Structural Health Monitoring for Maintaining Aging Civil Infrastructure

Maintaining aging civil infrastructure poses a significant challenge across the world. As structures age, their degradation increases requiring more complex and frequent maintenance to ensure structure integrity. This combined with the requirement to extend operational life and prolong the operational capabilities of infrastructure all while ensuring uptime poses significant challenges in infrastructure management.

Therefore, there is a demand for intelligent monitoring of the structures to direct, schedule and predict maintenance programs. MISTRAS Group Ltd. are a world-leader in asset management and monitors numerous large assets and structures throughout the world using Acoustic Emission (AE).

AE is the spontaneous release of a stress wave that propagates through a structure when damage occurs. By mounting sensors on a structure, the source of the AE can be located and monitored for its activity. In practice however this presents a real challenge due to AE originating from other acoustic sources such as rubbing from movement within the structure, traffic noise and the undertaking of maintenance operations.

Although methods exist that work to differentiate acoustic source mechanisms, these have short comings and often require the features of the different AE sources to be known. Furthermore, the methodology that is used has not changed for over thirty years. Therefore, there is a requirement to develop an improved signal acquisition and data analysis approach to better acquire AE data, analyse the data and correlate the AE signals with the extent of the developing damage.

This project will require the student to:

Research and gain understanding of the AE acquisition, signal processing and state-of-the-art data processing approaches Investigate artificial intelligence (AI) methods for signal decomposition

Explore statistical methods for determining the occurrence of AE transients, working both in the time and frequency domains Review approaches for applying developed methodologies in state-of-the-art edge processing technologies Plan and conduct laboratory investigations to gather data under realistic conditions

Apply methodologies developed in the laboratory to data gathered from real assets Explore methods, such as acoustic tomography, for correlating and quantifying the extent of the monitored damage