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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.
Manufacturing Process Simulation for the Prediction of Tool-Part-Interaction and Ply Wrinkling
(2015)
Manufacturing Process Simulation for the Prediction of Tool-Part-Interaction and Ply Wrinkling
(2019)
Manufacturing process simulation enables the evaluation and improvement of autoclave mold concepts early in the design phase. To achieve a high part quality at low cycle times, the thermal behavior of the autoclave mold can be investigated by means of simulations. Most challenging for such a simulation is the generation of necessary boundary conditions. Heat-up and temperature distribution in an autoclave mold are governed by flow phenomena, tooling material and shape, position within the autoclave, and the chosen autoclave cycle. This paper identifies and summarizes the most important factors influencing mold heat-up and how they can be introduced into a thermal simulation. Thermal measurements are used to quantify the impact of the various parameters. Finally, the gained knowledge is applied to develop a semi-empirical approach for boundary condition estimation that enables a simple and fast thermal simulation of the autoclave curing process with reasonably high accuracy for tooling optimization.