PSI - Issue 64

Vera Rillo et al. / Procedia Structural Integrity 64 (2024) 700–707 Rillo et al./ Structural Integrity Procedia 00 (2019) 000 – 000

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1. Introduction Nowadays, it is well known the importance to evaluate the condition of the structure without interrupting its operations and also plan maintenance actions. Traditionally, the evaluation of the condition of civil engineering structures has been carried out through periodically visual inspections. The latter has the advantage to be low cost and simply but it has the disadvantage to be dependent by the experience of the inspector and not able to provide information about the evolution of the condition of the system. For these reasons, the structural health monitoring (SHM) has became very important. However, the main critical issue of the structural health monitoring (SHM) system is the deployment cost. A possible way to reduce the cost of the SHM system is offered by the optimization of sensor placement in order to reduce the number of sensors. Many Optimal Sensor Placement (OSP) techniques have been used in SHM applications (Yi et al., 2011; Flynn & Todd, 2010) especially for modal identification of bridges or buildings (He et al., 2014). A systematic review can be found in Hassani & Dackermann (2023). This paper presents the design of a dynamic monitoring system layout for a recently constructed bridge, situated in Benevento (Italy), for which the authors are deploying novel, cost-effective prototype sensors for continuous bridge testing and monitoring over a one-year period. The main aim of the present paper is the design of the best sensors layout to let the future monitoring system gather the most effective information from in-situ monitoring to detect the health state. Designing an effective Structural Health Monitoring (SHM) system necessitates informed decisions regarding numerous system specifications, encompassing sensor type, quantity, placement, as well as data transfer, storage, and analysis methodologies. Consequently, in the layout design process, the imperative for obtaining precise and authentic data must be balanced against considerations such as sensor installation and management costs, alongside the imperative to mitigate excessive data accumulation. The optimal solution is attainable through the application of advanced sensor placement techniques, OSP based on modal displacements derived from Finite Element (FE) models. Well-known OPS techniques available in literature and improved by other researchers (Chioccarelli et al. 2024) are applied in the paper to derive the best sensors layout, however the novelty of the methodology lies in the choice as an optimal criterion of the Modal Assurance Criterion (MAC) between the exact and interpolated mode shapes implemented in MATLAB (2022). 2. Optimal sensor placement techniques Optimal Sensor Placement (OSP) is a methodology utilized in the field of structural monitoring to determine the ideal arrangement of sensors on a structure in order to achieve the best data acquisition and insights into structural behavior. Among the available methods, the most commonly used ones include: • EFI- Effective Independence Method that is an iterative method (Kammer, 1991) based on the Fisher matrix (FIM); the efficiency index (EFI) is reported in equation (1):       ( )       i i i i T i i i FIM EFI          =   = − − 1 1 (1) • EVP- Eigenvalue Vector Product (Yang et al., 2022) that calculates the product of eigenvector elements to derive sensor locations from N modes; the EVP of the i th DOF can be calculated as in equation (2):  = = N j ij i EVP 1  (2)

• ADPR-Average Driving Point Method (Chang & Pakzad, 2014) where the contribution of the i th sensor can be calculated as in equation (3) :