Optimal Positioning Solutions in Remote Sensing Technologies for Structural Health Monitoring

Structural Health Monitoring (SHM) is the process of implementing a strategy for damage detection of structures and infrastructures, with several application to aerospace, civil or mechanical engineering. An important activity for SHM is the so-called Optimal Sensor Placement (OSP), that aims to customize the monitoring system over a target structure: it allows to identify the optimal positions of the sensors, maximizing the spatial resolution of the detected quantities, e.g. the vibrating modes, especially when a limited number of sensors is available to cover a spatially extended structure such as civil or aerospace systems. In this framework, an interesting and beneficial approach appears to be a multi-disciplinary one, which aims to apply Remote Sensing (RS) data to OSP. Typically, OSP strategies are based on preliminary Finite Element (FE) models of the target system, which provide an estimate of the modes of vibration from which the most informative points can be drawn. This approach presents some issues as FE models are based on surveys and on geometric and mechanical information of the different structural elements, thus for extremely extensive or complex structures this could be expensive or misleading. This thesis explores the strategy of using RS data for OSP, examining the potential of different platforms for the placement of the measuring instruments. In this approach, FE models could be replaced directly by real data, such as position and displacement (or speed or acceleration) in the base triad (longitude, latitude, and topographic height) of points of the actual structure, together with their variation over time. After a state of the art of RS principles and technology, OSP requirements have been identified, setting constraints on: georeferencing, synchronization, spatial covering, acquisitions time-gap, spatial resolution, time resolution, frequency resolution and data sensitivity. The Analytical Hierarchy Process (AHP), a multi-criteria decision support technique, is used to recognize the most suitable solution by ordering the alternatives according to an axis of preference. AHP allows to identify the main attributes (or characteristics) with the relative importance weights and to draw up a ranking of the solutions based on how well they meet the requirements with respect to the weighted attributes. The author proposes guidelines on the choice of the best solution, which is the one that best meets the requirements together with the technical-economic considerations, regarding the payload, the mission objectives, the life and operating costs, the advantages and the risks.