Path Planning for Detection Robot Climbing on Rotor Blade Surfaces of Wind Turbine Based on Neural Network
Two-feet climbing robot is proposed for rotor blade surface damage detection. The penalty function is designed based on the simulated annealing neural network for waypoints inside blade. According to the derivative of path energy function to time, waypoints are updated and move toward the direction...
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2013-01-01
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Series: | Advances in Mechanical Engineering |
Online Access: | https://doi.org/10.1155/2013/760126 |
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doaj-8d742a660a6f488e8dd1c2fff2a5e6942020-11-25T01:27:14ZengSAGE PublishingAdvances in Mechanical Engineering1687-81322013-01-01510.1155/2013/76012610.1155_2013/760126Path Planning for Detection Robot Climbing on Rotor Blade Surfaces of Wind Turbine Based on Neural NetworkBinrui Wang0Haohua Luo1Yinglian Jin2Mewei He3 College of Engineering, University of Tennessee, Knoxville, TN 37996, USA College of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou 310018, China College of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou 310018, China College of Mechanical and Electrical Engineering, China Jiliang University, Hangzhou 310018, ChinaTwo-feet climbing robot is proposed for rotor blade surface damage detection. The penalty function is designed based on the simulated annealing neural network for waypoints inside blade. According to the derivative of path energy function to time, waypoints are updated and move toward the direction reducing the path energy consisting of length and penalty function. According to the curvature variation range, a novel weighted simulated-annealing-temperature updating method is designed to get comprehensive optimization of the path energy and convergence speed. The path planning is accomplished for the root, middle, and tip blade parts, respectively. The asymptotic analysis of the waypoint coordinating updating process was given, and the updated start point is adopted during escaping from inside. The effect of weight on path energy and convergence speed is analyzed. The planning results show the effectiveness of the proposed path planning algorithm, and the weighted average method is valid for the comprehensive optimization.https://doi.org/10.1155/2013/760126 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Binrui Wang Haohua Luo Yinglian Jin Mewei He |
spellingShingle |
Binrui Wang Haohua Luo Yinglian Jin Mewei He Path Planning for Detection Robot Climbing on Rotor Blade Surfaces of Wind Turbine Based on Neural Network Advances in Mechanical Engineering |
author_facet |
Binrui Wang Haohua Luo Yinglian Jin Mewei He |
author_sort |
Binrui Wang |
title |
Path Planning for Detection Robot Climbing on Rotor Blade Surfaces of Wind Turbine Based on Neural Network |
title_short |
Path Planning for Detection Robot Climbing on Rotor Blade Surfaces of Wind Turbine Based on Neural Network |
title_full |
Path Planning for Detection Robot Climbing on Rotor Blade Surfaces of Wind Turbine Based on Neural Network |
title_fullStr |
Path Planning for Detection Robot Climbing on Rotor Blade Surfaces of Wind Turbine Based on Neural Network |
title_full_unstemmed |
Path Planning for Detection Robot Climbing on Rotor Blade Surfaces of Wind Turbine Based on Neural Network |
title_sort |
path planning for detection robot climbing on rotor blade surfaces of wind turbine based on neural network |
publisher |
SAGE Publishing |
series |
Advances in Mechanical Engineering |
issn |
1687-8132 |
publishDate |
2013-01-01 |
description |
Two-feet climbing robot is proposed for rotor blade surface damage detection. The penalty function is designed based on the simulated annealing neural network for waypoints inside blade. According to the derivative of path energy function to time, waypoints are updated and move toward the direction reducing the path energy consisting of length and penalty function. According to the curvature variation range, a novel weighted simulated-annealing-temperature updating method is designed to get comprehensive optimization of the path energy and convergence speed. The path planning is accomplished for the root, middle, and tip blade parts, respectively. The asymptotic analysis of the waypoint coordinating updating process was given, and the updated start point is adopted during escaping from inside. The effect of weight on path energy and convergence speed is analyzed. The planning results show the effectiveness of the proposed path planning algorithm, and the weighted average method is valid for the comprehensive optimization. |
url |
https://doi.org/10.1155/2013/760126 |
work_keys_str_mv |
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