Trajectory control and modelling for wind turbine maintenance by using a RPAS
One of the most demanded assets nowadays is energy. Over many options to generate it, humankind must seek sustainable ways; therefore, renewable energies must be empowered. Moreover, wind provides great benefits, granting uncalculated power at our disposition. Since this task is executed by big structures, their maintenance represents a difficult task for human efforts to achieve, because the height requires much support, effort and time to accomplish.
A Remotely Piloted Aircraft System (RPAS) can be adapted to perform surveillance on different types of surfaces, presenting a comfortable way to execute it in dangerous and difficult to access spaces, providing safer methods, and bringing experience of qualified workers and technology together.
This paper will provide methods for generating a trajectory over Wind Turbine blades, relying on the specification of a Phantom 4. The main objective is to establish a path over this structure, based on the measurements of a specific model and incorporating all of the blades surface. The results were satisfying once the precision was inside the allowed deviation. Nevertheless, some issues might be improved such as the velocity between waypoints and the polynomial selected to define the trajectory.
This work is licensed under a Creative Commons Attribution 4.0 International License.
DJI. (2016). Phantom 4 Specs. Retrieved from https://www.dji.com/phantom-4/info
Esu, O. (2016). Feasibility of a fully autonomous wireless monitoring system for a wind turbine blade. Renewable Energy, 97, 89-96. https://doi.org/10.1016/j.renene.2016.05.021
Fried, L. (2017). Global Wind Energy Council. Retrieved from http://www.gwec.net/wp-content/uploads/vip/GWEC_PRstats2016_EN_WEB.pdf
Gupte, S. (2012). A survey of Quadrotor unmanned aerial vehicles. Proceedings of IEEE (pp. 1-6). Orlando: Southeastcon. https://doi.org/10.1109/SECon.2012.6196930
Hehn, M. (2011). Quadrocopter trajectory generation and control. IFAC World Congress, 1485-1491. https://doi.org/10.3182/20110828-6-IT-1002.03178
IRENA. (2012). Wind power. Renewable Energy Technologies: Cost Analysis Series, 1(5), 4-34.
Kovacs, M. (2016). Research on the potentiality of using aerial vehicles for monitoring the environment agent - air. Environmental Legislation, Safety Engineering and Disaster Management. Cluj-Napoca.
Kumar, V. (2016). Robotics: aerial robotics – lecture notes. Retrieved from https://www.coursera.org/learn/robotics-flight
Mellinger, D. W. (2012). Trajectory generation and control for quadrotors. Pennsylvania: University of Pennsylvania.
Morgenthal, G., & Hallermann, N. (2016). Quality assessment of unmanned aerial vehicle (UAV) based visual inspection of structures. Advances in Structural Engineering, 17(3), 289-302. https://doi.org/10.1260/1369-43184.108.40.2069
Motion, S. I. (2017). Operations and Maintenance Services. Retrieved from https://d3icht40s6fxmd.cloudfront.net/sites/default/files/inspeccion-aerea-profunda-de-palas-informes-y-mapeos-de-alta-resolucion-en-espectro-termico-y-spares_danos_en_punta.jpg
Nurm, M. (2017). Wind turbine operation and maintenance services. Retrieved from ttp://skyproff.com/wind-turbine-operation-and-maintenance-services/
Rosenbloom, E. (2014). Size specifications of common industrial wind turbines . Retrieved from http://www.aweo.org/windmodels.html
Saavedra, R. C. (2015). Noise and vibration issues of wind turbines and their impact – a review. Wind Engineering, 39(6), 693-702. https://doi.org/10.1260/0309-524X.39.6.693
Staffell, I. (2014). How does wind farm performance decline with age? Renewable Energy, 66, 775-786. https://doi.org/10.1016/j.renene.2013.10.041
Ziegler, J. G. (1942). Optimum settings for automatic controllers. ASME, 64, 759-768.