Identification of Wear Products in the Automotive Tribotechnical System Using Computer Vision Methods, Artificial Intelligence and Big Data
It has been emphasizing the importance of wear products identification during the automotive tribotechnical system operation. Some examples and concepts of combining and applying of computer vision, artificial intelligence, and big data techniques to identify the wear products has presented. Several...
Gespeichert in:
| Veröffentlicht in: | 2019 XIth International Scientific and Practical Conference on Electronics and Information Technologies (ELIT) S. 24 - 27 |
|---|---|
| Hauptverfasser: | , |
| Format: | Tagungsbericht |
| Sprache: | Englisch |
| Veröffentlicht: |
IEEE
01.09.2019
|
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| Abstract | It has been emphasizing the importance of wear products identification during the automotive tribotechnical system operation. Some examples and concepts of combining and applying of computer vision, artificial intelligence, and big data techniques to identify the wear products has presented. Several examples of proposed technology for recognizing wear products are presented. The following algorithm was used to obtain the surface shape of the wear particles. On the original image, an area corresponding to the studied object is allocated. In this case, the high reflectivity of wear particles was used compared with the background and the methods of threshold separation. Then a sharp object diagram (on the basis of which a distance map was calculated) was developed. The distance map has constructed in such way that the brighter the pixel of the image, the closer in this place the surface of the object to the observer. For example, the range map contains information on the shape of the surface of the wear particle. The software of the tribotechnical system was written in the Object Pascal programming language in the Delphi visual programming environment. It has been presented some examples and concepts for combining and applying computer vision, artificial intelligence, and big data techniques to identify wearing products. Further development of the industry and modern technologies will promote the introduction and improvement of such expert technology. |
|---|---|
| AbstractList | It has been emphasizing the importance of wear products identification during the automotive tribotechnical system operation. Some examples and concepts of combining and applying of computer vision, artificial intelligence, and big data techniques to identify the wear products has presented. Several examples of proposed technology for recognizing wear products are presented. The following algorithm was used to obtain the surface shape of the wear particles. On the original image, an area corresponding to the studied object is allocated. In this case, the high reflectivity of wear particles was used compared with the background and the methods of threshold separation. Then a sharp object diagram (on the basis of which a distance map was calculated) was developed. The distance map has constructed in such way that the brighter the pixel of the image, the closer in this place the surface of the object to the observer. For example, the range map contains information on the shape of the surface of the wear particle. The software of the tribotechnical system was written in the Object Pascal programming language in the Delphi visual programming environment. It has been presented some examples and concepts for combining and applying computer vision, artificial intelligence, and big data techniques to identify wearing products. Further development of the industry and modern technologies will promote the introduction and improvement of such expert technology. |
| Author | Balitskii, Olexiy Kolesnikov, Valerii |
| Author_xml | – sequence: 1 givenname: Olexiy surname: Balitskii fullname: Balitskii, Olexiy organization: Ivan Franko National University of Lviv,Faculty of Electronics and Computer Technolodies,System Design Department,Lviv,Ukraine – sequence: 2 givenname: Valerii surname: Kolesnikov fullname: Kolesnikov, Valerii organization: Taras Shevchenko National University in Starobilsk,starobilsk,Ukraine |
| BookMark | eNotkM1OAjEURmuiC394AOPmPoDgdEpnOktE1Ekwmgi6JJ32Fm4y05JOMeEZfGlRWX2rc07yXbBTHzwyds2zEedZdTeb14tRnvFqpFSV56U8YYOqVLzMFRey4OqcfdcWfSJHRicKHoKDT9QR3mKwO5N6IA9pgzDZpdCFRF8Ii0hNSGg2_gC18L7vE3aw7MmvYRq67S5hhA_qf3UvmDbB9rcwiX8ROgC1T9i2tEZvELS3cE9reNBJX7Ezp9seB8e9ZMvH2WL6PJy_PtXTyXxInKs0bGwjrDQctVO6yBplUXJ02prcjDNlM6nH2dghOmVLoVA00rqqkaYoLHdCiUt28-8lRFxtI3U67lfHi8QPOZNj-A |
| ContentType | Conference Proceeding |
| DBID | 6IE 6IL CBEJK RIE RIL |
| DOI | 10.1109/ELIT.2019.8892275 |
| DatabaseName | IEEE Electronic Library (IEL) Conference Proceedings IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume IEEE Xplore All Conference Proceedings IEEE Electronic Library (IEL) IEEE Proceedings Order Plans (POP All) 1998-Present |
| DatabaseTitleList | |
| Database_xml | – sequence: 1 dbid: RIE name: IEEE Electronic Library (IEL) url: https://ieeexplore.ieee.org/ sourceTypes: Publisher |
| DeliveryMethod | fulltext_linktorsrc |
| EISBN | 9781728135618 1728135613 |
| EndPage | 27 |
| ExternalDocumentID | 8892275 |
| Genre | orig-research |
| GroupedDBID | 6IE 6IL CBEJK RIE RIL |
| ID | FETCH-LOGICAL-i118t-bdb3d5c1eaf8a60b8de51efadc2c408d05a404feef8d738e3b5df9b5c66d1f383 |
| IEDL.DBID | RIE |
| IngestDate | Thu Jun 29 18:38:58 EDT 2023 |
| IsPeerReviewed | false |
| IsScholarly | false |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-i118t-bdb3d5c1eaf8a60b8de51efadc2c408d05a404feef8d738e3b5df9b5c66d1f383 |
| PageCount | 4 |
| ParticipantIDs | ieee_primary_8892275 |
| PublicationCentury | 2000 |
| PublicationDate | 2019-Sept. |
| PublicationDateYYYYMMDD | 2019-09-01 |
| PublicationDate_xml | – month: 09 year: 2019 text: 2019-Sept. |
| PublicationDecade | 2010 |
| PublicationTitle | 2019 XIth International Scientific and Practical Conference on Electronics and Information Technologies (ELIT) |
| PublicationTitleAbbrev | ELIT |
| PublicationYear | 2019 |
| Publisher | IEEE |
| Publisher_xml | – name: IEEE |
| Score | 1.6982281 |
| Snippet | It has been emphasizing the importance of wear products identification during the automotive tribotechnical system operation. Some examples and concepts of... |
| SourceID | ieee |
| SourceType | Publisher |
| StartPage | 24 |
| SubjectTerms | artificial intelligence automotive big data Computer vision identification Needles Observers Reflection Reflectivity Shape Steel tribotechnical system wear products |
| Title | Identification of Wear Products in the Automotive Tribotechnical System Using Computer Vision Methods, Artificial Intelligence and Big Data |
| URI | https://ieeexplore.ieee.org/document/8892275 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LSwMxEA5t8eBJpRXfzMFj1272mT1WbbGgpYeqvZU8JrKXXWm3_RP-aZPsWhW8eAshMJBJSCb5HoRcU4WYJVJ7VEhToGiReZlG5qFQ1NcMueDCmU2k0ylbLLJZi_R3XBhEdOAzvLFN95evSrmxT2UDxrIgSOM2aadpWnO1mo9K6meD0eNkbrFaNvlu3C_DFHdejA_-F-mQ9L6JdzDbHSlHpIVFl3zUZFrdvK5BqeHVrE870Iq1riEvwFzjYLipHLRui2D1QMpantXkAGpZcnDwAPjycYAXRyuHJ-chve7DcOWCmAUJkx9CncALBbf5G9zzivfI83g0v3vwGg8FLzelQ-UJJUIVS4pcM574gimMKWquZCAjnyk_5pEfaUTNVBoyDEWsdCZimSSKalO-HpNOURZ4QoAGKjHVWhRJq4vGra5OGLMk9JUMzc7Xp6RrJ3L5XstkLJs5PPu7-5zs21zVcK0L0qlWG7wke3Jb5evVlcvtJ2D4rHM |
| linkProvider | IEEE |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV1LTwIxEG4QTfSkBoxv5-CRle2-6B5RIRCBcEDlRvqYGi67Bhb-hH_atouoiRdvTdNkkk6bdtrvQcgtVYhpIrVHhTQFihapl2pkHgpFfc2QCy6c2URrNGLTaTqukMaWC4OIDnyGd7bp_vJVLlf2qazJWBoErXiH7MZRFNCSrbX5qqR-2uwM-hOL1rLpdyN_Waa4E6N7-L9YR6T-Tb2D8fZQOSYVzGrko6TT6s37GuQaXs0KtQOtXOsS5hmYixy0V4UD160RrCJIXgq0mixAKUwODiAAX04O8OKI5TB0LtLLBrQXLohZktD_IdUJPFNwP3-DR17wOnnudiYPPW_jouDNTfFQeEKJUMWSIteMJ75gCmOKmisZyMhnyo955EcaUTPVChmGIlY6FbFMEkW1KWBPSDXLMzwlQAOVmHotiqRVRuNWWSeMWRL6SoZm7-szUrMTOXsvhTJmmzk8_7v7huz3JsPBbNAfPV2QA5u3Erx1SarFYoVXZE-ui_lyce3y_AmAu6-6 |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=proceeding&rft.title=2019+XIth+International+Scientific+and+Practical+Conference+on+Electronics+and+Information+Technologies+%28ELIT%29&rft.atitle=Identification+of+Wear+Products+in+the+Automotive+Tribotechnical+System+Using+Computer+Vision+Methods%2C+Artificial+Intelligence+and+Big+Data&rft.au=Balitskii%2C+Olexiy&rft.au=Kolesnikov%2C+Valerii&rft.date=2019-09-01&rft.pub=IEEE&rft.spage=24&rft.epage=27&rft_id=info:doi/10.1109%2FELIT.2019.8892275&rft.externalDocID=8892275 |