Abnormal diagnosis of fiber Bragg grating strain gauges in health monitoring system

Xiao SUN; Qing-mei WANG; Zhen-wei LI; Jing-jing CHU

doi:10.37188/OPE.20212911.2581

您当前的位置：

首页 >

文章列表页 >

Abnormal diagnosis of fiber Bragg grating strain gauges in health monitoring system

Modern Applied Optics | 更新时间：2022-01-25

- Abnormal diagnosis of fiber Bragg grating strain gauges in health monitoring system
- Optics and Precision Engineering Vol. 29, Issue 11, Pages: 2581-2589(2021)
- 作者机构：
  
  1.青岛科技大学自动化与电子工程学院，山东青岛 266061
  2.中科院国家天文台，北京 100012
- 作者简介：
- 基金信息：
- DOI：10.37188/OPE.20212911.2581
  CLC： TN253;TH691.9
- Received：15 March 2021，
  
  Revised：11 May 2021，
  
  Published：15 November 2021
- 稿件说明：
移动端阅览
孙晓,王清梅,李振伟等.结构健康监测系统光纤Bragg光栅应变计的异常诊断[J].光学精密工程,2021,29(11):2581-2589.

SUN Xiao,WANG Qing-mei,LI Zhen-wei,et al.Abnormal diagnosis of fiber Bragg grating strain gauges in health monitoring system[J].Optics and Precision Engineering,2021,29(11):2581-2589.
孙晓,王清梅,李振伟等.结构健康监测系统光纤Bragg光栅应变计的异常诊断[J].光学精密工程,2021,29(11):2581-2589. DOI： 10.37188/OPE.20212911.2581.

SUN Xiao,WANG Qing-mei,LI Zhen-wei,et al.Abnormal diagnosis of fiber Bragg grating strain gauges in health monitoring system[J].Optics and Precision Engineering,2021,29(11):2581-2589. DOI： 10.37188/OPE.20212911.2581.

摘要

结构健康监测系统中光纤光栅应变计长期工作易发生故障，其本身的状态诊断与维护关系到系统的可靠性。基于同结构监测中光纤光栅应变计原始输出具有相同规律的特点，提出一种传感器异常诊断方法，利用信号处理方法提取测点样本长度、标准差、能量值及主成分周期值作为特征。通过循环迭代获取特征值聚合中心点，将特征偏离中心点距离标准化后融合为综合异常指数，实现传感器的异常和故障判别。仿真证明，故障测点为总测点数目的20%以内，可有效识别故障测点。对500米口径球面射电望远镜（FAST）工程健康监测系统的416个光纤光栅应变计测点进行诊断，成功提取317个传感器的特征，识别出4个故障测点与14个异常测点。该方法不需要先验知识训练，基于数据本身特性实现诊断，对光纤光栅应变计的多种故障有较强的指示作用，满足FAST结构健康监测的工程需求。

Abstract

Fiber Bragg grating strain gauges are usually used to access the structural strain and monitor the health of the structure. However， the performance of the structural health monitoring system is dependent on the status of such a large number of sensors， which are quite easy to break down after a long-term service in various conditions. Based on the phenomenon that similar characteristics will be observed for the outpout of the fiber grating strain gauge in the same structure， we propose a novel Malfunction-diagnosis method for the sensors in the fiber Bragg grating strain gauges. The proposed method extracted the eigenvalue s （i.e.， sample data length， standard deviation， energy value and principal component period） using signal processing algorithm. The eigenvalue convergence center points were determined by loop iterations. The eigenvalue distances from the convergence centers were standardized and merged into a comprehensive index for the health monitoring of the sensors. The simulation proves that the malfunction points can be effectively identified when the number of malfunction points is below 20% of the total points. The proposed method was used to monitor the 416 fiber Bragg grating strain gauges of five-hundred-meter aperture spherical telescope （FAST） health monitoring system， the results showed that the eigenvalue lists of 317 sensors could be extracted and 4 malfunction points and 14 abnormal points could be identified. Instead of a large amount of training with prior knowledge， the proposed method could provide reliable malfunction diagnosis for the sensors in fiber Bragg grating strain gauges just based on the characteristics of the data， which might be practical useful for the health monitoring of the FAST structure.

关键词

Keywords

references

TOMMY H T ， CHAN J L ， Andy Nguyenet ， et al . Preface： recent research advances on structural health monitoring of civil engineering structures ［J］. International Journal of Structural Stability and Dynamics ， 2020 ， 20 （ 10 ）： 2002002-1-2002002 - 3 . doi: 10.1142/s0219455420020022 http://dx.doi.org/10.1142/s0219455420020022

赵士元，崔继文，陈勐勐 . 光纤形状传感技术综述［J］. 光学精密工程， 2020 ， 28 （ 1 ）： 10 - 29 . doi: 10.3788/ope.20202801.0010 http://dx.doi.org/10.3788/ope.20202801.0010

ZHAO SH Y ， CUI J W ， CHEN M M . Review on optical fiber shape sensing technology ［J］. Opt. Precision Eng. ， 2020 ， 28 （ 1 ）： 10 - 29 . （in Chinese） . doi: 10.3788/ope.20202801.0010 http://dx.doi.org/10.3788/ope.20202801.0010

郭永兴，杨跃辉，熊丽，等 . 植入光纤布拉格光栅的不同杨氏模量软体材料弯曲测量响应特性［J］. 光学精密工程， 2020 ， 28 （ 8 ）： 1634 - 1643 .

GUO Y X ， YANG Y H ， XIONG L ， et al . Response characteristics of fiber Bragg gratings embedded in soft materials with different Young's modulus for bending measurement ［J］. Opt. Precision Eng. ， 2020 ， 28 （ 8 ）： 1634 - 1643 . （in Chinese）

章亚男，范迪，沈林勇，等 . FBG细径形状传感器的应变传递和精度实验［J］. 光学精密工程， 2019 ， 27 （ 7 ）： 1481 - 1491 . doi: 10.3788/OPE.20192707.1481 http://dx.doi.org/10.3788/OPE.20192707.1481

ZHANG Y N ， FAN D ， SHEN L Y ， et al . Strain transmission and accuracy experiment on fiber Bragg grating small-diameter shape sensors ［J］. Opt. Precision Eng. ， 2019 ， 27 （ 7 ）： 1481 - 1491 . （in Chinese） . doi: 10.3788/OPE.20192707.1481 http://dx.doi.org/10.3788/OPE.20192707.1481

NAN R D . Five hundred meter aperture spherical radio telescope （FAST）［J］. Science in China Series G ， 2006 ， 49 （ 2 ）： 129 - 148 . doi: 10.1007/s11433-006-0129-9 http://dx.doi.org/10.1007/s11433-006-0129-9

王晓琳，李东平，朱明，等 . FAST主动反射面健康监测系统设计与应用研究［J］. 广西科技大学学报， 2018 ， 29 （ 4 ）： 84 - 91， 98 .

WANG X L ， LI D P ， ZHU M ， et al . Design and application of health monitoring system of main reflector system for FAST ［J］. Journal of Guangxi University of Science and Technology ， 2018 ， 29 （ 4 ）： 84 - 91， 98 . （in Chinese）

CAZZULANI G ， CINQUEMANI S ， RONCHI M . A fault identification technique for FBG sensors embedded in composite structures ［J］. Smart Materials and Structures ， 2016 ， 25 （ 5 ）： 055049 . doi: 10.1088/0964-1726/25/5/055049 http://dx.doi.org/10.1088/0964-1726/25/5/055049

张晓丽 . 光纤结构健康监测系统及其传感器网络可靠性研究［D］. 南京：南京航空航天大学， 2012 ： 5 - 8 .

ZHANG X L . Study on the Optical Fiber Structural Health Monitoring System and its Sensor Network Reliability ［D］. Nanjing ： Nanjing University of Aeronautics and Astronautics ， 2012 ： 5 - 8 . （in Chinese）

姜婷睿 . 基于多模式识别的FBGS故障诊断与预测研究［D］. 哈尔滨：哈尔滨工程大学， 2018 ： 5 - 6 . doi: 10.21278/brod69210 http://dx.doi.org/10.21278/brod69210

JIANG T R . Diagnosis and Prediction Research of FBG Sensor Fault Based on Multi Pattern Recognition ［D］. Harbin ： Harbin Engineering University ， 2018 ： 5 - 6 . （in Chinese） . doi: 10.21278/brod69210 http://dx.doi.org/10.21278/brod69210

LI D L ， WANG Y ， WANG J X ， et al . Recent advances in sensor fault diagnosis： a review ［J］. Sensors and Actuators A： Physical ， 2020 ， 309 ： 111990 . doi: 10.1016/j.sna.2020.111990 http://dx.doi.org/10.1016/j.sna.2020.111990

CACCAVALE F ， MARINO A ， MUSCIO G ， et al . Discrete-time framework for fault diagnosis in robotic manipulators ［J］. IEEE Transactions on Control Systems Technology ， 2013 ， 21 （ 5 ）： 1858 - 1873 . doi: 10.1109/tcst.2012.2212196 http://dx.doi.org/10.1109/tcst.2012.2212196

李启明，李学明，黄庆，等 . 电机驱动系统电流传感器故障诊断与容错控制［J］. 科学技术与工程， 2020 ， 20 （ 32 ）： 13265 - 13272 . doi: 10.3969/j.issn.1671-1815.2020.32.026 http://dx.doi.org/10.3969/j.issn.1671-1815.2020.32.026

LI Q M ， LI X M ， HUANG Q ， et al . Fault diagnosis and fault tolerant control of current sensor for motor drive system ［J］. Science Technology and Engineering ， 2020 ， 20 （ 32 ）： 13265 - 13272 . （in Chinese） . doi: 10.3969/j.issn.1671-1815.2020.32.026 http://dx.doi.org/10.3969/j.issn.1671-1815.2020.32.026

余志伟，郭迎清 . 涡轴发动机分布式控制系统传感器故障诊断技术［J］. 推进技术， 2021 （ 1 ）： 200704 .

YU ZH W ， GUO Y Q . Sensor fault diagnosis technology for distributed control system of turbo shaft engine ［J］. Journal of Propulsion Technology ， 2021 （ 1 ）： 200704 . （in Chinese）

WU H ， ZHAO J S . Deep convolutional neural network model based chemical process fault diagnosis ［J］. Computers & Chemical Engineering ， 2018 ， 115 ： 185 - 197 . doi: 10.1016/j.compchemeng.2018.04.009 http://dx.doi.org/10.1016/j.compchemeng.2018.04.009

吴光强，陶义超，曾翔 . 数据驱动的变速器传感器故障诊断方法［J］. 同济大学学报（自然科学版）， 2021 ， 49 （ 2 ）： 272 - 279 .

WU G Q ， TAO Y CH ， ZENG X . Data-driven fault diagnosis method for transmission sensors ［J］. Journal of Tongji University （Natural Science）， 2021 ， 49 （ 2 ）： 272 - 279 . （in Chinese）

孙晓，王启明，朱明，等 . 光纤Bragg光栅应变计在500m口径球面射电望远镜工程索力监测中的应用［J］. 光学精密工程， 2015 ， 23 （ 4 ）： 919 - 925 . doi: 10.3788/ope.20152304.0919 http://dx.doi.org/10.3788/ope.20152304.0919

SUN X ， WANG Q M ， ZHU M ， et al . Application of optical fiber Bragg grating strain gauge to cable force monitoring of FAST ［J］. Opt. Precision Eng. ， 2015 ， 23 （ 4 ）： 919 - 925 . （in Chinese） . doi: 10.3788/ope.20152304.0919 http://dx.doi.org/10.3788/ope.20152304.0919

KRASNOPOLSKY R ， MARTÍNEZ M P ， SHANG H ， et al . Efficient direct method for self-gravity in 3D， accelerated by a fast Fourier transform ［J］. The Astrophysical Journal Letters Supplement Series ， 2021 ， 252 （ 2 ）： 14 . doi: 10.3847/1538-4365/abca97 http://dx.doi.org/10.3847/1538-4365/abca97

Views

917

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Abnormal diagnosis of fiber Bragg grating strain gauges in health monitoring system

Wind vector measurement based on ultrasonic sensors in the mixed noise of α and Gaussian noise

Signal processing methods of phase sensitive optical time domain reflectometer：a review

Signal processing algorithm of a single-track absolute encoder for photoelectrical theodolite

Assembly system for miniature optical parts and experimental study

Related Author

Qing-mei WANG

Zhen-wei LI

Jing-jing CHU

Yang ZHAO

Yi-ran SHI

Jin-wei QI

Si-ning QU

Kuang-lu YU

Related Institution

School of Communication Engineering， Jilin University

Beijing Key Laboratory of Modern Information Science and Network Technology

Institute of Information Science， Beijing Jiaotong University

Department of Electronic Information Engineering, Nanjing University of Aeronautics & Astronautics

Department of Electronic Engineering, Nanjing Xiaozhuang University

AI问答

Address：No.3888 Dong Nanhu Road, Changchun, Jilin, China Postal code：130033
Tel：0431-86176855 Email：gxjmgc@ciomp.ac.cn
Technical support is provided by Beijing Founder electronics co., LTD 吉ICP备11002662号-17 京公网安备11010802024621
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰