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5th International Symposium on Sensor Science

S4: Sensors for Structures


Structural health monitoring of aerospace, civil and mechanical structures and components is becoming increasingly relevant to minimize maintenance costs and provide additional layers of safety for the users. The session will focus on the progress of existing or novel sensing concepts including synergies among sensing approaches. All sensing mechanisms including piezoelectrics, piezoresistive, electrostrictives, magnetostrictives, shape memory alloys or polymers and optical are included in this session. Experimental studies are preferred but computational approaches that include applications and experimental results are also welcome. Presentations on data fusion, networking and computing of large amounts of data that are geared towards structural health monitoring applications are also encouraged in this session.

Session Chair

Prof. Dr. Jandro L. Abot
Department of Mechanical Engineering, The Catholic University of America, USA

Progress Towards Integrated Structural Health Monitoring Using Novel Carbon Nanotube Yarn Sensors

Keynote Speakers

 

Invited Speakers

Dr. Thomas Schumacher
Civil & Environmental Engineering, Portland State University, Portland, OR, USA

Development of Self-Sensing Carbon Nanotube-Based Composites for Civil Infrastructure Applications

Worldwide, civil infrastructure systems are aging and deteriorating due to maintenance neglect, increasing traffic, and an environment that is becoming increasingly severer. In particular, bridges play a critical role in the transportation network. With limited monies available for maintenance and repair, a need exists for effective yet inexpensive solutions to strengthen and monitor bridges. This presentation provides an overview of the development of carbon nanotube (CNT)-based composites, which offer a means to strengthen and monitor a deteriorated bridge member simultaneously. CNT sensors are created by infusing a fabric, which can be structural or non-structural, with carbon nanotubes to form a piezo-resistive network. Changes in the measured resistance between electrodes, which are attached to the composite layer, have been found to directly correlate to deformations and the formation and accumulation of internal damage. The resulting novel self-sensing composites are sensitive, inexpensive, and able to adhere to almost any shape. Two particular civil infrastructure applications will be presented and discussed in detail. First, two large-scale reinforced concrete beams were strengthened with a composite layer that had an embedded sensing layer and then loaded to failure using load cycles of increasing amplitude. The objective of the second application was to increase the remaining fatigue-life of a cracked steel bridge member. For this application, ASTM E647 test specimens were rehabilitated with self-sensing composites and loaded cyclically to failure. Both applications highlight the potential of CNT-based composites in bridge rehabilitation and monitoring.

Professor Tommy Chan
School of Civil Engineering & Built Environment, Queensland University of Technology (QUT), Brisbane, Australia

Recent Advances in Using Sensors for Structural Health Monitoring for Structures

Structural Health Monitoring (SHM) involves the use of various sensing devices and ancillary systems to monitor the in-situ behaviour of a structure to assess the performance of the structure and evaluate its condition. Because of well demonstrating its effectiveness in helping reduce operational costs and increase safety and reliability, it has attracted numerous researchers working in the area for the last three decades. Structural Health Monitoring (SHM) research can be divided into three main categories: (i) system development, (ii) sensors / measurement and (iii) applications. This presentation will report the recent advances in SHM in these three categories. Under the first category, number of test-beds have been selected covering a range of civil structural systems from laboratory models (two large-scale bridge models) and four real structures (i.e. a highway bridge, one 5-star-green rated medium-rise building, and two footbridges at QUT). In the sensors/measurement category much of the recent work has been done to enhance the Fibre Bragg Grating (FBG) sensing technology. Recent developments include new FBG strain modulation methods and new FBG accelerometers using axial and/or transverse forces and vertical displacement measurements. The application category includes number of ongoing projects on developing various Damage Detection (DD) methods, e.g. correlation MSE with Multi-Layer Genetic Algorithm (ML-GA) based optimization, multi-criteria approach using combination  of natural frequencies, Modal Frequencies (MF) and Modal Strain Energies (MSE) to detect damages in bridges, buildings and dams, Correlation based method using ratio of geometric MSE and natural frequency (GMSEF), Time Domain based methods based on Auto-Regressive (AR) and Auto-Regressive Moving Average (ARMA) models, Enhanced MF for locate damage in suspension bridge main cables and hangers. Apart from DD topics, a group has been involved in developing methods to identify the effective prestress force in prestressed concrete box girder bridges by combining various Moving Load Identification (MLI) methods and Electromagnetic Ultrasonic Transducers. Besides, the use of SHM for asset management will also be discussed.

 

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