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 地震学 复合材料 病理 物理 电气工程
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
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

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
超帅连虎发布了新的文献求助10
1秒前
陈小白发布了新的文献求助10
2秒前
2秒前
2秒前
敢敢完成签到,获得积分10
3秒前
999完成签到,获得积分20
4秒前
yookia应助科研通管家采纳,获得10
5秒前
coolkid应助科研通管家采纳,获得10
5秒前
麦乐迪应助科研通管家采纳,获得10
5秒前
田様应助科研通管家采纳,获得10
5秒前
领导范儿应助科研通管家采纳,获得10
5秒前
5秒前
5秒前
5秒前
上官若男应助科研通管家采纳,获得10
5秒前
Orange应助科研通管家采纳,获得10
5秒前
深情安青应助科研通管家采纳,获得10
5秒前
orixero应助科研通管家采纳,获得10
5秒前
打打应助科研通管家采纳,获得10
6秒前
coolkid应助科研通管家采纳,获得10
6秒前
6秒前
6秒前
6秒前
隐形曼青应助科研通管家采纳,获得10
6秒前
6秒前
Ava应助科研通管家采纳,获得10
6秒前
6秒前
6秒前
开朗艳一发布了新的文献求助10
6秒前
6秒前
6秒前
6秒前
7秒前
7秒前
天天快乐应助雪1214采纳,获得10
7秒前
xuan完成签到,获得积分10
8秒前
独特的兰发布了新的文献求助10
8秒前
1111应助不散的和弦采纳,获得10
9秒前
10秒前
10秒前
高分求助中
Ophthalmic Equipment Market by Devices(surgical: vitreorentinal,IOLs,OVDs,contact lens,RGP lens,backflush,diagnostic&monitoring:OCT,actorefractor,keratometer,tonometer,ophthalmoscpe,OVD), End User,Buying Criteria-Global Forecast to2029 2000
A new approach to the extrapolation of accelerated life test data 1000
Cognitive Neuroscience: The Biology of the Mind 1000
Cognitive Neuroscience: The Biology of the Mind (Sixth Edition) 1000
ACSM’s Guidelines for Exercise Testing and Prescription, 12th edition 588
Christian Women in Chinese Society: The Anglican Story 500
A Preliminary Study on Correlation Between Independent Components of Facial Thermal Images and Subjective Assessment of Chronic Stress 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3961269
求助须知:如何正确求助?哪些是违规求助? 3507536
关于积分的说明 11136688
捐赠科研通 3239991
什么是DOI,文献DOI怎么找? 1790625
邀请新用户注册赠送积分活动 872449
科研通“疑难数据库(出版商)”最低求助积分说明 803199