Wind Turbine Rotor Fault Prediction Based on Convolutional Neural Network
Author:
Affiliation:
1. Nanjing Power Supply Branch State Grid Jiangsu Electric Power Co., LTD,Nanjing,China
2. Nanjing Suyi Industrial Co., LTD, State Grid Jiangsu Electric Power Co., LTD,Nanjing,China
3. Business School, Nanjing University,Nanjing,China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9948700/9948714/09948980.pdf?arnumber=9948980
Reference20 articles.
1. Fault diagnosis of wind turbine structures using decision tree learning algorithms with big data
2. A novel implementation of kNN classifier based on multi-tupled meteorological input data for wind power prediction
3. Wind turbine health state monitoring based on a Bayesian data-driven approach
4. On Fault Prediction for Wind Turbine Pitch System Using Radar Chart and Support Vector Machine Approach
5. Wind turbine fault detection based on SCADA data analysis using ANN
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