Bridges are fundamental components of modern communities, playing a crucial role in trans-portation infrastructure by connecting people and facilitating trade. In recent years, many bridges have been equipped with Structural Health Monitoring (SHM) systems, which collect vast amounts of data to monitor the structural integrity of bridges in real-time, with the pri-mary objective of detecting issues before they become critical. Consequently, it is imperative to develop new methods and techniques for effectively managing and analysing this large vol-ume of data to enhance decision-making and maintenance strategies in a multi-risk context (structural, hydro-geological). To address these challenges an innovative multi-risk informed ICT platform is developed by the multi-level approach of the Italian Guidelines. This Platform is a significant advancement in the field, integrating various data sources and analytical methods to offer comprehensive insights into bridge health. The ICT platform is structured as follows: (i) territorial level, which involves compiling detailed information about the struc-tural components of bridges, including materials, structural type, construction methods, and geometry. It also assesses interactions with regional risk factors such as seismic activity, hy-drology, and geotechnical conditions; (ii) inspection level, where data is gathered about the inspected defects in structural components and any interfering phenomena, providing a clear picture of the bridge's current condition; (iii) informed data-driven SHM level, representing a cutting-edge approach to anomaly detection that relies solely on data collected from sensors. The system is designed for informed decision-making, utilising reference damage scenarios based on structural type, construction material, environmental and operational contexts; (iv) model-based SHM level, where the Platform combines information concerning structural be-haviour from theoretical models with data from SHM systems. This hybrid approach enhanc-es accuracy by integrating predictive modelling with real-time monitoring; (v) data fusion level, where the Platform combines all the information gathered from the previous steps in a probabilistic manner, enabling robust and informed decision-making. Integrating diverse da-ta sets ensures a comprehensive understanding of bridge health and risk factors. The pro-posed ICT platform represents a revolutionary step forward in bridge health monitoring, offering unprecedented data integration and risk assessment capabilities. A real case study will be included to demonstrate the absolute innovation of this approach, showcasing the Platform's ability to handle bridge maintenance and safety strategies.
AN ICT MULTI-RISK INFORMED PLATFORM FOR THE MANAGEMENT OF BRIDGES
Michele Morici;Laura Gioiella;Andrea Dall’Asta;
2025-01-01
Abstract
Bridges are fundamental components of modern communities, playing a crucial role in trans-portation infrastructure by connecting people and facilitating trade. In recent years, many bridges have been equipped with Structural Health Monitoring (SHM) systems, which collect vast amounts of data to monitor the structural integrity of bridges in real-time, with the pri-mary objective of detecting issues before they become critical. Consequently, it is imperative to develop new methods and techniques for effectively managing and analysing this large vol-ume of data to enhance decision-making and maintenance strategies in a multi-risk context (structural, hydro-geological). To address these challenges an innovative multi-risk informed ICT platform is developed by the multi-level approach of the Italian Guidelines. This Platform is a significant advancement in the field, integrating various data sources and analytical methods to offer comprehensive insights into bridge health. The ICT platform is structured as follows: (i) territorial level, which involves compiling detailed information about the struc-tural components of bridges, including materials, structural type, construction methods, and geometry. It also assesses interactions with regional risk factors such as seismic activity, hy-drology, and geotechnical conditions; (ii) inspection level, where data is gathered about the inspected defects in structural components and any interfering phenomena, providing a clear picture of the bridge's current condition; (iii) informed data-driven SHM level, representing a cutting-edge approach to anomaly detection that relies solely on data collected from sensors. The system is designed for informed decision-making, utilising reference damage scenarios based on structural type, construction material, environmental and operational contexts; (iv) model-based SHM level, where the Platform combines information concerning structural be-haviour from theoretical models with data from SHM systems. This hybrid approach enhanc-es accuracy by integrating predictive modelling with real-time monitoring; (v) data fusion level, where the Platform combines all the information gathered from the previous steps in a probabilistic manner, enabling robust and informed decision-making. Integrating diverse da-ta sets ensures a comprehensive understanding of bridge health and risk factors. The pro-posed ICT platform represents a revolutionary step forward in bridge health monitoring, offering unprecedented data integration and risk assessment capabilities. A real case study will be included to demonstrate the absolute innovation of this approach, showcasing the Platform's ability to handle bridge maintenance and safety strategies.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
