Fault diagnosis of wind turbine pitch system based on LSTM with multi-channel attention mechanism
Author:
Publisher
Elsevier BV
Subject
General Energy
Reference27 articles.
1. Data fusion based on an iterative learning algorithm for fault detection in wind turbine pitch control systems [J];Acho;Sensors,2021
2. Discussion of wind turbine performance based on SCADA data and multiple test case analysis [J];Astolfi;Energies,2022
3. The effect of dataset imbalance on the performance of SCADA intrusion detection systems;Balla;Sensors,2023
4. Anomaly detection and critical SCADA parameters identification for wind turbines based on LSTM-AE neural network;Chen;Renew. Energy,2021
5. A CNN encoder decoder LSTM model for sustainable wind power predictive analytics;Garg;Sustain. Comput.: Inform. Syst.,2023
Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. A hybrid intelligent diagnostic approach for spool jamming faults of hydraulic directional valves;Measurement;2025-02
2. A new chiller fault diagnosis method under the imbalanced data environment via combining an improved generative adversarial network with an enhanced deep extreme learning machine;Engineering Applications of Artificial Intelligence;2024-11
3. Particle accelerator power system early fault diagnosis based on deep learning and multi-sensor feature fusion;Engineering Research Express;2024-06-01
4. A hybrid fault diagnosis method for rolling bearings based on GGRU-1DCNN with AdaBN algorithm under multiple load conditions;Measurement Science and Technology;2024-04-02
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3