Intelligent pavement condition assessment using piezofloating-gate sensors
This study presents a self-powered sensing approach for pavement health monitoring based on the interpretation of the data outputted from a piezo-floating-gate(PFG)sensor.The recently developed PFG sensor operates by harvesting mechanical energy from structures using a piezoelectric transducers.These piezoelectric materials generate electrical energy when subjected to an external mechanical loading.The beauty of this technology is that the signal sensed by the piezoelectric transducers from traffic loading can be used both for empowering the self-powered sensors and damage diagnosis.Numerical studies are carried out to evaluate the performance the proposed self-powered sensing system.Different 3D finite element(FE)models of an asphalt concrete(AC)pavement are developed using ABAQUS to simulate the pavement response under different damage scenarios.The damage detection accuracy is improved through a data fusion model based on the effect of group of sensors.The proposed senor fusion model is based on the integration of a Gaussian mixture model(GMM)for defining descriptive features,different feature selection algorithms,and a robust computational intelligence approach for multi-class damage classification.
Pavement health monitoring self-powered sensors sensor fusion
H.Hasni N.Lajnef K.Chatti K.Aono S.Chakrabartty F.Faridazar
Department of Civil and Environmental Engineering,Michigan State University,East Lansing,MI 48824,US Department of Computer Science & Engineering,Washington University,Saint Louis,MO 63130,USA Turner-Fairbank Highway Research Center,FHWA,McLean,VA 22101,USA
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
2893-2902
2018-07-22（万方平台首次上网日期，不代表论文的发表时间）