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)

Filippo Biondi, Pia Addabbo, Carmine Clemente, Danilo Orlando

Research output: Contribution to conferencePaper

Abstract

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 space borne 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.
Original languageEnglish
Number of pages5
Publication statusAccepted/In press - 31 Jan 2020
EventEuropean Synthetic Aperture Radar Conference 2021 -
Duration: 1 Apr 2021 → …

Conference

ConferenceEuropean Synthetic Aperture Radar Conference 2021
Period1/04/21 → …

Keywords

  • early warning system
  • synthetic aperture radar
  • infrastructure fault detection

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