Parallel Cross-section Recognition of Geometrical Features for Selected Machine Parts
Increase of automation and autonomy of production is the latest trend incorporated into Industry 4.0 objectives. Production autonomy is very desirable in the field of damaged parts replacement. To fulfill this goal numerous reverse engineering systems have been developed that support geometry recogn...
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| Format: | Article |
| Language: | English |
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Publishing House of Wrocław Board of Scientific Technical Societies Federation NOT
2021-08-01
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| Series: | Journal of Machine Engineering |
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| Online Access: | http://jmacheng.not.pl/Parallel-Cross-section-Recognition-of-Geometrical-Features-for-Selected-Machine-Parts,141500,0,2.html |
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| _version_ | 1849773758189928448 |
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| author | Marcin Gołaszewski Marcin Królikowski Bartosz Powałka |
| author_facet | Marcin Gołaszewski Marcin Królikowski Bartosz Powałka |
| author_sort | Marcin Gołaszewski |
| collection | DOAJ |
| description | Increase of automation and autonomy of production is the latest trend incorporated into Industry 4.0 objectives. Production autonomy is very desirable in the field of damaged parts replacement. To fulfill this goal numerous reverse engineering systems have been developed that support geometry recognition from the 3D scan data. This study is focused on converting non-parametric geometry representation of shaft-type elements into a CAD model with a rebuilt feature tree. Algorithms are based on the analysis of parallel cross-sections. The proposed system is also capable of identification of additional geometric features typical for 2.5 axes milling such as pockets, islands and outer walls. The proposed algorithms are optimized to increase efficiency of the process. Initial identification parameters are selected with respect to defined criteria, e.g. identification accuracy, computing power and scanning accuracy. Described algorithms can be implemented in reverse engineering systems. |
| format | Article |
| id | doaj-art-32c06ed127fe48ba8d010b64ffdb141c |
| institution | DOAJ |
| issn | 1895-7595 2391-8071 |
| language | English |
| publishDate | 2021-08-01 |
| publisher | Publishing House of Wrocław Board of Scientific Technical Societies Federation NOT |
| record_format | Article |
| series | Journal of Machine Engineering |
| spelling | doaj-art-32c06ed127fe48ba8d010b64ffdb141c2025-08-20T03:01:58ZengPublishing House of Wrocław Board of Scientific Technical Societies Federation NOTJournal of Machine Engineering1895-75952391-80712021-08-01213607910.36897/jme/141500141500Parallel Cross-section Recognition of Geometrical Features for Selected Machine PartsMarcin Gołaszewski0https://orcid.org/0000-0002-8221-7769Marcin Królikowski1https://orcid.org/0000-0002-3668-8463Bartosz Powałka2https://orcid.org/0000-0002-6850-4614Faculty of Mechanical Engineering and Mechatronics, West Pomeranian University of Technology, PolandFaculty of Mechanical Engineering and Mechatronics, West Pomeranian University of Technology, PolandFaculty of Mechanical Engineering and Mechatronics, West Pomeranian University of Technology, PolandIncrease of automation and autonomy of production is the latest trend incorporated into Industry 4.0 objectives. Production autonomy is very desirable in the field of damaged parts replacement. To fulfill this goal numerous reverse engineering systems have been developed that support geometry recognition from the 3D scan data. This study is focused on converting non-parametric geometry representation of shaft-type elements into a CAD model with a rebuilt feature tree. Algorithms are based on the analysis of parallel cross-sections. The proposed system is also capable of identification of additional geometric features typical for 2.5 axes milling such as pockets, islands and outer walls. The proposed algorithms are optimized to increase efficiency of the process. Initial identification parameters are selected with respect to defined criteria, e.g. identification accuracy, computing power and scanning accuracy. Described algorithms can be implemented in reverse engineering systems.http://jmacheng.not.pl/Parallel-Cross-section-Recognition-of-Geometrical-Features-for-Selected-Machine-Parts,141500,0,2.htmlfeature recognitioncomputer aided reengineering3d scanningparametric geometry |
| spellingShingle | Marcin Gołaszewski Marcin Królikowski Bartosz Powałka Parallel Cross-section Recognition of Geometrical Features for Selected Machine Parts Journal of Machine Engineering feature recognition computer aided reengineering 3d scanning parametric geometry |
| title | Parallel Cross-section Recognition of Geometrical Features for Selected Machine Parts |
| title_full | Parallel Cross-section Recognition of Geometrical Features for Selected Machine Parts |
| title_fullStr | Parallel Cross-section Recognition of Geometrical Features for Selected Machine Parts |
| title_full_unstemmed | Parallel Cross-section Recognition of Geometrical Features for Selected Machine Parts |
| title_short | Parallel Cross-section Recognition of Geometrical Features for Selected Machine Parts |
| title_sort | parallel cross section recognition of geometrical features for selected machine parts |
| topic | feature recognition computer aided reengineering 3d scanning parametric geometry |
| url | http://jmacheng.not.pl/Parallel-Cross-section-Recognition-of-Geometrical-Features-for-Selected-Machine-Parts,141500,0,2.html |
| work_keys_str_mv | AT marcingołaszewski parallelcrosssectionrecognitionofgeometricalfeaturesforselectedmachineparts AT marcinkrolikowski parallelcrosssectionrecognitionofgeometricalfeaturesforselectedmachineparts AT bartoszpowałka parallelcrosssectionrecognitionofgeometricalfeaturesforselectedmachineparts |