Wireless structural health monitoring of cable-stayed bridge using Imote2-platformed smart sensors

Abstract

In this study, wireless structural health monitoring (SHM) system of cable-stayed bridge is developed using Imote2-platformed smart sensors. In order to achieve the objective, the following approaches are proposed. Firstly, vibrationand impedance-based SHM methods suitable for the pylon-cable-deck system in cable-stayed bridge are briefly described. Secondly, the multi-scale vibration-impedance sensor node on Imote2-platform is presented on the design of hardware components and embedded software for vibration-and impedance-based SHM. In this approach, a solarpowered energy harvesting is implemented for autonomous operation of the smart sensor node. Finally, the feasibility and practicality of the multi-scale sensor system is experimentally evaluated on a real cable-stayed bridge, Hwamyung Bridge in Korea. Successful level of wireless communication and solar-power supply for smart sensor nodes are verified. Also, vibration and impedance responses measured from the target bridge which experiences various weather conditions are examined for the robust long-term monitoring capability of the smart sensor system.

A cost effective wireless structural health monitoring network for buildings in earthquake zones

“…Autonomy is a very important aspect as it determines the capability of the system to operate continuously for a long time, in the absence of an external power supply. In particular, wireless systems is not expected to connect to external power supply, thus high autonomy can be achieved mainly by low power design of the system [12,14,16,18,21,24,25,[35][36][37][38][39].…”

Identification of Tension Force in Cable Structures Using Vibration-Based and Impedance-Based Methods in Parallel

“…In addition, the cable anchorage models were simulated and compared with experiments to verify the model's reliability and effectiveness [14][15][16]. Moreover, damage detection models were applied and combined with the impedance-based method to accurately determine the damages in various structures, such as cable-anchorage [17,18], tendon-anchorage [19][20][21], bolted connections [22], long cables [23], concrete structures [24][25][26][27][28]. Presently, the machine learning techniques were employed for the feature extraction with the impedance-based method to efficiently detect damages or cracks in structures [29,30].…”