000005020 001__ 5020
000005020 005__ 20141120140004.0
000005020 04107 $$aeng
000005020 046__ $$k2008-06-25
000005020 100__ $$aArangio, S.
000005020 24500 $$aSLOW AND HIGH SPEED STRUCTURAL MONITORING OF SUSPENSION BRIDGES

000005020 24630 $$n4.$$pProceedings of the 4th International ASRANet Colloquium
000005020 260__ $$bASRANet Ltd., 2008
000005020 506__ $$arestricted
000005020 520__ $$2eng$$aComplex structural systems like long suspension bridges, are exposed to various external loads such as traffic-induced and wind-induced during their service life. These structures may deteriorate and degrade with time, something that may lead to structural failures causing costly repairs and, even, loss of human lives. To ensure safety and to minimize financial loss, damage detection becomes important so that remedial works can be carried out as early as possible. Structural health monitoring assumes an important role in conjunction with the damage assessment and the safety evaluation of the structure. In the case of large structures the monitoring process should be planned since the design phase and should be carried out continuously during the entire life, assessing structural health and performance under in-service conditions. In continuous monitoring it is important to differentiate between slow-speed and high-speed monitoring because each category would require different equipment and processing techniques and provide different information. The slow-speed monitoring regime is suitable for long term tracking of natural environmental loads, such as wind, and to capture their influence on the structural and operational conditions. A high-speed data acquisition regime is needed for capturing high-speed events, such as traffic loads. In this work, the technologies related to these kinds of regimes and the information they can provide are discussed. The various concepts are then applied to the continuous monitoring of a long suspension bridge. In particular, a damage detection strategy, based on the analysis of the response time history of the structure using neural networks, is proposed. This strategy allows to detect the occurrence of damage and to identify the damaged portion of the deck. The results obtained using responses from high-speed and slow-speed monitoring systems are compared.

000005020 540__ $$aText je chráněný podle autorského zákona č. 121/2000 Sb.
000005020 653__ $$a

000005020 7112_ $$a4th International ASRANet Colloquium$$cAthens (GR)$$d2008-06-25 / 2008-06-27$$gASRANet4
000005020 720__ $$aArangio, S.$$iGkoumas, K.$$iBontempi, F.
000005020 8560_ $$ffischerc@itam.cas.cz
000005020 8564_ $$s216010$$uhttps://invenio.itam.cas.cz/record/5020/files/063_Gkoumas,_K.pdf$$yOriginal version of the author's contribution as presented on CD, paper No. 63.
000005020 962__ $$r4967
000005020 980__ $$aPAPER