Automated cable monitoring system using smart sensors under the varying tension force condition
As a demand for long-span bridges is increasing worldwide,maintenance of bridges has become a critical issue to keep the structural safety and prolong bridge lifetime.Cable-stayed bridges have been preferably used for construction of long-span bridges,due to their better aerodynamic behavior and higher overall stiffness compared to suspension bridges.Given that the stay-cable is a significant load carrying component in the cable-stayed bridges,monitoring the health condition of a cable is needed to assure the safety of the bridges.Indeed,various methodologies have been developed to measure cable tension forces,an important indicator of structural health of cable-stayed bridges in service.Particularly,vibration-based tension estimation has been known as a cost-effective approach,which has been used to build a monitoring system using wireless smart sensors.However,full automation considering varying cable tension has not been demonstrated in the literature.This study aims to develop the automated cable tension monitoring system using smart sensors,possible to measure the tension under the varying tension conditions.A peak-picking algorithm tailored to cable vibration is proposed using a convolution neural network(CNN)to apply the vibration-based tension estimation method to automated cable tension monitoring.The developed system features embedded processing on smart sensors,including data acquisition,power spectral density analysis,automated peak-picking,and tension estimation for varying tension forces.A series of laboratory tests are conducted on a cable to verify the operation of proposed automated monitoring system under the variety of tension forces.The experimental results validate the proposed system for automated cable tension monitoring with different tension conditions.
Automated cable monitoring embedded processing smart sensors peak-picking
Seunghoo Jeong Hyunjun Kim Junhwa Lee Sung-Han Sim
School of Urban and Environmental Engineering,Ulsan National Institute of Science and Technology(UNIST),Ulsan,Republic of Korea
国际会议
The 7th World Conference on Structural Control and Monitoring(7WCSCM)(第七届结构控制与监测世界大会)
青岛
英文
2170-2171
2018-07-22（万方平台首次上网日期，不代表论文的发表时间）