Back to Search
Start Over
Susceptibility of surface texture parameters to acquisition point clouds with digital data processing of data from optical measuring systems
- Source :
- MATEC Web of Conferences, Vol 252, p 03020 (2019)
- Publication Year :
- 2019
- Publisher :
- EDP Sciences, 2019.
-
Abstract
- Digital processing of the recorded point clouds on innovative surfaces could facilitate the operator’s planning of the metrological process and give more freedom in the assessment of the surface texture. The current state of knowledge about surface characteristics, precision and quality of measurements and especially the repeatability of measurements – not only in the laboratory environment but also in the industry pose a big challenge. The paper presents research works related to the identification of the impact of the method of acquisition point clouds using digital data processing on surface texture. The main assumption of the paper was to carry out, according to the prepared plan of the experiment, the series of sample measurements with the use of the optical measuring systems AltiSurf A520 in the Laboratory of Surface Topography at the West Pomeranian University of Technology in Szczecin. The next task was to determine the impact of the digital data processing strategy in order to identify the significance of the impact (conditions and methods of filtration), which in practice largely determines the repeatability and reproducibility of the parameter values of the geometry surface structure.
- Subjects :
- 0209 industrial biotechnology
020303 mechanical engineering & transports
020901 industrial engineering & automation
Materials science
0203 mechanical engineering
lcsh:TA1-2040
System of measurement
Point cloud
02 engineering and technology
Surface finish
lcsh:Engineering (General). Civil engineering (General)
Digital data processing
Remote sensing
Subjects
Details
- ISSN :
- 2261236X
- Volume :
- 252
- Database :
- OpenAIRE
- Journal :
- MATEC Web of Conferences
- Accession number :
- edsair.doi.dedup.....e37f24abfed350713f107d4e6235ea85
- Full Text :
- https://doi.org/10.1051/matecconf/201925203020