Fiber Bragg grating sensors for structural health monitoring of Tsing Ma bridge: Background and experimental observation

Chan, Tommy H.T.; Yu, Ling; Tam, Hwa Yaw; Ni, Yiqing; Liu, S. Y.; Chung, W.H.; Cheng, Liangliang

doi:10.1016/j.engstruct.2005.09.018

Cited by 404 publications

(218 citation statements)

References 32 publications

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“…Also, sensors are promising sensing alternatives in SHM system and future smart structures. They exhibit several advantages such as electromagnetic interference (EMI) immunity, harsh condition immunity, lightweight, embeds ability, as compared with traditional sensors [2,3]. Among vary optical based sensors; Fiber Bragg Grating (FBG) sensors are the leading technology because they have some more advantages such as linearity sensing, easily frequency multiplexed [2].…”

Section: Introductionmentioning

confidence: 99%

Specialized Sensors and System Modeling for Safety-critical Application

Jeong¹

2014

Journal of Electrical Engineering and Technology

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-Special purpose sensor design using MEMS (Micro-Electro-Mechanical Systems) technique is commonly used in Nondestructive Testing (NDT) research for the evaluation of existing structures and for the safety control and requirements. Various sensors and network have been developed for general infrastructures as well as safety-critical applications, e.g., aerospace, defense, and nuclear system, etc. In this paper, one of sensor technique using Fiber Bragg Gratings (FBG) and Finite Element Method (FEM) evaluation is discussed. The experimental setup and data collection technique is also demonstrated. The factors influencing test result and the advantages/limitations of this technique are also reviewed using various methods.

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Section: Introductionmentioning

confidence: 99%

Specialized Sensors and System Modeling for Safety-critical Application

Jeong¹

2014

Journal of Electrical Engineering and Technology

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“…SHM systems can be composed of tens or hundreds of sensors, each of which has to be powered. The monitoring system of three bridges in Hong Kong: Tsing Ma, Ting Kau and Kap Shui Mun contains 300 sensors measuring several variables (deformations, displacements, acceleration, temperature) (Chan et al, 2006). The monitoring system containing 63 sensors measures the stress in the girders of Taylor bridge in Canada (Kim et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

Experimental investigation on the piezoelectric energy harvester as the self-powered vibration sensor

Grzybek

Micek

2018

jtam

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The article presents an experimental study of a system consisting of a piezoelectric energy harvesting device, Graetz bridge rectifier, capacitor, voltage comparator and radio transmitter. In the presented experimental study, the recovered electrical energy is accumulated in the capacitor and is used to send signals by a radio transmitter. In the first part, the application of piezoelectric energy harvesting devices based on the cantilever beam in wireless monitoring systems is discussed. In the second part, the mathematical model of energy conversion in the piezoelectric energy harvesting devices is presented. In the third part, the characteristics obtained during laboratory research are presented.

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“…The first stage, falling in the mature stage, is to install sensors on the bridge structures and conduct much research on the data transition system, data acquisition technology, system integration technology, and other aspects. [2][3][4] The second stage is mainly the reasonable application of SHM data. A sound number of studies are mainly focused on the modal parameter identification, structural damage detection, performance prediction, and reliability assessment.…”

Section: Introductionmentioning

confidence: 99%

Dynamic extreme stress prediction of bridges based on nonlinear mixed Gaussian particle filtering algorithm and structural health monitoring data

Fan

Liu

2016

Advances in Mechanical Engineering

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In the long-term service period, the bridge health monitoring system produced a huge amount of monitoring stress data; proper handling of these data is one of the main difficulties in the field of structural health monitoring, especially to predict the structural stress based on the monitored data. The objectives of this article are to present: (1) a nonlinear dynamic model, (2) a nonlinear mixed Gaussian particle filtering algorithm for predicting the monitored data based on the dynamic model, and (3) an approach combining nonlinear mixed Gaussian particle filtering algorithm with structural health monitoring data to predict the structural stress under uncertainty in real time. And an actual example is provided to illustrate the application and feasibility of the proposed models and methods.

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Fiber Bragg grating sensors for structural health monitoring of Tsing Ma bridge: Background and experimental observation

Cited by 404 publications

References 32 publications

Specialized Sensors and System Modeling for Safety-critical Application

Specialized Sensors and System Modeling for Safety-critical Application

Experimental investigation on the piezoelectric energy harvester as the self-powered vibration sensor

Dynamic extreme stress prediction of bridges based on nonlinear mixed Gaussian particle filtering algorithm and structural health monitoring data

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