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Abstract(s)
Devido aos efeitos cada vez mais negativos dos combustíveis fósseis no meio ambiente,
foram propostas soluções para atingir os objetivos de descarbonização acordados na
COP26 sobre as alterações climáticas, nomeadamente a utilização de energias mais
limpas como a energia eólica. A instalação de turbinas em offshore têm vindo
a crescer devido à elevada capacidade de gerar energia com os ventos marítimos.
Contudo, a utilização de tecnologias que possibilitam a inspeção não presencial é
um dos fatores de maior procura.
Esta dissertação visa desenvolver uma solução de uma embarcação não tripulada,
denominado por Nautilus, um veículo modular, munido de sensores que permitam
a inspeção das fundações e peça de transição de turbinas eólicas em offshore. O
Nautilus foi testado e validado num centro de testes criado pelo projeto ATLANTIS
situado numa zona costeira e por fim num campo eólico com turbinas flutuantes
situado a 20 km da costa, em Viana do Castelo. Nos testes realizados foi validada a
capacidade de mobilização e recolha, modularidade dos equipamentos e capacidade
de operação em diferentes condições atmosféricas e de ondulação. O Nautilus mos trou ser uma solução com nível de maturidade elevado e tornou-se o primeiro veículo
não tripulado no mundo, a realizar recolha de dados e missão autónoma num campo
eólico em offshore com turbinas eólicas flutuantes.
No contexto de veículos autónomos, um dos fatores mais importantes é a sua
segurança estrutural. Para isso foi feito um estudo sobre algoritmos de desvio de
obstáculos. O algoritmo implementado passa pelo calculo das distâncias mínimas por
secções discretizadas em volta do veículo e a definição de uma metodologia de áreas
de risco possibilitam a tomada de decisão consoante a proximidade ao obstáculo,
sendo a paragem ou o desvio do obstáculo num trajeto livre de colisão. Para tal,
foram realizados diversos testes e validações em simulação, utilizando o Gazebo, que
tem a capacidade de representar a dinâmica marítima real. Os resultados obtidos
representam a capacidade de, com sucesso, o veículo se desviar dos obstáculos em
diversos cenários, tendo sido testado com um algoritmo de missão autónoma em
simultâneo.
Due to the increasingly negative effects of fossil fuels on the environment, solutions have been proposed to achieve the decarbonization goals agreed upon at COP26 on climate change, notably the use of cleaner energies such as wind energy. The installation of offshore wind turbines has been growing due to their high capacity to generate energy from maritime winds. However, the use of technologies that enable remote inspection is one of the most sought-after factors. This dissertation aims to present a solution of an unmanned vessel, referred to as Nautilus, a modular vehicle equipped with sensors that allow for the inspection of the foundations and transition pieces of offshore wind turbines. The Nautilus was tested and validated at a test centre created by the ATLANTIS project located in a coastal area and finally at an offshore wind farm with floating turbines located 20 km of the coast in Viana do Castelo. The tests conducted validated the deploy and retrieval capability, equipment modularity and operational capacity under different atmospheric and wave conditions. The Nautilus proved to be a solution with a high level of maturity and became the world’s first unmanned vehicle to perform data collection and autonomous mission in an offshore wind farm with floating wind turbines. In the context of autonomous vehicles, one of the most important factors is their structural safety. For this purpose, a study on obstacle avoidance algorithms was conducted. The implemented algorithm involves calculating minimum distances per section around the vehicle and defining risk areas that enable decision-making based on proximity to the obstacle, either stopping or deviating from the obstacle along a collision-free path. To achieve this, various tests and validations were conducted in simulation using Gazebo, which has the ability to represent real maritime dynamics. The results obtained demonstrate the vehicle’s successful ability to avoid obstacles in various scenarios, having been tested with a autonomous mission algorithm.
Due to the increasingly negative effects of fossil fuels on the environment, solutions have been proposed to achieve the decarbonization goals agreed upon at COP26 on climate change, notably the use of cleaner energies such as wind energy. The installation of offshore wind turbines has been growing due to their high capacity to generate energy from maritime winds. However, the use of technologies that enable remote inspection is one of the most sought-after factors. This dissertation aims to present a solution of an unmanned vessel, referred to as Nautilus, a modular vehicle equipped with sensors that allow for the inspection of the foundations and transition pieces of offshore wind turbines. The Nautilus was tested and validated at a test centre created by the ATLANTIS project located in a coastal area and finally at an offshore wind farm with floating turbines located 20 km of the coast in Viana do Castelo. The tests conducted validated the deploy and retrieval capability, equipment modularity and operational capacity under different atmospheric and wave conditions. The Nautilus proved to be a solution with a high level of maturity and became the world’s first unmanned vehicle to perform data collection and autonomous mission in an offshore wind farm with floating wind turbines. In the context of autonomous vehicles, one of the most important factors is their structural safety. For this purpose, a study on obstacle avoidance algorithms was conducted. The implemented algorithm involves calculating minimum distances per section around the vehicle and defining risk areas that enable decision-making based on proximity to the obstacle, either stopping or deviating from the obstacle along a collision-free path. To achieve this, various tests and validations were conducted in simulation using Gazebo, which has the ability to represent real maritime dynamics. The results obtained demonstrate the vehicle’s successful ability to avoid obstacles in various scenarios, having been tested with a autonomous mission algorithm.
Description
Keywords
Renewable energy inspection wind turbines offshore floating structure ASV perception sensors navigation sensors obstacle avoidance