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
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
Lina完成签到 ,获得积分10
刚刚
量子星尘发布了新的文献求助10
1秒前
1秒前
sodarday完成签到,获得积分10
2秒前
Fayth完成签到,获得积分10
2秒前
伊里七关注了科研通微信公众号
2秒前
Spike发布了新的文献求助20
2秒前
Biophilia完成签到 ,获得积分10
3秒前
大角牛发布了新的文献求助10
3秒前
猪头发布了新的文献求助10
3秒前
李健的小迷弟应助王柯采纳,获得10
3秒前
3秒前
zzz完成签到,获得积分10
3秒前
科目三应助南风采纳,获得10
3秒前
rrjl完成签到,获得积分10
3秒前
tejing1158发布了新的文献求助10
4秒前
含蓄的溪灵完成签到,获得积分10
4秒前
善学以致用应助xuan采纳,获得10
4秒前
NexusExplorer应助xuan采纳,获得10
5秒前
天天快乐应助xuan采纳,获得10
5秒前
科研通AI6应助xuan采纳,获得10
5秒前
科研通AI6应助xuan采纳,获得10
5秒前
herococa应助xuan采纳,获得10
5秒前
领导范儿应助xuan采纳,获得10
5秒前
科研通AI6应助xuan采纳,获得20
5秒前
zhonglv7应助xuan采纳,获得10
5秒前
科研通AI6应助xuan采纳,获得10
5秒前
重要代荷发布了新的文献求助10
5秒前
5秒前
鲤鱼谷秋完成签到 ,获得积分10
5秒前
DHMO完成签到,获得积分10
5秒前
臭屁萌发布了新的文献求助10
5秒前
6秒前
7秒前
7秒前
8秒前
8秒前
8秒前
詹思宇完成签到 ,获得积分20
8秒前
GCY发布了新的文献求助10
9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
Binary Alloy Phase Diagrams, 2nd Edition 8000
Encyclopedia of Reproduction Third Edition 3000
Comprehensive Methanol Science Production, Applications, and Emerging Technologies 2000
From Victimization to Aggression 1000
Translanguaging in Action in English-Medium Classrooms: A Resource Book for Teachers 700
Exosomes Pipeline Insight, 2025 500
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5652169
求助须知:如何正确求助?哪些是违规求助? 4786896
关于积分的说明 15058821
捐赠科研通 4810805
什么是DOI,文献DOI怎么找? 2573410
邀请新用户注册赠送积分活动 1529283
关于科研通互助平台的介绍 1488184