• Corpus ID: 239024391

Data-driven and Automatic Surface Texture Analysis Using Persistent Homology

@article{Yesilli2021DatadrivenAA,
  title={Data-driven and Automatic Surface Texture Analysis Using Persistent Homology},
  author={Melih C. Yesilli and Firas A. Khasawneh},
  journal={ArXiv},
  year={2021},
  volume={abs/2110.10005}
}
Surface roughness plays an important role in analyzing engineering surfaces. It quantifies the surface topography and can be used to determine whether the resulting surface finish is acceptable or not. Nevertheless, while several existing tools and standards are available for computing surface roughness, these methods rely heavily on user input thus slowing down the analysis and increasing manufacturing costs. Therefore, fast and automatic determination of the roughness level is essential to… 

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