Hyperspectral and thermal temperature estimation during laser cladding Article Swipe
Margot Lison
,
Wim Devesse
,
Dieter De Baere
,
Michaël Hinderdael
,
Patrick Guillaume
·
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.2351/7.0004049
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.2351/7.0004049
Although there is no doubt about the tremendous industrial potential of metal additive manufacturing techniques such as laser metal deposition, the technology still has some intrinsic quality challenges to overcome before reaching its industrial maturity. Noncontact in-situ monitoring of the temperature evolution of the workpiece could provide the necessary information to implement an automated closed loop process control system and optimize the manufacturing process, providing a robust solution to these issues. However, measuring absolute temperatures is not self- evident: wavelength-dependent emissivity values vary between solid, liquid and mushy metallic regions, requiring spectral information and dedicated post- processing to relate the amount of emitted infrared radiation to the material temperature. This paper compares the temperature estimation results obtained from a VNIR hyperspectral line camera and a conventional SWIR thermal camera during the laser melting and cladding of a 316L steel sample. Both methods show agreeing results for the temperature distribution inside the melt pool, with the SWIR camera extending the temperature measurements beyond the melt pool boundaries into the solid region.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.2351/7.0004049
- OA Status
- gold
- References
- 9
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- OpenAlex ID
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https://openalex.org/W3139633123Canonical identifier for this work in OpenAlex
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https://doi.org/10.2351/7.0004049Digital Object Identifier
- Title
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Hyperspectral and thermal temperature estimation during laser claddingWork title
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articleOpenAlex work type
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enPrimary language
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2018Year of publication
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2018-10-01Full publication date if available
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Margot Lison, Wim Devesse, Dieter De Baere, Michaël Hinderdael, Patrick GuillaumeList of authors in order
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https://doi.org/10.2351/7.0004049Publisher landing page
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://doi.org/10.2351/7.0004049Direct OA link when available
- Concepts
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Hyperspectral imaging, Laser, Materials science, Thermal, Cladding (metalworking), Optics, Optoelectronics, Remote sensing, Environmental science, Computer science, Geology, Physics, Composite material, MeteorologyTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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| abstract_inverted_index.relate | 98 |
| abstract_inverted_index.robust | 66 |
| abstract_inverted_index.solid, | 84 |
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| abstract_inverted_index.melting | 132 |
| abstract_inverted_index.methods | 141 |
| abstract_inverted_index.process | 56 |
| abstract_inverted_index.provide | 46 |
| abstract_inverted_index.quality | 26 |
| abstract_inverted_index.region. | 169 |
| abstract_inverted_index.results | 115, 144 |
| abstract_inverted_index.sample. | 139 |
| abstract_inverted_index.thermal | 127 |
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| abstract_inverted_index.absolute | 73 |
| abstract_inverted_index.additive | 12 |
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| abstract_inverted_index.cladding | 134 |
| abstract_inverted_index.compares | 111 |
| abstract_inverted_index.evident: | 78 |
| abstract_inverted_index.infrared | 103 |
| abstract_inverted_index.material | 107 |
| abstract_inverted_index.metallic | 88 |
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| abstract_inverted_index.regions, | 89 |
| abstract_inverted_index.solution | 67 |
| abstract_inverted_index.spectral | 91 |
| abstract_inverted_index.automated | 53 |
| abstract_inverted_index.dedicated | 94 |
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| abstract_inverted_index.extending | 157 |
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| abstract_inverted_index.radiation | 104 |
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| abstract_inverted_index.temperatures | 74 |
| abstract_inverted_index.hyperspectral | 120 |
| abstract_inverted_index.manufacturing | 13, 62 |
| abstract_inverted_index.wavelength-dependent | 79 |
| cited_by_percentile_year | |
| countries_distinct_count | 1 |
| institutions_distinct_count | 5 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/9 |
| sustainable_development_goals[0].score | 0.46000000834465027 |
| sustainable_development_goals[0].display_name | Industry, innovation and infrastructure |
| citation_normalized_percentile.value | 0.31548614 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |