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ItemInternet of Things for Structural Health MonitoringSRIDHARA RAO, A ; Gubbi, J ; Ngo, T ; Mendis, P ; Palaniswami, M ; Epaarachchi, A ; Chanaka Kahandawa, G (CRC Press, 2016-05)The Internet revolution led to the interconnection between people at an unprecedented scale and pace. The ability of the sensor networks to send data over the Internet further enhanced the scope and usage of the sensor networks. The Internet uses unique address to identify the devices connected to the network. Structural Health Monitoring (SHM) implies monitoring of the state of the structures through sensor networks in an online mode and are pertinent to aircraft and buildings. SHM can be further divided into two categories: global health monitoring and local health monitoring. Continuous online SHM would be an ideal solution. SHM is performed by using acoustic sensors, ultrasonic sensors, strain gauges, optical fibers, and so on. Video cameras can also be used for SHM. SHM can be achieved in real-time and rich analytics. With the advent of smart sensors—sensors with programmable microprocessors, memory, and processing—has reduced load of central data processing, communication overhead while proving continuous SHM status.
ItemStructural Health Monitoring of Bridges Using Advanced Non-destructive Testing TechniqueMaizuar, M ; Zhang, L ; Miramini, S ; Mendis, P ; Duffield, C ; Wang, CM ; Ho, JCM ; Kitipornchai, S (Springer, Singapore, 2020-01-01)This paper presents an integrated framework for structural health monitoring of bridges by using advanced non-destructive testing (NDT) technique in conjunction with computational modelling. First, the structural characteristics of the Eltham Trestle Bridge under train loading were monitored using the combination of the 3D optical measurement system and IBIS-S. The results demonstrate that, in conjunction with computational modelling, the NDT can capture the structural health conditions of the bridge by analysing the natural frequencies and deformation profiles of the critical members of the bridges. Then, the developed framework also takes into account the impact of extreme events (e.g. truck impacts and earthquakes) by using a reliability-based model. Finally, using the Montague Street Bridge as a case study, it shows that proposed framework has the capability of predicting the residual life of a bridge subject to both progressive deterioration and extreme events throughout its service life.