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Piezoelectric Energy Harvester Response Statistics
Safety and reliability are essential engineering concerns for energy-harvesting installations. In the case of the piezoelectric galloping energy harvester, there is a risk that excessive wake galloping may lead to instability, overload, and thus damage. With this in mind, this paper studies bivariat...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9963450/ https://www.ncbi.nlm.nih.gov/pubmed/36837974 http://dx.doi.org/10.3390/mi14020271 |
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author | Gaidai, Oleg Cao, Yu Xing, Yihan Wang, Junlei |
author_facet | Gaidai, Oleg Cao, Yu Xing, Yihan Wang, Junlei |
author_sort | Gaidai, Oleg |
collection | PubMed |
description | Safety and reliability are essential engineering concerns for energy-harvesting installations. In the case of the piezoelectric galloping energy harvester, there is a risk that excessive wake galloping may lead to instability, overload, and thus damage. With this in mind, this paper studies bivariate statistics of the extreme, experimental galloping energy harvester dynamic response under realistic environmental conditions. The bivariate statistics were extracted from experimental wind tunnel results, specifically for the voltage-force data set. Authors advocate a novel general-purpose reliability approach that may be applied to a wide range of dynamic systems, including micro-machines. Both experimental and numerically simulated dynamic responses can be used as input for the suggested structural reliability analysis. The statistical analysis proposed in this study may be used at the design stage, supplying proper characteristic values and safeguarding the dynamic system from overload, thus extending the machine’s lifetime. This work introduces a novel bivariate technique for reliability analysis instead of the more general univariate design approaches. |
format | Online Article Text |
id | pubmed-9963450 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-99634502023-02-26 Piezoelectric Energy Harvester Response Statistics Gaidai, Oleg Cao, Yu Xing, Yihan Wang, Junlei Micromachines (Basel) Article Safety and reliability are essential engineering concerns for energy-harvesting installations. In the case of the piezoelectric galloping energy harvester, there is a risk that excessive wake galloping may lead to instability, overload, and thus damage. With this in mind, this paper studies bivariate statistics of the extreme, experimental galloping energy harvester dynamic response under realistic environmental conditions. The bivariate statistics were extracted from experimental wind tunnel results, specifically for the voltage-force data set. Authors advocate a novel general-purpose reliability approach that may be applied to a wide range of dynamic systems, including micro-machines. Both experimental and numerically simulated dynamic responses can be used as input for the suggested structural reliability analysis. The statistical analysis proposed in this study may be used at the design stage, supplying proper characteristic values and safeguarding the dynamic system from overload, thus extending the machine’s lifetime. This work introduces a novel bivariate technique for reliability analysis instead of the more general univariate design approaches. MDPI 2023-01-20 /pmc/articles/PMC9963450/ /pubmed/36837974 http://dx.doi.org/10.3390/mi14020271 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Gaidai, Oleg Cao, Yu Xing, Yihan Wang, Junlei Piezoelectric Energy Harvester Response Statistics |
title | Piezoelectric Energy Harvester Response Statistics |
title_full | Piezoelectric Energy Harvester Response Statistics |
title_fullStr | Piezoelectric Energy Harvester Response Statistics |
title_full_unstemmed | Piezoelectric Energy Harvester Response Statistics |
title_short | Piezoelectric Energy Harvester Response Statistics |
title_sort | piezoelectric energy harvester response statistics |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9963450/ https://www.ncbi.nlm.nih.gov/pubmed/36837974 http://dx.doi.org/10.3390/mi14020271 |
work_keys_str_mv | AT gaidaioleg piezoelectricenergyharvesterresponsestatistics AT caoyu piezoelectricenergyharvesterresponsestatistics AT xingyihan piezoelectricenergyharvesterresponsestatistics AT wangjunlei piezoelectricenergyharvesterresponsestatistics |