Machine Vision-Based Fatigue Crack Propagation System
This paper introduces a machine vision-based system promising low-cost solution for detecting a fatigue crack propagation caused by alternating mechanical stresses. The fatigue crack in technical components usually starts on surfaces at stress concentration points. The presented system was designed...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2022-09-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/22/18/6852 |
| _version_ | 1827656924182609920 |
|---|---|
| author | Jan Gebauer Pavel Šofer Martin Jurek Renata Wagnerová Jiří Czebe |
| author_facet | Jan Gebauer Pavel Šofer Martin Jurek Renata Wagnerová Jiří Czebe |
| author_sort | Jan Gebauer |
| collection | DOAJ |
| description | This paper introduces a machine vision-based system promising low-cost solution for detecting a fatigue crack propagation caused by alternating mechanical stresses. The fatigue crack in technical components usually starts on surfaces at stress concentration points. The presented system was designed to substitute a strain gauge sensor-based measurement using an industrial camera in cooperation with branding software. This paper presents implementation of a machine vision system and algorithm outputs taking on fatigue crack propagation samples. |
| first_indexed | 2024-03-09T22:35:10Z |
| format | Article |
| id | doaj.art-c3ce47b24b3f4e8d85affca388b621ff |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T22:35:10Z |
| publishDate | 2022-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-c3ce47b24b3f4e8d85affca388b621ff2023-11-23T18:50:21ZengMDPI AGSensors1424-82202022-09-012218685210.3390/s22186852Machine Vision-Based Fatigue Crack Propagation SystemJan Gebauer0Pavel Šofer1Martin Jurek2Renata Wagnerová3Jiří Czebe4Department of Control Systems and Instrumentation, VŠB—Technical University of Ostrava, 708 00 Ostrava, Czech RepublicDepartment of Control Systems and Instrumentation, VŠB—Technical University of Ostrava, 708 00 Ostrava, Czech RepublicDepartment of Control Systems and Instrumentation, VŠB—Technical University of Ostrava, 708 00 Ostrava, Czech RepublicDepartment of Control Systems and Instrumentation, VŠB—Technical University of Ostrava, 708 00 Ostrava, Czech RepublicDepartment of Control Systems and Instrumentation, VŠB—Technical University of Ostrava, 708 00 Ostrava, Czech RepublicThis paper introduces a machine vision-based system promising low-cost solution for detecting a fatigue crack propagation caused by alternating mechanical stresses. The fatigue crack in technical components usually starts on surfaces at stress concentration points. The presented system was designed to substitute a strain gauge sensor-based measurement using an industrial camera in cooperation with branding software. This paper presents implementation of a machine vision system and algorithm outputs taking on fatigue crack propagation samples.https://www.mdpi.com/1424-8220/22/18/6852crackpropagationsurface crackmachine visionNational InstrumentsVision Builder |
| spellingShingle | Jan Gebauer Pavel Šofer Martin Jurek Renata Wagnerová Jiří Czebe Machine Vision-Based Fatigue Crack Propagation System Sensors crack propagation surface crack machine vision National Instruments Vision Builder |
| title | Machine Vision-Based Fatigue Crack Propagation System |
| title_full | Machine Vision-Based Fatigue Crack Propagation System |
| title_fullStr | Machine Vision-Based Fatigue Crack Propagation System |
| title_full_unstemmed | Machine Vision-Based Fatigue Crack Propagation System |
| title_short | Machine Vision-Based Fatigue Crack Propagation System |
| title_sort | machine vision based fatigue crack propagation system |
| topic | crack propagation surface crack machine vision National Instruments Vision Builder |
| url | https://www.mdpi.com/1424-8220/22/18/6852 |
| work_keys_str_mv | AT jangebauer machinevisionbasedfatiguecrackpropagationsystem AT pavelsofer machinevisionbasedfatiguecrackpropagationsystem AT martinjurek machinevisionbasedfatiguecrackpropagationsystem AT renatawagnerova machinevisionbasedfatiguecrackpropagationsystem AT jiriczebe machinevisionbasedfatiguecrackpropagationsystem |