AI-enabled and multimodal data driven smart health monitoring of wind power systems: A case study-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

AI-enabled and multimodal data driven smart health monitoring of wind power systems: A case study

Published:2023-04 Issue: Volume:56 Page:102018
ISSN:1474-0346
Container-title:Advanced Engineering Informatics
language:en
Short-container-title:Advanced Engineering Informatics

Author:

Zhao Yang,Zhang Yanjie,Li Zeqiang,Bu Lingguo,Han Su

Funder

National Natural Science Foundation of China

Natural Science Foundation of Shandong Province

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems,Building and Construction

Reference47 articles.

1. Data transformation;Manikandan;J. Pharmacol. Pharmacother.,2010

2. Data-driven instruction;Bedwell;Phi Delta Kappa Fastbacks,2004

3. On damage diagnosis for a wind turbine blade using pattern recognition;Dervilis;J. Sound Vib.,2014

4. Damage and nonlinearities detection in wind turbine blades based on strain field pattern recognition. FBGs, OBR and strain gauges comparison;Sierra-Pérez;Compos. Struct.,2016

5. A survey of modeling for prognosis and health management of industrial equipment;Yucesan;Adv. Eng. Inf.,2021

Cited by 7 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. Neural architecture search for multi-sensor information fusion-based intelligent fault diagnosis;Advanced Engineering Informatics;2024-10

2. Fractional-order transfer Q-learning based on modal decomposition and convolutional neural networks for voltage control of smart grids;Advanced Engineering Informatics;2024-10

3. A short-term wind speed prediction method based on the IDBO-BPNN;Engineering Research Express;2024-08-29

4. Advancements in condition monitoring and fault diagnosis of rotating machinery: A comprehensive review of image-based intelligent techniques for induction motors;Engineering Applications of Artificial Intelligence;2024-04

5. Defect detection of the surface of wind turbine blades combining attention mechanism;Advanced Engineering Informatics;2024-01

同舟云学术

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