Simulating Eddy Current Sensors in Blade Tip Timing Application: Modeling and Experimental Validation

N. Jamia, M. Friswell, S. El-Borgi, P. Rajendran
{"title":"Simulating Eddy Current Sensors in Blade Tip Timing Application: Modeling and Experimental Validation","authors":"N. Jamia, M. Friswell, S. El-Borgi, P. Rajendran","doi":"10.1115/IMECE2018-87414","DOIUrl":null,"url":null,"abstract":"In gas turbines, the blade vibration caused by aerodynamic excitation or by self-excited vibration and flutter leads to high cycle fatigue that represents the main cause of damage in turbomachinery. Turbine operators have resorted to assess the blade vibrations using non-contact systems. One of the well-known non-contact methods is Blade Tip Timing (BTT). BTT is based on monitoring the time history of the passing of each blade tip by stationary sensors mounted in a casing around the blades. The BTT method evaluates the blade time of arrival (ToA) in order to estimate the vibration. To perform the BTT technique, optical sensors were widely used by industry due to their high accuracy and performance under high temperatures, but the main drawback of these systems is their low tolerance to the presence of contaminants. To mitigate this downside, Eddy Current Sensors (ECS) are a good alternative for health monitoring application in gas turbines due to their immunity to contaminants and debris. This type of sensor was used by many researches, predominantly on the experimental side. The focus was to extract response frequencies and therefore the accuracy of the timing measurement was ignored due to the lack of modeling. This paper fills the gap between experiments and modeling by simulating a BTT application where detailed finite element modeling of active and passive ECS outputs was performed. A test rig composed of a bladed disk with 12 blades clamped to a rotating shaft was designed and manufactured in order to validate the proposed models with experimental measurements. Finally, a comparison between these different types of sensor output is presented to show the effect of the blade tip clearance and rotational speed on the accuracy of the BTT measurement.","PeriodicalId":375383,"journal":{"name":"Volume 9: Mechanics of Solids, Structures, and Fluids","volume":"184 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Volume 9: Mechanics of Solids, Structures, and Fluids","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/IMECE2018-87414","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

In gas turbines, the blade vibration caused by aerodynamic excitation or by self-excited vibration and flutter leads to high cycle fatigue that represents the main cause of damage in turbomachinery. Turbine operators have resorted to assess the blade vibrations using non-contact systems. One of the well-known non-contact methods is Blade Tip Timing (BTT). BTT is based on monitoring the time history of the passing of each blade tip by stationary sensors mounted in a casing around the blades. The BTT method evaluates the blade time of arrival (ToA) in order to estimate the vibration. To perform the BTT technique, optical sensors were widely used by industry due to their high accuracy and performance under high temperatures, but the main drawback of these systems is their low tolerance to the presence of contaminants. To mitigate this downside, Eddy Current Sensors (ECS) are a good alternative for health monitoring application in gas turbines due to their immunity to contaminants and debris. This type of sensor was used by many researches, predominantly on the experimental side. The focus was to extract response frequencies and therefore the accuracy of the timing measurement was ignored due to the lack of modeling. This paper fills the gap between experiments and modeling by simulating a BTT application where detailed finite element modeling of active and passive ECS outputs was performed. A test rig composed of a bladed disk with 12 blades clamped to a rotating shaft was designed and manufactured in order to validate the proposed models with experimental measurements. Finally, a comparison between these different types of sensor output is presented to show the effect of the blade tip clearance and rotational speed on the accuracy of the BTT measurement.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
涡流传感器在叶尖定时中的模拟应用:建模与实验验证
在燃气轮机中,由气动激励或自激振动和颤振引起的叶片振动导致高周疲劳,这是导致涡轮机械损坏的主要原因。涡轮操作员已经采用非接触式系统来评估叶片振动。其中一种众所周知的非接触方法是叶尖定时(BTT)。BTT是通过安装在叶片周围的固定传感器来监测每个叶片尖端通过的时间历史。BTT方法通过叶片到达时间(ToA)来估计振动。为了实现BTT技术,光学传感器由于其在高温下的高精度和性能而被广泛应用于工业,但这些系统的主要缺点是对污染物的容忍度较低。为了减轻这一缺点,涡流传感器(ECS)是燃气轮机健康监测应用的一个很好的替代方案,因为它们对污染物和碎片具有免疫力。这种类型的传感器被许多研究使用,主要是在实验方面。重点是提取响应频率,因此,由于缺乏建模,定时测量的准确性被忽略。本文通过模拟BTT应用程序填补了实验和建模之间的空白,该应用程序对主动和被动ECS输出进行了详细的有限元建模。设计并制造了一个由12个叶片夹紧在转轴上的叶片盘组成的试验台,通过实验测量验证了所提出的模型。最后,对不同类型的传感器输出进行了比较,以显示叶尖间隙和转速对BTT测量精度的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Macro-Scale Geometric Voids to Alter Stress Wave Propagation in Solids Finite Element Analysis of the Effect of Porosity on the Plasticity and Damage Behavior of Mg AZ31 and Al 6061 T651 Alloys Effects of Drive Side Pressure Angle on Gear Fatigue Crack Propagation Life for Spur Gears With Symmetric and Asymmetric Teeth Guidelines and Limitations of the Compact Compression Specimen Modelling Stress Softening and Necking Phenomena in Double Network Hydrogels
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1