Using machine learning for dynamic authentication in telehealth: A tutorial
Telehealth systems have evolved into more prevalent services that can serve people in
remote locations and at their homes via smart devices and 5G systems. Protecting the …
remote locations and at their homes via smart devices and 5G systems. Protecting the …
Multi-source weighted source-free domain transfer method for rotating machinery fault diagnosis
The mainstream approach to addressing the issues of insufficient historical data and high
annotation costs in the domain of rotating machinery is to build transfer learning models …
annotation costs in the domain of rotating machinery is to build transfer learning models …
CAD system for inter-turn fault diagnosis of offshore wind turbines via multi-CNNs & feature selection
Condition monitoring, fault diagnosis, and scheduled maintenance of wind turbines (WTs)
are becoming a necessity to maximize their economic benefits and reduce their downtime …
are becoming a necessity to maximize their economic benefits and reduce their downtime …
Federated learning for condition monitoring of industrial processes: a review on fault diagnosis methods, challenges, and prospects
Condition monitoring (CM) of industrial processes is essential for reducing downtime and
increasing productivity through accurate Condition-Based Maintenance (CBM) scheduling …
increasing productivity through accurate Condition-Based Maintenance (CBM) scheduling …
An efficient federated transfer learning framework for collaborative monitoring of wind turbines in IoE-enabled wind farms
Wind turbine (WT) condition monitoring has gained increasing interests in the era of the
Internet of Energy (IoE), and existing monitoring approaches mainly focus on training a …
Internet of Energy (IoE), and existing monitoring approaches mainly focus on training a …
Fault diagnosis of wind turbines under nonstationary conditions based on a novel tacho-less generalized demodulation
D Liu, L Cui, W Cheng - Renewable Energy, 2023 - Elsevier
Abstract—The fault diagnosis of wind turbines under nonstationary conditions is still
challenging. This paper proposes a novel tacho-less generalized demodulation (NTLGD) …
challenging. This paper proposes a novel tacho-less generalized demodulation (NTLGD) …
Deep mixed domain generalization network for intelligent fault diagnosis under unseen conditions
Emerging intelligent fault diagnosis models based on domain adaptation can resolve
domain shift problems produced by different working conditions. However, the prerequisite …
domain shift problems produced by different working conditions. However, the prerequisite …
The fault frequency priors fusion deep learning framework with application to fault diagnosis of offshore wind turbines
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 …
To address this issue, we develop a novel fault frequency priors fusion deep learning (FFP …
A multi-step probability density prediction model based on gaussian approximation of quantiles for offshore wind power
W Zhang, Y He, S Yang - Renewable Energy, 2023 - Elsevier
With the increasing utilization of offshore wind power, accurate prediction of offshore wind
power is crucial for preventive control and scheduling. In this paper, a new hybrid probability …
power is crucial for preventive control and scheduling. In this paper, a new hybrid probability …
Extreme structural response prediction and fatigue damage evaluation for large-scale monopile offshore wind turbines subject to typhoon conditions
Offshore wind is becoming the way forward for green energy harnessing worldwide.
However, frequent typhoons are a major constraint for the development of offshore wind …
However, frequent typhoons are a major constraint for the development of offshore wind …