A statistical approach to abstract and predict turbine states in an online manner has been
developed. Online inference is performed on temperature measurement residuals to predict …

In the process of detecting the paint film thickness of offshore wind turbine towers, there are
problems such as the risk of high-altitude and the changeable working environments, which …

This paper proposes an approach for stress condition monitoring and maintenance
assessment in wind turbines (WTs) through large amounts of collected data from the …

Details about a fault's progression, including the remaining-useful-lifetime (RUL), are key
features in monitoring, industrial operation and maintenance (O&M) planning. In order to …

A data-driven model based on Bayesian classifiers and multivariate analysis of the power
curve (wind speed vs. power) for monitoring wind farms' performance is presented. A new …

Purpose This paper aims to explore how maintenance tasks can be planned and executed
in a smarter way and, consequently, how the operations and maintenance of offshore wind …

With increase in the number of sensors installed on sub-assemblies of industrial
components, the amount of data collected is rapidly increasing. These data hold information …

Abstracting turbine states and predicting the transition into failure states ahead of time is
important in operation and maintenance of wind turbines. This study presents a method to …

In this study, we propose a method to monitor state transitions for wind turbines based on the
online inference on model residuals. Slowly developing faults in wind turbine can, when not …

The world's first large scale offshore wind farm, Horns Rev 1, is approaching the
decommissioning phase the profitability of future investments therefore has to be …