AI-Enhanced IoT System for Assessing Bridge Deflection in Drive-By Conditions.

The increasing traffic on roads poses a significant challenge to the structural integrity of bridges and viaducts. Indirect structural monitoring offers a cost-effective and efficient solution for monitoring multiple infrastructures. The presented work aims to explore new sensing strategies based on digital MEMS sensors integrated into an intelligent IoT infrastructure to predict the bridge deflection behaviour for indirect Bridge Structural Health Monitoring purposes.

A Damage Detection Approach for Axially Loaded Beam-like Structures Based on Gaussian Mixture Model.

Axially loaded beam-like structures represent a challenging case study for unsupervised learning vibration-based damage detection. Under real environmental and operational conditions, changes in axial load cause changes in the characteristics of the dynamic response that are significantly greater than those due to damage at an early stage. In previous works, the authors proposed the adoption of a multivariate damage feature composed of eigenfrequencies of multiple vibration modes.

Combined Use of Cointegration Analysis and Robust Outlier Statistics to Improve Damage Detection in Real-World Structures.

Due to the need for controlling many ageing and complex structures, structural health monitoring (SHM) has become increasingly common over the past few decades. However, one of the main limitations for the implementation of continuous monitoring systems in real-world structures is the effect that benign influences, such as environmental and operational variations (EOVs), have on damage sensitive features. These fluctuations may mask malign changes caused by structural damages, resulting in false structural condition assessment.

Low-Cost and High-Performance Solution for Positioning and Monitoring of Large Structures.

Systems for accurate attitude and position monitoring of large structures, such as bridges, tunnels, and offshore platforms are changing in recent years thanks to the exploitation of sensors based on Micro-ElectroMechanical Systems (MEMS) as an Inertial Measurement Unit (IMU). Currently adopted solutions are, in fact, mainly based on fiber optic sensors (characterized by high performance in attitude estimation to the detriment of relevant costs large volumes and heavy weights) and integrated with a Global Position System (GPS) capable of providing low-frequency or single-update information about the position. To provide a cost-effective alternative and overcome the limitations in terms of dimensions and position update frequency, a suitable solution and a corresponding prototype, exhibiting performance very close to those of the traditional solutions, are presented and described hereinafter.

Automatic Detection of Real Damage in Operating Tie-Rods.

Many researchers have proposed vibration-based damage-detection approaches for continuous structural health monitoring. Translation to real applications is not always straightforward because the proposed methods have mostly been developed and validated in controlled environments, and they have not proven to be effective in detecting real damage when considering real scenarios in which environmental and operational variations are not controlled. This work was aimed to develop a fully-automated strategy to detect damage in operating tie-rods that only requires one sensor and that can be carried out without knowledge of physical variables, e.