已入深夜,您辛苦了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!祝你早点完成任务,早点休息,好梦!

A review of the application of oil analysis in condition monitoring and life prediction of wind turbine gearboxes

机油分析 涡轮机 状态监测 断层(地质) 润滑油 粘度 可靠性工程 风力发电 医学诊断 海洋工程 状态维修 振动 工程类 汽车工程 石油工程 机械工程 声学 材料科学 医学 地质学 物理 电气工程 病理 地震学 复合材料
作者
Yu Bie,Xihao Liu,Tao Xu,Zhengfei Zhu,Zhixiong Li
出处
期刊:Insight [British Institute of Non-Destructive Testing]
卷期号:63 (5): 289-301 被引量:9
标识
DOI:10.1784/insi.2021.63.5.289
摘要

Condition maintenance of wind turbine gearboxes is important because of their high failure probability and the difficulties associated with their maintenance. Diagnosis and prognosis are the two main aspects of condition maintenance. This paper summarises the development of fault diagnosis and life prediction methods for wind power gearboxes. Fault diagnosis methods include single-method analyses such as vibration analysis, acoustic emission (AE) analysis and oil analysis, as well as multi-information testing methods. Oil analysis can be used to monitor early wear and the wear evolution process, providing direct data for the remaining useful life (RUL) prediction of the gearbox and the lubricant. Though wind turbine gearbox RUL prediction has received more attention among these diagnoses, there is still only limited literature available regarding this. Measurement of the lubricating oil condition is one of the most often applied methods for diagnosis and prognosis and within this the oil viscosity is an important parameter. Viscosity estimation has wide application prospects in oil analysis and the tendency is to apply online testing methods. Oil viscosity can be more accurately measured by considering thermal effects, which can be studied using numerical and experimental methods. This viscosity measurement has been increasingly applied in oil analysis, with viscosity sensors. This review focuses on the application of online oil testing and measurement technology in the fault diagnosis and RUL prediction of wind turbine gearboxes. Challenging problems are identified and possible solutions are suggested in this review.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
细心白竹完成签到 ,获得积分10
1秒前
慕青应助火星上项链采纳,获得10
1秒前
cmmm完成签到 ,获得积分10
1秒前
Rory完成签到 ,获得积分10
2秒前
4秒前
丘比特应助小德采纳,获得10
4秒前
6秒前
guan完成签到,获得积分10
8秒前
赵狗儿完成签到,获得积分10
8秒前
Zhaoyuemeng发布了新的文献求助10
9秒前
9秒前
科研通AI6.3应助PearRay采纳,获得10
9秒前
11秒前
赵狗儿发布了新的文献求助10
11秒前
12秒前
完美世界应助积极乌龟采纳,获得10
12秒前
Yikao完成签到 ,获得积分10
13秒前
yooga完成签到,获得积分10
13秒前
15秒前
沐风发布了新的文献求助10
16秒前
AZN完成签到 ,获得积分10
16秒前
文艺问柳完成签到 ,获得积分10
16秒前
秋博发布了新的文献求助10
17秒前
18秒前
penxyy应助hujie采纳,获得50
19秒前
Annie完成签到 ,获得积分10
19秒前
20秒前
核桃应助科研通管家采纳,获得10
21秒前
ame发布了新的文献求助10
21秒前
核桃应助科研通管家采纳,获得30
21秒前
所所应助科研通管家采纳,获得10
21秒前
烟花应助科研通管家采纳,获得10
21秒前
田様应助科研通管家采纳,获得10
21秒前
核桃应助科研通管家采纳,获得10
21秒前
核桃应助科研通管家采纳,获得20
21秒前
星辰大海应助科研通管家采纳,获得10
21秒前
在水一方应助科研通管家采纳,获得10
21秒前
科研通AI2S应助科研通管家采纳,获得80
21秒前
24秒前
哈哈哈哈发布了新的文献求助10
25秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Modern Epidemiology, Fourth Edition 5000
Handbook of pharmaceutical excipients, Ninth edition 5000
Digital Twins of Advanced Materials Processing 2000
Weaponeering, Fourth Edition – Two Volume SET 2000
Polymorphism and polytypism in crystals 1000
Social Cognition: Understanding People and Events 800
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 纳米技术 有机化学 物理 生物化学 化学工程 计算机科学 复合材料 内科学 催化作用 光电子学 物理化学 电极 冶金 遗传学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 6027192
求助须知:如何正确求助?哪些是违规求助? 7674801
关于积分的说明 16184774
捐赠科研通 5174836
什么是DOI,文献DOI怎么找? 2769013
邀请新用户注册赠送积分活动 1752443
关于科研通互助平台的介绍 1638214