Damage mechanics and condition monitoring of wind turbine gearbox materials

The wind energy industry has been suffering from premature wind turbine gearbox failures since its inception. These components are designed to last 20-25 years. However, they rarely survive more than 7 years without being refurbished or replaced. The aim of this study is to better understand wind turbine gearbox failures and increase the reliability of this component. Failed samples were retrieved from the field. Thorough failure analysis revealed that misalignments, poor lubrication, and the presence of MnS inclusions can severely reduce the lifetime of wind turbine gearboxes. Rolling contact fatigue tests reiterate these findings. Acoustic emission monitoring was employed during laboratory tests. This condition monitoring technique was able to detect damage nucleation and propagation accurately during fatigue crack growth and rolling contact fatigue testing. Finally, finite element analysis was coupled with a constitutive model to quantify and predict damage in wind turbine gearboxes, while also testing for different service conditions. It was found that angular misalignment was the most detrimental service condition, followed by radial misalignment, and lack of lubrication. Additionally, an estimation of the remaining useful lifetime of the component was generated, further assisting wind turbine farm operators to move towards the implementation of a true predictive maintenance approach

A damage mechanics approach for lifetime estimation of wind turbine gearbox materials

Wind turbine gearboxes (WTG) have been suffering from premature failures and rarely live up to their designed lifetime. This study focuses on a better understanding of WTG failures. A finite element model of a gear pair was coupled with a constitutive model to quantify and predict damage, while also testing for different service conditions. A damage mechanics formulation is presented based on a physics-based dislocation slip model. Additionally, an estimation of the remaining useful lifetime of the component was generated, further assisting wind turbine farm operators to move towards the implementation of a truly predictive maintenance approach

Numerical evaluation of type I pressure vessels for ultra-deep ocean trench exploration

Oceans are areas on our planet which remain largely unexplored. This is mainly due to the considerable challenges involved in underwater exploration. So far the majority of surveys are carried out using Remotely Operated Vehicles (ROVs) and Automated Unmanned Vehicles (AUVs). These vehicles, despite their impressive capabilities, have several limitations, especially in terms of their operational endurance. Moreover, a very small number of ROVs have been qualified for operations in depths beyond 6 km. The use of ROVs in ocean trenches involves extremely complex operations and is not free of risk. The deepest known point is Challenger Deep at the Mariana Trench in the Pacific Ocean, with a maximum depth of just under 11 km. Only a handful of manned and unmanned missions have managed to reach this depth since Piccard's mission in 1960, on-board the bathyscaphe Trieste. Herewith we report on the finite elements analysis of type I pressure vessels for hydrogen storage to be used in future AUVs with long endurance capability for ultra-deep exploration

Use of UIoT for offshore surveys through autonomous vehicles

The ENDURUNS project is a European Research project of the Horizon 2020 framework, which has as its main objective to achieve the optimum and intelligent use of green hydrogen energy for long-term ocean surveys. The ENDURUNS system comprises an Unmanned Surface Vehicle (USV) and an Autonomous Underwater Vehicle (AUV) with gliding capability. The power pack of the USV integrates Li-ion batteries with photovoltaic panels, whilst the AUV employs Li-ion batteries and a hydrogen fuel cell. It is essential to develop a continuous monitoring ca-pability for the different systems of the vehicles. Data transmission between the devices onboard presents challenges due to the volume and structure of the different datasets. A telecommunications network has been designed to manage the operational components considered in the project. The autonomous vehicles perform measurements, providing their position and other data wirelessly. The system will generate a great volume of various signals during the survey. The Remote Control Centre needs to be interfaced with the vehicles in order to receive, manage and store the acquired data. An Underwater Internet of Things (IoT) platform is designed to establish efficient and smart data management. This study presents an exhaustive survey to analyse the telecommunication systems employed in the autonomous vehicles, including the back-end, user interface and mobile units. This paper presents the novel design of the hardware and software structure of the ENDURUNS project with regard to the literature, where its components and their in-terconnection layers are detailed, which is a novel scientific and technological approach for autonomous seabed surveying in deep oceans or in coastal areas