Figure 6 - uploaded by Josef Schleupen
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displays the height of the four circular distributed track drives during two test drives. The time depending heights reflect the motion of the main body. The left figure shows a normal lifting procedere with the current state of the demonstrator. On the right the motion behavior is displayed for a 140 kg weight dummy attached to the extension arm.
Source publication
The rapid development in the wind energy market is exhausting the capability for upcoming maintenance needs. [1] While the reliability of mechanical parts, e.g. main bearing, generator, gears and main shaft evolved, rotor blade maintenance and improvement turn more and more into focus [2]. Since September 2014 University of Applied Sciences Aachen...
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Citations
... Digital twins can be derived from sensor data to enable predictive maintenance and long-term condition monitoring. The first step towards this goal is to develop several prototypes to validate the basics [4][5][6][7]. Flying and surface climbing systems are collaborating with the goal of large-scale inspection in wind farms and on-demand local repairs ( Figure 1). A friction-based climbing ring robot (SMART: Scanning, Monitoring, Analyzing, Repair and Transportation) can carry high payloads and is equipped with an onboard robotic arm. ...
... The final concept was finally validated with a 1:3 demonstrator before the large-scale prototype was designed and tested on a conical-shaped tower for the first time. Within the project, two systems at 1:3 scale were developed and intensively tested [5]. The crawler concept and materials were quite similar. ...
... A cable connects the robot's power supply units to the main supply. Within the project, two systems at 1:3 scale were developed and intensively tested [5]. The crawler concept and materials were quite similar. ...
The maintenance of wind turbines is of growing importance considering the transition to renewable energy. This paper presents a multi-robot-approach for automated wind turbine maintenance including a novel climbing robot. Currently, wind turbine maintenance remains a manual task, which is monotonous, dangerous, and also physically demanding due to the large scale of wind turbines. Technical climbers are required to work at significant heights, even in bad weather conditions. Furthermore, a skilled labor force with sufficient knowledge in repairing fiber composite material is rare. Autonomous mobile systems enable the digitization of the maintenance process. They can be designed for weather-independent operations. This work contributes to the development and experimental validation of a maintenance system consisting of multiple robotic platforms for a variety of tasks, such as wind turbine tower and rotor blade service. In this work, multicopters with vision and LiDAR sensors for global inspection are used to guide slower climbing robots. Light-weight magnetic climbers with surface contact were used to analyze structure parts with non-destructive inspection methods and to locally repair smaller defects. Localization was enabled by adapting odometry for conical-shaped surfaces considering additional navigation sensors. Magnets were suitable for steel towers to clamp onto the surface. A friction-based climbing ring robot (SMART— Scanning, Monitoring, Analyzing, Repair and Transportation) completed the set-up for higher payload. The maintenance period could be extended by using weather-proofed maintenance robots. The multi-robot-system was running the Robot Operating System (ROS). Additionally, first steps towards machine learning would enable maintenance staff to use pattern classification for fault diagnosis in order to operate safely from the ground in the future.
