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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Main Authors: Binrui Wang, Haohua Luo, Yinglian Jin, Mewei He
Format: Article
Language:English
Published: SAGE Publishing 2013-01-01
Series:Advances in Mechanical Engineering
Online Access:https://doi.org/10.1155/2013/760126
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spelling 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 AT binruiwang pathplanningfordetectionrobotclimbingonrotorbladesurfacesofwindturbinebasedonneuralnetwork
AT haohualuo pathplanningfordetectionrobotclimbingonrotorbladesurfacesofwindturbinebasedonneuralnetwork
AT yinglianjin pathplanningfordetectionrobotclimbingonrotorbladesurfacesofwindturbinebasedonneuralnetwork
AT meweihe pathplanningfordetectionrobotclimbingonrotorbladesurfacesofwindturbinebasedonneuralnetwork
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