Optimal Layout of Sensors on Wind Turbine Blade Based on Combinational Algorithm
This work proposes a comprehensive combinational algorithm for sensor layout to solve the problem that unreasonable sensor layout affects the effectiveness of data selection and reduces the accuracy of monitoring system in healthy monitoring system of wind turbine blade structure. This algorithm int...
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2016-02-01
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Series: | International Journal of Distributed Sensor Networks |
Online Access: | https://doi.org/10.1155/2016/5782026 |
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doaj-b891e4be02124ed29f9b4d46bca6cac32020-11-25T03:43:39ZengSAGE PublishingInternational Journal of Distributed Sensor Networks1550-14772016-02-011210.1155/2016/57820265782026Optimal Layout of Sensors on Wind Turbine Blade Based on Combinational AlgorithmGuimei GuYu ZhaoXin ZhangThis work proposes a comprehensive combinational algorithm for sensor layout to solve the problem that unreasonable sensor layout affects the effectiveness of data selection and reduces the accuracy of monitoring system in healthy monitoring system of wind turbine blade structure. This algorithm integrates the advantages of kinetic energy method, effective independence method, modal assurance criterion (MAC), and many other optimal methods. In order to avoid information redundancy caused by partial concentration of test spots, Euclidean distance was introduced as the iteration condition of algorithm. Finite element simulation and experimental results show that the layout obtained by this method is beneficial to improving signal-to-noise ratio and can maximize the crossing angle between target vibration modes. Therefore, relatively complete characteristics of actual wind turbine blade structure can be obtained.https://doi.org/10.1155/2016/5782026 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Guimei Gu Yu Zhao Xin Zhang |
spellingShingle |
Guimei Gu Yu Zhao Xin Zhang Optimal Layout of Sensors on Wind Turbine Blade Based on Combinational Algorithm International Journal of Distributed Sensor Networks |
author_facet |
Guimei Gu Yu Zhao Xin Zhang |
author_sort |
Guimei Gu |
title |
Optimal Layout of Sensors on Wind Turbine Blade Based on Combinational Algorithm |
title_short |
Optimal Layout of Sensors on Wind Turbine Blade Based on Combinational Algorithm |
title_full |
Optimal Layout of Sensors on Wind Turbine Blade Based on Combinational Algorithm |
title_fullStr |
Optimal Layout of Sensors on Wind Turbine Blade Based on Combinational Algorithm |
title_full_unstemmed |
Optimal Layout of Sensors on Wind Turbine Blade Based on Combinational Algorithm |
title_sort |
optimal layout of sensors on wind turbine blade based on combinational algorithm |
publisher |
SAGE Publishing |
series |
International Journal of Distributed Sensor Networks |
issn |
1550-1477 |
publishDate |
2016-02-01 |
description |
This work proposes a comprehensive combinational algorithm for sensor layout to solve the problem that unreasonable sensor layout affects the effectiveness of data selection and reduces the accuracy of monitoring system in healthy monitoring system of wind turbine blade structure. This algorithm integrates the advantages of kinetic energy method, effective independence method, modal assurance criterion (MAC), and many other optimal methods. In order to avoid information redundancy caused by partial concentration of test spots, Euclidean distance was introduced as the iteration condition of algorithm. Finite element simulation and experimental results show that the layout obtained by this method is beneficial to improving signal-to-noise ratio and can maximize the crossing angle between target vibration modes. Therefore, relatively complete characteristics of actual wind turbine blade structure can be obtained. |
url |
https://doi.org/10.1155/2016/5782026 |
work_keys_str_mv |
AT guimeigu optimallayoutofsensorsonwindturbinebladebasedoncombinationalalgorithm AT yuzhao optimallayoutofsensorsonwindturbinebladebasedoncombinationalalgorithm AT xinzhang optimallayoutofsensorsonwindturbinebladebasedoncombinationalalgorithm |
_version_ |
1724518441014001664 |