清晨好,您是今天最早来到科研通的研友!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,伴您科研之路漫漫前行!

Full-field dynamic strain prediction on a wind turbine using displacements of optical targets measured by stereophotogrammetry

有限元法 固定装置 应变计 涡轮叶片 流离失所(心理学) 结构工程 结构健康监测 振动器 涡轮机 位移场 工程类 悬臂梁 声学 振动 机械工程 物理 心理治疗师 心理学
作者
Javad Baqersad,Christopher Niezrecki,Peter Avitabile
出处
期刊:Mechanical Systems and Signal Processing [Elsevier]
卷期号:62-63: 284-295 被引量:88
标识
DOI:10.1016/j.ymssp.2015.03.021
摘要

Health monitoring of rotating structures (e.g. wind turbines and helicopter blades) has historically been a challenge due to sensing and data transmission problems. Unfortunately mechanical failure in many structures initiates at components on or inside the structure where there is no sensor located to predict the failure. In this paper, a wind turbine was mounted with a semi-built-in configuration and was excited using a mechanical shaker. A series of optical targets was distributed along the blades and the fixture and the displacement of those targets during excitation was measured using a pair of high speed cameras. Measured displacements with three dimensional point tracking were transformed to all finite element degrees of freedom using a modal expansion algorithm. The expanded displacements were applied to the finite element model to predict the full-field dynamic strain on the surface of the structure as well as within the interior points. To validate the methodology of dynamic strain prediction, the predicted strain was compared to measured strain by using six mounted strain-gages. To verify if a simpler model of the turbine can be used for the expansion, the expansion process was performed both by using the modes of the entire turbine and modes of a single cantilever blade. The results indicate that the expansion approach can accurately predict the strain throughout the turbine blades from displacements measured by using stereophotogrammetry.

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
5秒前
long发布了新的文献求助10
16秒前
Wan完成签到,获得积分10
33秒前
42秒前
lhl完成签到,获得积分0
47秒前
48秒前
1分钟前
cadcae完成签到,获得积分10
1分钟前
huco完成签到,获得积分10
1分钟前
SciGPT应助科研通管家采纳,获得10
1分钟前
鲤鱼山人完成签到 ,获得积分10
1分钟前
浮游应助王贤平采纳,获得10
1分钟前
科科通通完成签到,获得积分10
1分钟前
www完成签到 ,获得积分10
1分钟前
刘玲完成签到 ,获得积分10
1分钟前
1分钟前
浮游应助王贤平采纳,获得10
2分钟前
静静完成签到 ,获得积分10
2分钟前
Lillianzhu1完成签到,获得积分10
2分钟前
内向的雅山应助香菜张采纳,获得10
2分钟前
李爱国应助香菜张采纳,获得50
2分钟前
王贤平完成签到,获得积分10
2分钟前
美好灵寒完成签到 ,获得积分10
2分钟前
long发布了新的文献求助10
2分钟前
2分钟前
2分钟前
dx完成签到,获得积分10
2分钟前
debu9完成签到,获得积分10
3分钟前
自然亦凝完成签到,获得积分10
3分钟前
华仔应助科研通管家采纳,获得10
3分钟前
上官若男应助科研通管家采纳,获得50
3分钟前
3分钟前
传奇3应助舒适的大有采纳,获得10
3分钟前
myq完成签到 ,获得积分10
3分钟前
香菜张完成签到,获得积分10
3分钟前
龚瑶完成签到 ,获得积分10
3分钟前
3分钟前
ayato发布了新的文献求助10
3分钟前
hqh发布了新的文献求助10
3分钟前
4分钟前
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
Nonlinear Problems of Elasticity 3000
List of 1,091 Public Pension Profiles by Region 1581
Encyclopedia of Agriculture and Food Systems Third Edition 1500
Minimizing the Effects of Phase Quantization Errors in an Electronically Scanned Array 1000
Specialist Periodical Reports - Organometallic Chemistry Organometallic Chemistry: Volume 46 1000
Current Trends in Drug Discovery, Development and Delivery (CTD4-2022) 800
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 纳米技术 计算机科学 内科学 化学工程 复合材料 物理化学 基因 遗传学 催化作用 冶金 量子力学 光电子学
热门帖子
关注 科研通微信公众号,转发送积分 5534583
求助须知:如何正确求助?哪些是违规求助? 4622588
关于积分的说明 14582660
捐赠科研通 4562738
什么是DOI,文献DOI怎么找? 2500362
邀请新用户注册赠送积分活动 1479864
关于科研通互助平台的介绍 1451095