A New Paradigm to Observe Early Warning Faults of Critical Infrastructures by Micro-Motion Estimation from Satellite SAR Observations. Application to Pre-Collapse Damage Assessment of the Morandi Bridge in Genoa (Italy)
Konferenz: EUSAR 2021 - 13th European Conference on Synthetic Aperture Radar
29.03.2021 - 01.04.2021 in online
Tagungsband: EUSAR 2021
Seiten: 5Sprache: EnglischTyp: PDF
Autoren:
Biondi, Filippo (University of L’Aquila, Monteluco di Roio, Italy)
Addabbo, Pia (Università degli Studi “Giustino Fortunato”, Benevento, Italy)
Clemente, Carmine (University of Strathclyde, Department of Electronic and Electrical Engineering, Glasgow, UK)
Orlando, Danilo (Università degli Studi “Niccolò Cusano”, Engineering Faculty, Roma, Italy)
Inhalt:
Damage in civil engineering structures can be represented by a reduction of the structural bearing capacity during their service period. This reduction is usually caused by degradation of materials, structural components or connections due to environmental phenomena leading to excessive loading effects. Typical damages in civil engineering structures include cracks, fatigue, steel corrosion, concrete spalls, scour and deterioration. Undetected damage can lead to structural failure causing loss of human life. Considering these problems it is necessary to detect early damage within a structure, in order to undertake appropriate repairs as early as possible. The main issue of early warning infrastructure fault detection is that expensive in-situ distributed monitoring sensor networks has to be installed. This research propose a new global infrastructure monitoring paradigm using micro-motion (m-m) estimation of critical sites, from spaceborne Synthetic Aperture Radar (SAR) data, in this case. In order to apply this method for damage detection, an approach using modal proprieties is applied. m-m is processed to extract modal features such as natural frequencies and mode shapes. The case study of the Morandi bridge (Polcevera Viaduct) in Genoa (Italy) is considered in this paper and the proposed method shows abnormal vibrational modes during the period before the collapse of the bridge.