Structural Health Monitoring on composite structures

: (Alternative Format Thesis)

Abstract

The purpose of Structural Health Monitoring (SHM) is to provide an instantaneous diagnosis of the integrity condition of a part, component, or entire structure using sensors (embedded or not), new types of materials and improved signal processing. During operations such as manufacturing or maintenance, output data from SHM analysis are used as an economical and time saving inspection process of the structures without removing individual components; then, in case of detected damage, fixing or replacement actions are executed (taken) to restore the pristine state.

The first objective of this research work is to develop new localisation methods for impact events, with output the coordinates of the contact position. Using the Time Reversal (TR) as a reference technique, a method developed upon the RBF and aided cell identification algorithm, is proposed, aiming to improve the accuracy and reliability of the previous localisation methodology listed in the literature. Furthermore, a method based on the signal power calculation is discussed as an alternative tool for impact localisation. The second objective is the development of a baseline free method to assess the damage state of structures with real-time feedback.

Furthermore, it is described the development of an augmented reality (AR) headset for remote damage inspection during maintenance operations. The system is based on laser speckle pattern stereo vision, that aims to acquire a surface map of the inspected component to discern whether a defect or damage is affecting the structure.

In chapter 2 the wave propagation theoretical background is discussed and a review of the previous localisation and damage detection methods, illustrating the pros and disadvantages of each of them. In section 3 the proposed algorithm based on TR is in detail explained, underlining the difference with the old method, with a dedicated section on the RBF. In chapter 4 is proposed the alternative localisation algorithm based on the signal power technique, and the experimental setup used to validate his effectiveness. Chapter 5 presents the novel damage detection method, that does not require a baseline to assess the state of the monitored structure. Chapter 6 discusses a novel visual inspection method, based on a depth map from a stereo vision system, and a custom headset.

Finally, in chapter 7, the conclusion and future work.

Date of Award	29 Mar 2023
Original language	English
Awarding Institution	University of Bath
Supervisor	Michele Meo (Supervisor) & Fulvio Pinto (Supervisor)