Fault state recognition of wind turbine gearbox based on generalized multi-scale dynamic time warping

Author:

Pang Bin1ORCID,Tian Tian2,Tang Gui-Ji2

Affiliation:

1. National & Local Joint Engineering Research Center of Metrology Instrument and System, College of Quality and Technical Supervision, Hebei University, Baoding, China

2. Department of Mechanical Engineering, North China Electric Power University, Baoding, China

Abstract

Fault diagnosis of wind turbine gearbox is significant to ensure the operating efficiency and reduce the maintenance cost of wind farms. The key to achieve an accurate fault diagnosis is to extract the evidence of fault state identification effectively. Dynamic time warping has been widely used as a classifier for automatic pattern recognition as the dynamic time warping distance can indicate the similarity between two data sequences. The similarity between the analyzed signal and the template signal can be an evidence for characterizing the fault types of the analyzed signal; a generalized multi-scale dynamic time warping algorithm was accordingly developed in this article to quantitatively evaluate the condition information of wind turbine gearbox by calculating the generalized multi-scale dynamic time warping distances between the template signal (i.e. the vibration signal of wind turbine gearbox in normal state) and the testing signal (i.e. the vibration signals of wind turbine gearbox to be analyzed). Then, the sensitive features of the condition information evaluation results obtained via the generalized multi-scale dynamic time warping algorithm were selected by the Laplace Score approach to construct the eigenvector. Finally, random forest was introduced to realize the intelligent fault recognition of wind turbine gearbox. The analysis results of both experimental and engineering signals indicate that the presented method can accurately identify different fault states of wind turbine gearbox. In addition, the proposed method performs a higher accuracy of fault state classification compared with some existing methods.

Funder

National Natural Science Foundation of China

National Natural Science Foundation of Hebei Province

Publisher

SAGE Publications

Subject

Mechanical Engineering,Biophysics

Cited by 18 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

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