FRAMEWORK FOR A PRACTICAL AND COST–EFFECTIVE IOT–ENHANCED STRUCTURAL HEALTH MONITORING WITH DIGITAL TWINNING

Abstract

The South African railway and civil infrastructure are critical for passenger and freight transit, connecting major cities and ports. Despite state owned investment efforts aimed at maintaining and improving existing infrastructure, it continues to deteriorate rapidly. This degradation negatively impacts the commercial sector and diminishes the country's global economic competitiveness. With increasing traffic volumes to meet escalating transport demands, effective condition assessment and maintenance of existing civil infrastructure are paramount. Currently, the industry primarily relies on visual inspections, which are useful for identifying visible issues but are subjective, inconsistent, and unable to detect internal problems. Other non-destructive methods exist but are often costly, labour intensive, complex and disruptive to operations. These challenges highlight the urgent need for advanced, automated, and timely monitoring approaches to ensure infrastructure integrity, support economic growth, and promote infrastructure sustainability. The Fourth Industrial Revolution has introduced advanced smart technologies and data driven solutions, significantly impacting civil infrastructure management. A critical area within this development is Structural Health Monitoring (SHM), which provides stakeholders with valuable insights into infrastructure conditions. The integration of sensor systems, the Internet of Things (IoT), and advanced data processing has led to the concept of Digital Twins (DTs). DTs offer dynamic, real time simulations of structures, aiding in proactive asset management by predicting potential risks and formulating maintenance strategies. However, current DT based SHM systems often involve prohibitive costs, complex data processing, and demanding computing systems and power, making them impractical and financially unfeasible, especially for small scale implementations. Additionally, many existing systems lack user-friendly interfaces and interpretability, reducing user confidence and comprehension. This study aims to establish a practical and cost effective SHM framework enhanced by DT technology for civil infrastructure. The primary objectives include demonstrating that affordable contact and non contact sensors can provide precise and reliable results for DT enhanced SHM frameworks, proving that cost effective microcomputing hardware with IoT capability can enable efficient, near real time data transmission from physical structures to digital models, and developing a practical, comparatively simple numerical DT model to simulate the mechanical behaviour of Reinforced Concrete (RC) structures. The experimental study performed for the needs of this research work successfully developed a DT based SHM prototype capable of digitally replicating the mechanical response of a RC beam. It introduced novel low cost sensors, a potentiometer contact sensor, and an Infrared (IR) non contact sensor. The potentiometer sensor showed excellent accuracy and stability, making it highly suitable for precise measurements, while the IR sensor, despite higher noise levels, proved effective for submillimetre displacement detection. The hardware system incorporated these innovative low cost sensors and an IoT enabled microcontroller, together with a developed software program named “ReConTwin”, featured an interactive, automated post processing system for near real time model updates, analysis, and damage diagnosis. The calibrated DT accurately estimated imposed loads and predicted strain and crack widths, providing reliable insights into the monitored beam’s structural behaviour. The user friendly design and compatibility with standard commercial computers significantly enhance the accessibility and feasibility of the proposed DT SHM framework for widespread adoption. The study demonstrates the potential of practical and affordable DT enhanced SHM systems, making them more accessible for real world civil infrastructure applications.