images, 33 (SIBGRAPI)
Conference LocationPorto de Galinhas (virtual)
Date7-10 Nov. 2020
PublisherIEEE Computer Society
Publisher CityLos Alamitos
Book TitleProceedings
Tertiary TypeFull Paper
History (UTC)2020-09-30 01:28:55 :: marta.anjosduarte@gmail.com -> administrator ::
2022-06-14 00:00:13 :: administrator -> marta.anjosduarte@gmail.com :: 2020
3. Content and structure
Is the master or a copy?is the master
Content Stagecompleted
Transferable1
Version Typefinaldraft
Keywordsthermal image
pipeline inspection
neural networks
fertilizer
AbstractIndustry pipeline fault, like blockage can create major problems for engineers and financial loss for the company. The blockage detection is necessary for smooth functioning of an industry and safety of the environment. This work presents a model for non-invasive inspection of pipes. It proposes the use of a neural network to identify the obstruction stage in fertilizer industry, using external thermal images obtained from the pipelines. A dataset capable of mapping the external thermal behavior in profile of the internal deposit is developed. The Multilayer Perceptron neural network was able to learn the thermal pixel mapping in a deposit profile, obtaining satisfactory results.
Arrangement 1urlib.net > SDLA > Fonds > SIBGRAPI 2020 > Thermographic Non-Invasive Inspection...
Arrangement 2urlib.net > SDLA > Fonds > Full Index > Thermographic Non-Invasive Inspection...
doc Directory Contentaccess
source Directory Contentthere are no files
agreement Directory Content
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4. Conditions of access and use
data URLhttp://urlib.net/ibi/8JMKD3MGPEW34M/43BD8EH
zipped data URLhttp://urlib.net/zip/8JMKD3MGPEW34M/43BD8EH
Languageen
Target FilePaper ID 120.pdf
User Groupmarta.anjosduarte@gmail.com
Visibilityshown
Update Permissionnot transferred
5. Allied materials
Mirror Repositorysid.inpe.br/banon/2001/03.30.15.38.24
Next Higher Units8JMKD3MGPEW34M/43G4L9S
8JMKD3MGPEW34M/4742MCS
Citing Item Listsid.inpe.br/sibgrapi/2020/10.28.20.46 43
sid.inpe.br/sibgrapi/2022/06.10.21.49 4
Host Collectionsid.inpe.br/banon/2001/03.30.15.38
6. Notes
Empty Fieldsarchivingpolicy archivist area callnumber contenttype copyholder copyright creatorhistory descriptionlevel dissemination edition electronicmailaddress group isbn issn label lineage mark nextedition notes numberofvolumes orcid organization pages parameterlist parentrepositories previousedition previouslowerunit progress project readergroup readpermission resumeid rightsholder schedulinginformation secondarydate secondarykey secondarymark secondarytype serieseditor session shorttitle sponsor subject tertiarymark type url volume
7. Description control
e-Mail (login)marta.anjosduarte@gmail.com
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