Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/9954
Title: Optimisation of multi-type sensor placement for SHM based on application demands
Authors: Soman, Rohan N. 
Onoufriou, Toula 
Votsis, Renos 
Chrysostomou, Christis 
Kyriakides, Marios 
metadata.dc.contributor.other: Ονουφρίου, Τούλα
Βότσης, Ρένος
Χρυσοστόμου, Κρίστης
Κυριακίδης, Μάριος
Major Field of Science: Engineering and Technology
Field Category: Civil Engineering
Keywords: GA;Long span bridge;Modal clarity index;Modal identification;Mode shape expansion;Sensor placement optimisation
Issue Date: 2013
Source: 36th International Association for Bridge and Structural Engineering Symposium on Long Span Bridges and Roofs - Development, Design and Implementation; Kolkata; India; 24 September 2013 through 27 September 2013
Abstract: The research presents a multi-objective optimisation problem for a multi-type sensor placement for Structural Health Monitoring (SHM) on a long span bridge. The problem is formulated for simultaneous placement of strain sensors and accelerometers (heterogeneous network) based on the application demands for SHM system. The primary demands for SHM are Modal Identification (MI) and Accurate Mode Shape Expansion (AMSE). The optimisation problem is solved through the use of Integer Genetic Algorithm (GA) to maximise a common metric to ensure adequate MI and AMSE. The performance of the joint optimisation problem solved by GA is compared with other established methods for homogenous sensor placement. The results indicate that the use of a multi-type sensor system improves the quality of SHM and the use of GA improves the overall quality of the sensor placement compared to other methods for optimisation of sensor placement.
URI: https://hdl.handle.net/20.500.14279/9954
ISBN: 978-385748128-4
Rights: ©IABSE
Type: Conference Papers
Affiliation : Cyprus University of Technology 
Publication Type: Peer Reviewed
Appears in Collections:Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation

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