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Solar panel surface dirt detection and removal based on arduino color recognition
Color sensing is a technique for identifying physical changes in materials based on appearance assessment. Dirt deposition on solar panels can change their physical appearance and performance. Considering that dirt accumulation on solar panels needs monitoring to make efficient cleaning schedules, r...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9803813/ https://www.ncbi.nlm.nih.gov/pubmed/36593762 http://dx.doi.org/10.1016/j.mex.2022.101967 |
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author | Olorunfemi, Benjamin O. Nwulu, Nnamdi I. Ogbolumani, Omolola A. |
author_facet | Olorunfemi, Benjamin O. Nwulu, Nnamdi I. Ogbolumani, Omolola A. |
author_sort | Olorunfemi, Benjamin O. |
collection | PubMed |
description | Color sensing is a technique for identifying physical changes in materials based on appearance assessment. Dirt deposition on solar panels can change their physical appearance and performance. Considering that dirt accumulation on solar panels needs monitoring to make efficient cleaning schedules, reduce unnecessary costs, and optimize solar panel output generation. Color sensing can achieve fast, accurate, and economical dirt detection, unlike the use of robotic cameras, mathematical formulae, and considering varying output current and voltage methods. Here, we introduce a method that detects and removes dirt on solar panels based on TCS3200 and Arduino Uno components. The approach targets (i.) Panel color measurement, calibration, threshold selection process, (ii.) comparison of color measurement values, and (iii.) align further calibration in response to discoloration of solar panels. This method aims to correct the dirt detection methods previously in use. Hence, a high-speed rolling brush arrangement is designed to improve the cleaning of the solar panel without using water. Further investigations of the panel's color may require some improvement in terms of increasing the sensitivity of the color sensor even with increased distance from the solar panel. Combining multiple color sensors may also be necessary. |
format | Online Article Text |
id | pubmed-9803813 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-98038132023-01-01 Solar panel surface dirt detection and removal based on arduino color recognition Olorunfemi, Benjamin O. Nwulu, Nnamdi I. Ogbolumani, Omolola A. MethodsX Method Article Color sensing is a technique for identifying physical changes in materials based on appearance assessment. Dirt deposition on solar panels can change their physical appearance and performance. Considering that dirt accumulation on solar panels needs monitoring to make efficient cleaning schedules, reduce unnecessary costs, and optimize solar panel output generation. Color sensing can achieve fast, accurate, and economical dirt detection, unlike the use of robotic cameras, mathematical formulae, and considering varying output current and voltage methods. Here, we introduce a method that detects and removes dirt on solar panels based on TCS3200 and Arduino Uno components. The approach targets (i.) Panel color measurement, calibration, threshold selection process, (ii.) comparison of color measurement values, and (iii.) align further calibration in response to discoloration of solar panels. This method aims to correct the dirt detection methods previously in use. Hence, a high-speed rolling brush arrangement is designed to improve the cleaning of the solar panel without using water. Further investigations of the panel's color may require some improvement in terms of increasing the sensitivity of the color sensor even with increased distance from the solar panel. Combining multiple color sensors may also be necessary. Elsevier 2022-12-13 /pmc/articles/PMC9803813/ /pubmed/36593762 http://dx.doi.org/10.1016/j.mex.2022.101967 Text en © 2022 Published by Elsevier B.V. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Method Article Olorunfemi, Benjamin O. Nwulu, Nnamdi I. Ogbolumani, Omolola A. Solar panel surface dirt detection and removal based on arduino color recognition |
title | Solar panel surface dirt detection and removal based on arduino color recognition |
title_full | Solar panel surface dirt detection and removal based on arduino color recognition |
title_fullStr | Solar panel surface dirt detection and removal based on arduino color recognition |
title_full_unstemmed | Solar panel surface dirt detection and removal based on arduino color recognition |
title_short | Solar panel surface dirt detection and removal based on arduino color recognition |
title_sort | solar panel surface dirt detection and removal based on arduino color recognition |
topic | Method Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9803813/ https://www.ncbi.nlm.nih.gov/pubmed/36593762 http://dx.doi.org/10.1016/j.mex.2022.101967 |
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