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Improved approximation of spatial light distribution
The rapid worldwide evolution of LEDs as light sources has brought new challenges, which means that new methods are needed and new algorithms have to be developed. Since the majority of LED luminaries are of the multi-source type, established methods for the design of light engines cannot be used in...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5409530/ https://www.ncbi.nlm.nih.gov/pubmed/28453546 http://dx.doi.org/10.1371/journal.pone.0176252 |
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author | Kaljun, David Novak, Tina Žerovnik, Janez |
author_facet | Kaljun, David Novak, Tina Žerovnik, Janez |
author_sort | Kaljun, David |
collection | PubMed |
description | The rapid worldwide evolution of LEDs as light sources has brought new challenges, which means that new methods are needed and new algorithms have to be developed. Since the majority of LED luminaries are of the multi-source type, established methods for the design of light engines cannot be used in the design of LED light engines. This is because in the latter case what is involved is not just the design of a good reflector or projector lens, but the design of several lenses which have to work together in order to achieve satisfactory results. Since lenses can also be bought off the shelf from several manufacturers, it should be possible to combine together different off the shelf lenses in order to design a good light engine. However, with so many different lenses to choose from, it is almost impossible to find an optimal combination by hand, which means that some optimization algorithms need to be applied. In order for them to work properly, it is first necessary to describe the input data (i.e. spatial light distribution) in a functional form using as few as possible parameters. In this paper the focus is on the approximation of the input data, and the implementation of the well-known mathematical procedure for the separation of linear and nonlinear parameters, which can provide a substantial increase in performance. |
format | Online Article Text |
id | pubmed-5409530 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-54095302017-05-12 Improved approximation of spatial light distribution Kaljun, David Novak, Tina Žerovnik, Janez PLoS One Research Article The rapid worldwide evolution of LEDs as light sources has brought new challenges, which means that new methods are needed and new algorithms have to be developed. Since the majority of LED luminaries are of the multi-source type, established methods for the design of light engines cannot be used in the design of LED light engines. This is because in the latter case what is involved is not just the design of a good reflector or projector lens, but the design of several lenses which have to work together in order to achieve satisfactory results. Since lenses can also be bought off the shelf from several manufacturers, it should be possible to combine together different off the shelf lenses in order to design a good light engine. However, with so many different lenses to choose from, it is almost impossible to find an optimal combination by hand, which means that some optimization algorithms need to be applied. In order for them to work properly, it is first necessary to describe the input data (i.e. spatial light distribution) in a functional form using as few as possible parameters. In this paper the focus is on the approximation of the input data, and the implementation of the well-known mathematical procedure for the separation of linear and nonlinear parameters, which can provide a substantial increase in performance. Public Library of Science 2017-04-28 /pmc/articles/PMC5409530/ /pubmed/28453546 http://dx.doi.org/10.1371/journal.pone.0176252 Text en © 2017 Kaljun et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Kaljun, David Novak, Tina Žerovnik, Janez Improved approximation of spatial light distribution |
title | Improved approximation of spatial light distribution |
title_full | Improved approximation of spatial light distribution |
title_fullStr | Improved approximation of spatial light distribution |
title_full_unstemmed | Improved approximation of spatial light distribution |
title_short | Improved approximation of spatial light distribution |
title_sort | improved approximation of spatial light distribution |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5409530/ https://www.ncbi.nlm.nih.gov/pubmed/28453546 http://dx.doi.org/10.1371/journal.pone.0176252 |
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