A hybrid 3DSE-CNN-2DLSTM model for compound fault detection of wind turbines

Author:

Wang Tian,Yin LinfeiORCID

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference48 articles.

1. Agnostic CH-DT technique for SCADA network high-dimensional data-aware intrusion detection system;Ahakonye;IEEE Internet of Things Journal,2023

2. A novel targeted method of informative frequency band selection based on lagged information for diagnosis of gearbox single and compound faults;Alavi;Mechanical Systems and Signal Processing,2022

3. CAD system for inter-turn fault diagnosis of offshore wind turbines via multi-CNNs & feature selection;Attallah;Renewable Energy,2023

4. Critical comparison of power-based wind turbine fault-detection methods using a realistic framework for SCADA data simulation;Aziz;Renewable and Sustainable Energy Reviews,2021

5. A multi-factor driven spatiotemporal wind power prediction model based on ensemble deep graph attention reinforcement learning networks;Cheng;Energy,2023

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