Image-based chip detection during turning
This study proposes a method to analyze chip formation using camera surveillance to enhance safety and efficiency in machine operations. The process involved the face and straight turning of a workpiece under the observation of a camera strategically placed within the workspace. The suggested algori...
Gespeichert in:
Veröffentlicht in: | International journal of advanced manufacturing technology 2024-12, Vol.135 (7-8), p.3219-3227 |
---|---|
Hauptverfasser: | , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
container_end_page | 3227 |
---|---|
container_issue | 7-8 |
container_start_page | 3219 |
container_title | International journal of advanced manufacturing technology |
container_volume | 135 |
creator | Filep, Tamás Andó, Mátyás Szekeres, Béla J. |
description | This study proposes a method to analyze chip formation using camera surveillance to enhance safety and efficiency in machine operations. The process involved the face and straight turning of a workpiece under the observation of a camera strategically placed within the workspace. The suggested algorithm carries out initial image preprocessing and edge detection, followed by background subtraction to isolate dynamic elements and filtering based on the size of the objects. Pre-determined masks are applied to eliminate overlaps with existing workspace objects, based on the tool’s trajectory. The research validates that the applied technique effectively recognizes chips in both face and straight turning. Specific filtering techniques improve the algorithm’s capability to detect even smaller chips, and it substantially reduces false alarms, laying the groundwork for long, continuous chip detection systems. |
doi_str_mv | 10.1007/s00170-024-14637-x |
format | Article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_journals_3126437828</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>3126437828</sourcerecordid><originalsourceid>FETCH-LOGICAL-c244t-5a0e7b79e511cbbf96152585317e2ca22d466f9e359cea468d229d633ccc55633</originalsourceid><addsrcrecordid>eNp9kLtOwzAUhi0EEqXwAkyRmBgMPr5nRBWUSpVYYLYc56Skok2wE6m8PS5BYmP6l_9yzkfINbA7YMzcJ8bAMMq4pCC1MPRwQmYghaCCgTolM8a1pcJoe04uUtpmuwZtZ-R2tfMbpJVPWBfhve2LGgcMQ9vti3qM7X5TDGPcZ70kZ43_SHj1q3Py9vT4unim65flavGwpoFLOVDlGZrKlKgAQlU1pQbFlVUCDPLgOa-l1k2JQpUBvdS25rystRAhBKWyzsnN1NvH7nPENLhtly_Ik04A11IYy2128ckVYpdSxMb1sd35-OWAuSMSNyFxGYn7QeIOOSSmUOqPn2H8q_4n9Q2TFmKv</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3126437828</pqid></control><display><type>article</type><title>Image-based chip detection during turning</title><source>SpringerNature Journals</source><creator>Filep, Tamás ; Andó, Mátyás ; Szekeres, Béla J.</creator><creatorcontrib>Filep, Tamás ; Andó, Mátyás ; Szekeres, Béla J.</creatorcontrib><description>This study proposes a method to analyze chip formation using camera surveillance to enhance safety and efficiency in machine operations. The process involved the face and straight turning of a workpiece under the observation of a camera strategically placed within the workspace. The suggested algorithm carries out initial image preprocessing and edge detection, followed by background subtraction to isolate dynamic elements and filtering based on the size of the objects. Pre-determined masks are applied to eliminate overlaps with existing workspace objects, based on the tool’s trajectory. The research validates that the applied technique effectively recognizes chips in both face and straight turning. Specific filtering techniques improve the algorithm’s capability to detect even smaller chips, and it substantially reduces false alarms, laying the groundwork for long, continuous chip detection systems.</description><identifier>ISSN: 0268-3768</identifier><identifier>EISSN: 1433-3015</identifier><identifier>DOI: 10.1007/s00170-024-14637-x</identifier><language>eng</language><publisher>London: Springer London</publisher><subject>Advanced manufacturing technologies ; Algorithms ; CAE) and Design ; Cameras ; Chip formation ; Computer-Aided Engineering (CAD ; Edge detection ; Efficiency ; Engineering ; False alarms ; Image enhancement ; Image filters ; Industrial and Production Engineering ; Manufacturing ; Mechanical Engineering ; Media Management ; Methods ; Original Article ; Workpieces</subject><ispartof>International journal of advanced manufacturing technology, 2024-12, Vol.135 (7-8), p.3219-3227</ispartof><rights>The Author(s) 2024</rights><rights>The Author(s) 2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c244t-5a0e7b79e511cbbf96152585317e2ca22d466f9e359cea468d229d633ccc55633</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s00170-024-14637-x$$EPDF$$P50$$Gspringer$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s00170-024-14637-x$$EHTML$$P50$$Gspringer$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids></links><search><creatorcontrib>Filep, Tamás</creatorcontrib><creatorcontrib>Andó, Mátyás</creatorcontrib><creatorcontrib>Szekeres, Béla J.</creatorcontrib><title>Image-based chip detection during turning</title><title>International journal of advanced manufacturing technology</title><addtitle>Int J Adv Manuf Technol</addtitle><description>This study proposes a method to analyze chip formation using camera surveillance to enhance safety and efficiency in machine operations. The process involved the face and straight turning of a workpiece under the observation of a camera strategically placed within the workspace. The suggested algorithm carries out initial image preprocessing and edge detection, followed by background subtraction to isolate dynamic elements and filtering based on the size of the objects. Pre-determined masks are applied to eliminate overlaps with existing workspace objects, based on the tool’s trajectory. The research validates that the applied technique effectively recognizes chips in both face and straight turning. Specific filtering techniques improve the algorithm’s capability to detect even smaller chips, and it substantially reduces false alarms, laying the groundwork for long, continuous chip detection systems.</description><subject>Advanced manufacturing technologies</subject><subject>Algorithms</subject><subject>CAE) and Design</subject><subject>Cameras</subject><subject>Chip formation</subject><subject>Computer-Aided Engineering (CAD</subject><subject>Edge detection</subject><subject>Efficiency</subject><subject>Engineering</subject><subject>False alarms</subject><subject>Image enhancement</subject><subject>Image filters</subject><subject>Industrial and Production Engineering</subject><subject>Manufacturing</subject><subject>Mechanical Engineering</subject><subject>Media Management</subject><subject>Methods</subject><subject>Original Article</subject><subject>Workpieces</subject><issn>0268-3768</issn><issn>1433-3015</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><recordid>eNp9kLtOwzAUhi0EEqXwAkyRmBgMPr5nRBWUSpVYYLYc56Skok2wE6m8PS5BYmP6l_9yzkfINbA7YMzcJ8bAMMq4pCC1MPRwQmYghaCCgTolM8a1pcJoe04uUtpmuwZtZ-R2tfMbpJVPWBfhve2LGgcMQ9vti3qM7X5TDGPcZ70kZ43_SHj1q3Py9vT4unim65flavGwpoFLOVDlGZrKlKgAQlU1pQbFlVUCDPLgOa-l1k2JQpUBvdS25rystRAhBKWyzsnN1NvH7nPENLhtly_Ik04A11IYy2128ckVYpdSxMb1sd35-OWAuSMSNyFxGYn7QeIOOSSmUOqPn2H8q_4n9Q2TFmKv</recordid><startdate>20241201</startdate><enddate>20241201</enddate><creator>Filep, Tamás</creator><creator>Andó, Mátyás</creator><creator>Szekeres, Béla J.</creator><general>Springer London</general><general>Springer Nature B.V</general><scope>C6C</scope><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>20241201</creationdate><title>Image-based chip detection during turning</title><author>Filep, Tamás ; Andó, Mátyás ; Szekeres, Béla J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c244t-5a0e7b79e511cbbf96152585317e2ca22d466f9e359cea468d229d633ccc55633</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Advanced manufacturing technologies</topic><topic>Algorithms</topic><topic>CAE) and Design</topic><topic>Cameras</topic><topic>Chip formation</topic><topic>Computer-Aided Engineering (CAD</topic><topic>Edge detection</topic><topic>Efficiency</topic><topic>Engineering</topic><topic>False alarms</topic><topic>Image enhancement</topic><topic>Image filters</topic><topic>Industrial and Production Engineering</topic><topic>Manufacturing</topic><topic>Mechanical Engineering</topic><topic>Media Management</topic><topic>Methods</topic><topic>Original Article</topic><topic>Workpieces</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Filep, Tamás</creatorcontrib><creatorcontrib>Andó, Mátyás</creatorcontrib><creatorcontrib>Szekeres, Béla J.</creatorcontrib><collection>Springer Nature OA Free Journals</collection><collection>CrossRef</collection><jtitle>International journal of advanced manufacturing technology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Filep, Tamás</au><au>Andó, Mátyás</au><au>Szekeres, Béla J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Image-based chip detection during turning</atitle><jtitle>International journal of advanced manufacturing technology</jtitle><stitle>Int J Adv Manuf Technol</stitle><date>2024-12-01</date><risdate>2024</risdate><volume>135</volume><issue>7-8</issue><spage>3219</spage><epage>3227</epage><pages>3219-3227</pages><issn>0268-3768</issn><eissn>1433-3015</eissn><abstract>This study proposes a method to analyze chip formation using camera surveillance to enhance safety and efficiency in machine operations. The process involved the face and straight turning of a workpiece under the observation of a camera strategically placed within the workspace. The suggested algorithm carries out initial image preprocessing and edge detection, followed by background subtraction to isolate dynamic elements and filtering based on the size of the objects. Pre-determined masks are applied to eliminate overlaps with existing workspace objects, based on the tool’s trajectory. The research validates that the applied technique effectively recognizes chips in both face and straight turning. Specific filtering techniques improve the algorithm’s capability to detect even smaller chips, and it substantially reduces false alarms, laying the groundwork for long, continuous chip detection systems.</abstract><cop>London</cop><pub>Springer London</pub><doi>10.1007/s00170-024-14637-x</doi><tpages>9</tpages><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0268-3768 |
ispartof | International journal of advanced manufacturing technology, 2024-12, Vol.135 (7-8), p.3219-3227 |
issn | 0268-3768 1433-3015 |
language | eng |
recordid | cdi_proquest_journals_3126437828 |
source | SpringerNature Journals |
subjects | Advanced manufacturing technologies Algorithms CAE) and Design Cameras Chip formation Computer-Aided Engineering (CAD Edge detection Efficiency Engineering False alarms Image enhancement Image filters Industrial and Production Engineering Manufacturing Mechanical Engineering Media Management Methods Original Article Workpieces |
title | Image-based chip detection during turning |
url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2024-12-22T12%3A55%3A51IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Image-based%20chip%20detection%20during%20turning&rft.jtitle=International%20journal%20of%20advanced%20manufacturing%20technology&rft.au=Filep,%20Tam%C3%A1s&rft.date=2024-12-01&rft.volume=135&rft.issue=7-8&rft.spage=3219&rft.epage=3227&rft.pages=3219-3227&rft.issn=0268-3768&rft.eissn=1433-3015&rft_id=info:doi/10.1007/s00170-024-14637-x&rft_dat=%3Cproquest_cross%3E3126437828%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=3126437828&rft_id=info:pmid/&rfr_iscdi=true |