Wind energy is contributing to more and more portions in the world energy market. However,
one deterrent to even greater investment in wind energy is the considerable failure rate of …

Privacy protection as a major concern of the industrial big data enabling entities makes the
massive safety-critical operation data of a wind turbine unable to exert its great value …

Fault detection and classification are considered as one of the most mandatory techniques
in nowadays industrial monitoring. The necessity of fault monitoring is due to the fact that …

Synthetic minority oversampling technique (SMOTE) has been widely used in dealing with
the imbalance classification problem in the machine learning field. However, classical …

Vibration analysis is considered as a cost-efficient and nondestructive technique to monitor
the transformer operating conditions and evaluate the transformer mechanical integrity. This …

Condition monitoring of the wind turbine based on supervisory control and data acquisition
(SCADA) data has attracted much attention in recent years. Nevertheless, there are some …

In response to the high demand of the operation reliability and predictive maintenance,
health monitoring and fault diagnosis and classification have been paramount for complex …

In fault diagnosis, deep learning plays an important role, but still lacks good interpretability.
To address this issue, we develop a novel fault frequency priors fusion deep learning (FFP …

In this article, the simultaneous state and fault estimation problem is investigated for a class
of nonlinear 2-D shift-varying systems, where the sensors and the estimator are connected …

Wind turbines are usually exposed to dynamic and adverse environmental conditions, and
faults on mechanical parts are major threats to the economic efficiency of wind farms …