Cargando…

Sensor Distribution Optimization for Structural Impact Monitoring Based on NSGA-II and Wavelet Decomposition

Optimal sensor placement is a significant task for structural health monitoring (SHM). In this paper, an SHM system is designed which can recognize the different impact location and impact degree in the composite plate. Firstly, the finite element method is used to simulate the impact, extracting nu...

Descripción completa

Detalles Bibliográficos
Autores principales: Li, Peng, Huang, Liuwei, Peng, Jiachao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308493/
https://www.ncbi.nlm.nih.gov/pubmed/30518094
http://dx.doi.org/10.3390/s18124264
_version_ 1783383201775878144
author Li, Peng
Huang, Liuwei
Peng, Jiachao
author_facet Li, Peng
Huang, Liuwei
Peng, Jiachao
author_sort Li, Peng
collection PubMed
description Optimal sensor placement is a significant task for structural health monitoring (SHM). In this paper, an SHM system is designed which can recognize the different impact location and impact degree in the composite plate. Firstly, the finite element method is used to simulate the impact, extracting numerical signals of the structure, and the wavelet decomposition is used to extract the band energy. Meanwhile, principal component analysis (PCA) is used to reduce the dimensions of the vibration signal. Following this, the non-dominated sorting genetic algorithm (NSGA-II) is used to optimize the placement of sensors. Finally, the experimental system is established, and the Product-based Neural Network is used to recognize different impact categories. Three sets of experiments are carried out to verify the optimal results. When three sensors are applied, the average accuracy of the impact recognition is 59.14%; when the number of sensors is four, the average accuracy of impact recognition is 76.95%.
format Online
Article
Text
id pubmed-6308493
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-63084932019-01-04 Sensor Distribution Optimization for Structural Impact Monitoring Based on NSGA-II and Wavelet Decomposition Li, Peng Huang, Liuwei Peng, Jiachao Sensors (Basel) Article Optimal sensor placement is a significant task for structural health monitoring (SHM). In this paper, an SHM system is designed which can recognize the different impact location and impact degree in the composite plate. Firstly, the finite element method is used to simulate the impact, extracting numerical signals of the structure, and the wavelet decomposition is used to extract the band energy. Meanwhile, principal component analysis (PCA) is used to reduce the dimensions of the vibration signal. Following this, the non-dominated sorting genetic algorithm (NSGA-II) is used to optimize the placement of sensors. Finally, the experimental system is established, and the Product-based Neural Network is used to recognize different impact categories. Three sets of experiments are carried out to verify the optimal results. When three sensors are applied, the average accuracy of the impact recognition is 59.14%; when the number of sensors is four, the average accuracy of impact recognition is 76.95%. MDPI 2018-12-04 /pmc/articles/PMC6308493/ /pubmed/30518094 http://dx.doi.org/10.3390/s18124264 Text en © 2018 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Li, Peng
Huang, Liuwei
Peng, Jiachao
Sensor Distribution Optimization for Structural Impact Monitoring Based on NSGA-II and Wavelet Decomposition
title Sensor Distribution Optimization for Structural Impact Monitoring Based on NSGA-II and Wavelet Decomposition
title_full Sensor Distribution Optimization for Structural Impact Monitoring Based on NSGA-II and Wavelet Decomposition
title_fullStr Sensor Distribution Optimization for Structural Impact Monitoring Based on NSGA-II and Wavelet Decomposition
title_full_unstemmed Sensor Distribution Optimization for Structural Impact Monitoring Based on NSGA-II and Wavelet Decomposition
title_short Sensor Distribution Optimization for Structural Impact Monitoring Based on NSGA-II and Wavelet Decomposition
title_sort sensor distribution optimization for structural impact monitoring based on nsga-ii and wavelet decomposition
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308493/
https://www.ncbi.nlm.nih.gov/pubmed/30518094
http://dx.doi.org/10.3390/s18124264
work_keys_str_mv AT lipeng sensordistributionoptimizationforstructuralimpactmonitoringbasedonnsgaiiandwaveletdecomposition
AT huangliuwei sensordistributionoptimizationforstructuralimpactmonitoringbasedonnsgaiiandwaveletdecomposition
AT pengjiachao sensordistributionoptimizationforstructuralimpactmonitoringbasedonnsgaiiandwaveletdecomposition