P3P: a software suite for autonomous SHM of bridge networks

This paper presents the development of a new software code for the fully autonomous management of permanent integrated Structural Health Monitoring (SHM) systems installed in highway bridge structures. The code was developed within the framework of a research project funded by Anas S.p.A., the largest public infrastructure manager in Italy. The software program includes all the necessary steps to conduct SHM within the statistical pattern recognition paradigm, including automated dynamic identification, modal tracking, filtering of environmental effects, and damage detection through novelty analysis. Additionally, the software suite includes specific modules for processing and analysis of seismic events and structural reliability analysis of bridges, as well as specific functionalities for span-wise identification of long multi-span bridges. Moreover, a novel automated density-based tracking algorithm is developed. The potential of P3P is illustrated through two real application case studies: (i) a long multi-span bridge, the Trigno V Bridge in Italy; and (ii) the Z-24 Bridge benchmark. This work demonstrates the effectiveness of the developed code for handling large monitoring databases within the framework of SHM as a statistical pattern recognition, and currently P3P is in phase of being applied by Anas S.p.A for the management of a large number of bridges of the Italian roadway system.