Juan Francisco Carbonell-Márquez

Dynamic magnification factors of SDOF oscillators under harmonic loading

Abstract The magnification factor for the steady-state response of a SDOF system under harmonic loading is described in many structural dynamics textbooks; the well-known analytical solution is easily obtained from the solution to the damped equation of motion for harmonic loading. The complete and steady-state solutions can differ significantly. An analytical expression for the maximum response to the complete solution (steady state plus transient) remains elusive; however, a simple analytical expression is identified herein for the undamped case. Differences in the magnification factors obtained for the two solutions are discussed.

Efficient Decentralized Data Aggregation in Wireless Smart Sensor Networks

Smart sensors have been recognized as a promising technology with the potential to overcome many of the inherent difficulties and limitations associated with traditional wired structural health monitoring (SHM) systems. The unique features offered by smart sensors, including wireless communication, on-board computation, and cost effectiveness, enable deployment of the dense array of sensors that are needed for monitoring of large-scale civil infrastructure. Despite the many advances in smart sensor technologies, power consumption is still considered as one of the most important challenges that should be addressed for the smart sensors to be more widely adopted in SHM applications. Data communication, the most significant source of the power consumption, can be reduced by appropriately selecting data processing schemes and the related network topology. This paper presents a new decentralized data aggregation approach for system identification based on the Random Decrement Technique (RDT). Following a brief overview of the RDT, which is an output-only system identification approach, a decentralized hierarchical approach is described and shown to be suitable for implementation in the intrinsically distributed computing environment found in wireless smart sensor networks (WSSNs). RDT-based decentralized data aggregation is then implemented on the Imote2 smart sensor platform based on the Illinois Structural Health Monitoring Project (ISHMP) Services Toolsuite. Finally, the efficacy of the RDT method is demonstrated experimentally in terms of the required data communication and the accuracy of identified dynamic properties.