Complexity Modeling of Steel-Laser-Hardened Surface Microstructures
Created by W.Langdon from
gp-bibliography.bib Revision:1.8010
- @Article{babic:2022:AS,
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author = "Matej Babic and Dragan Marinkovic and
Marco Bonfanti and Michele Cali",
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title = "Complexity Modeling of {Steel-Laser-Hardened} Surface
Microstructures",
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journal = "Applied Sciences",
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year = "2022",
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volume = "12",
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number = "5",
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keywords = "genetic algorithms, genetic programming",
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ISSN = "2076-3417",
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URL = "https://www.mdpi.com/2076-3417/12/5/2458",
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DOI = "doi:10.3390/app12052458",
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abstract = "Nowadays, laser hardening is a consolidated process in
many industrial sectors. One of the most interesting
aspects to be considered when treating the
surface-hardening process in steel materials by means
of laser devices is undoubtedly the evaluation of the
heat treatment quality and surface finish. In the
present study, an innovative method based on fractal
geometry was proposed to evaluate the quality of
surface-steel-laser-hardened treatment. A suitable
genetic programming study of SEM images (1280 ×
950 pixels) was developed in order to predict the
effect of the main laser process parameters on the
microstructural geometry, assuming the microstructure
of laser-hardened steel to be of a structurally complex
geometrical nature. Specimens hardened by
anthropomorphic laser robots were studied to determine
an accurate measure of the process parameters
investigated (surface temperature, laser beam velocity,
laser beam impact angle). In the range of variation
studied for these parameters, the genetic programming
model obtained was in line with the complexity index
calculated following the fractal theory. In particular,
a percentage error less than 1percent was calculated.
Finally, a preliminary study of the surface roughness
was carried out, resulting in its strong correlation
with complex surface microstructures. Three-dimensional
voxel maps that reproduce the surface roughness were
developed by automating a routine in Python virtual
environment.",
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notes = "also known as \cite{app12052458}",
- }
Genetic Programming entries for
Matej Babic
Dragan Marinkovic
Marco Bonfanti
Michele Cali
Citations