Vision-Based Monitoring and Frequency analysis for Structural beams

Abstract

Real-time assessment presents a significant challenge in Structural Health Monitoring (SHM), where the timely detection of structural defects and determination of in-service strength are crucial. In the developing field of SHM, the integration of diverse technologies is becoming increasingly essential, especially given the different challenges brought on by climate change and the complex nature of civil engineering structures. Traditional approaches, such as vibration analysis, acoustic emission, ultrasonic testing, and thermal imaging, despite their widespread use, face challenges in accurately pinpointing structural damage due to their reliance on a single technology. Meanwhile, dynamic response measurements of structures present a promising method for gaining internal insights into structures. Additionally, the advent of Unmanned Aerial Vehicles (UAVs) has enhanced the viability of vision-based techniques, such as digital image correlation (DIC), for surface assessment. This paper investigates damage in lightly reinforced concrete beams using a dual-technique approach that exploits the strengths of the DIC technique and frequency measurement technique, aiming to enhance the detection and analysis of damage in reinforced concrete beams. This integration signifies a step forward in SHM especially if integrated with other advancements leading to a better monitoring of structures.