Multi-Monostatic Interferometric Radar with Radar Link for Bridge Monitoring

In recent years, interferometric radars have been extensively used as sensors for static and dynamic monitoring of bridges. Generally speaking, a radar can only detect the displacement component along its view direction. As the movement of a real bridge or a large structure can be rather complex, this limitation can be a significant drawback in engineering practice. In order toovercome this limitation, in this article, a multi-monostatic interferometric radar with radio link is proposed. This radar is able to detect a second component of displacement using a transponder. The transponder is connected to the radar through a radio link. The radio link allows the installation of the transponder far away from the radar, and even in the opposite direction. The equipment is based on a MIMO radar, two transceivers for the radio link, and a transponder. The transceivers and the transponder are essentially two antennas and an amplifier system. The equipment is experimentally tested in controlled scenarios and in the case study of Indiano Bridge, Florence, Italy.

Processing Strategy and Comparative Performance of Different Mobile LiDAR System Grades for Bridge Monitoring: A Case Study

Collecting precise as-built data is essential for tracking construction progress. Three-dimensional models generated from such data capture the as-is conditions of the structures, providing valuable information for monitoring existing infrastructure over time. As-built data can be acquired using a wide range of remote sensing technologies, among which mobile LiDAR is gaining increasing attention due to its ability to collect high-resolution data over a relatively large area in a short time. The quality of mobile LiDAR data depends not only on the grade of onboard LiDAR scanners but also on the accuracy of direct georeferencing information and system calibration. Consequently, millimeter-level accuracy is difficult to achieve. In this study, the performance of mapping-grade and surveying-grade mobile LiDAR systems for bridge monitoring is evaluated against static laser scanners. Field surveys were conducted over a concrete bridge where grinding was required to achieve desired smoothness. A semi-automated, feature-based fine registration strategy is proposed to compensate for the impact of georeferencing and system calibration errors on mobile LiDAR data. Bridge deck thickness is evaluated using surface segments to minimize the impact of inherent noise in the point cloud. The results show that the two grades of mobile LiDAR delivered thickness estimates that are in agreement with those derived from static laser scanning in the 1 cm range. The mobile LiDAR data acquisition took roughly five minutes without having a significant impact on traffic, while the static laser scanning required more than three hours.

Using Fiber Optic Sensors for Bridge Monitoring

This paper presents the data obtained from monitoring a steel Struss bridge using Fiber Bragg Grating (FBG) sensors before and after a proposed repair for a crack propagation in the end plates. This paper details the operating mechanism behind the FBG sensors and advantages of using FBG sensors over resistive foil strain gauges for bridge structural health monitoring and also details how cracks on the outer web’s end plate originated and then provides a step-by-step guide to the completed repair. This technology can be use in other practical applications where structural health monitoring is needed.

Development of Smart Sensing Technology Approaches in Structural Health Monitoring of Bridge Structures

In recent years, immense development in Structural Health Monitoring (SHM) of bridges helps address the life span and reliability of bridge structure at contrasting phases of their service life. This article provides a detailed understanding of bridge monitoring, and it focuses on sensors utilized and all kinds of damage detection (strain, displacement, acceleration, and temperature) according to bridge nature (scour, suspender failure, disconnection of bolt and cables, etc.) and environmental degradation under static and dynamic loading. This paper presents information about various methods, approaches, case studies, advanced technologies, real-time experiments, stimulated models, data acquisition, and predictive analysis. Future scope and research also discussed the implementation of SHM in bridges. The main aim of this research is to assist researchers in better understanding the monitoring mechanism in bridges.