Now showing 1 - 2 of 2
  • Publication
    Effect of Road Surface, Vehicle, and Device Characteristics on Energy Harvesting from Bridge–Vehicle Interactions
    Energy harvesting to power sensors for structural health monitoring (SHM) has received huge attention worldwide. A number of practical aspects affecting energy harvesting and the possibility of health monitoring directly from energy harvesters is investigated here. The key idea is the amount of power received from a damaged and an undamaged structure varying and the signature of such variation can be used for SHM. For this study, a damaged bridge and an undamaged bridge are considered with harvesters located at different positions and the power harvested is accessed numerically to determine how energy harvesting can act as a damage detector and monitor. Bridge–vehicle interaction is exploited to harvest energy. For a damaged bridge, a bilinear breathing crack is considered. Variable surface roughness according to ISO 8606:1995(E) is considered such that the real values can be considered in the simulation. The possibility of a drive-by type health monitoring using energy harvesting is highlighted and the effects of road surface on such monitoring are identified. The sensitivity of the harvester health monitoring to locations and extents of crack damage are reported. This study investigates the effects of multiple harvesters and the effects of vehicular parameters on the harvested power. Continuous harvesting over a length of the bridge is considered semianalytically. A comparison among the numerical simulations, detailed finite element analysis, and experimental results emphasizes the feasibility of the proposed method.
      414Scopus© Citations 33
  • Publication
    Estimation of nonlinearities from pseudodynamic and dynamic responses of bridge structures using the Delay Vector Variance method
    Analysis of the variability in the responses of large structural systems and quantification of their linearity or nonlinearity as a potential non-invasive means of structural system assessment from output-only condition remains a challenging problem. In this study, the Delay Vector Variance (DVV) method is used for full scale testing of both pseudo-dynamic and dynamic responses of two bridges, in order to study the degree of nonlinearity of their measured response signals. The DVV detects the presence of determinism and nonlinearity in a time series and is based upon the examination of local predictability of a signal. The pseudo-dynamic data is obtained from a concrete bridge during repair while the dynamic data is obtained from a steel railway bridge traversed by a train. We show that DVV is promising as a marker in establishing the degree to which a change in the signal nonlinearity reflects the change in the real behaviour of a structure. It is also useful in establishing the sensitivity of instruments or sensors deployed to monitor such changes.
      302Scopus© Citations 9