Despite a few recent meta-learning studies have facilitated few-shot cross-domain fault
diagnosis of bearing, they are limited to homogenous signal analysis and have challenges …

Data-driven intelligent systems provide a possible solution to condition-based maintenance
of wind turbines without experts' knowledge or mechanism models. However, the accuracy …

A wind turbine (WT) is an electromechanical system that often operates under a wide range
of production conditions. These electrical systems are nowadays expanding rapidly, and …

Condition monitoring (CM) of wind turbines (WTs) is commonly accepted as an effective way
to increase the availability and reduce the operation and maintenance (O&M) costs of wind …

Wind turbines have become one of the essential sources of energy generation due to their
contribution to energy security, economic development, job creation, and technological …

This research propounds a general theoretical and practical solution for the simulation of the
repair time of equipment and forecasting equipment preventive maintenance, availability …

This article develops a hybrid approach to fault detection and isolation (FDI) based on a
machine learning technique and quasi-Linear Parameter Varying (qLPV) zonotopic …

Condition-monitoring and anomaly-detection methods used for the assessment of wind
turbines are key to reducing operation and maintenance (O&M) cost and improving their …

Labeling the fault data is a time-consuming and expensive operation. Therefore, the
monitoring data obtained from wind farms are rarely accurately labeled. The method of deep …

The condition monitoring and potential anomaly detection of wind turbines have gained
significant attention because of the benefits of reducing the operating and maintenance …