A LCCA framework for the management of bridges based on data fusion from visual inspections and SHM systems.

Abstract

Bridges' integrity, safety and serviceability are fundamental targets that need to be ensured during the structural lifetime, owing to the crucial role that such infrastructure components play in modern communities. Recently, a particular attention is being paid to the management of bridges since many of them have reached the end of their expected service life. To this purpose, the Italian Ministry of Sustainable Mobility issued in 2020 the “Guidelines for risk classification and management, safety assessment and monitoring of bridges” that regulate visual inspections, risk assessment based on multilevel protocols and consequent monitoring and maintenance activities. In this context, structural health monitoring (SHM) systems play a fundamental role to guarantee safety and adequate performance levels. However, the synergy between visual inspections and SHM is yet to be fully understood and exploited. The main goal of this research work is to contribute to filling this gap by proposing a general probabilistic framework, based on Life‐Cycle Cost Analysis (LCCA), able to fuse information from SHM data and visual inspections, with the aim to plan over time short‐term and long‐term interventions and to optimize fund allocation by considering all the stored information.

Wireless Sensor Placement Optimization for Bridge Health Monitoring: A Critical Review

“…Integrating information from multiple wireless sensors or sources. [34,47,48] Signal reconstruction Reconstruct missing or incomplete data.…”

“…Sensor fusion methods such as sensor selection, sensor calibration, feature fusion, and decision-level fusion. [34,47,48] Quality-aware aggregation Reliability and quality of data collected from different sensors when performing aggregation.…”