AbstractOver the last decade, acoustic emission localisation has become an important tool for structural health monitoring and non-destructive inspection applications, particularly for the aerospace field. Acoustic source localisation consists of identifying in space and time the source of acoustic waves, by recording the propagating acoustic signals using several receiving sensors. In this work, the impact between a foreign object and a component was considered as the source of acoustic emissions.
The main topic of this thesis was, therefore, the creation of structural health monitoring systems for the localisation of impact events and the reconstruction of impact loads on both isotropic and composite aerospace components. Innovative acoustic emission identification methods and algorithms were here developed and presented. These include: (i) the linearisation of the nonlinear system of equations for the localisation of impact events, (ii) the creation of a new signal power algorithm for impact localisation, (iii) the development of a novel ultrasonic data interpolation algorithm by using hierarchical radial basis functions and (iv) the creation of the first impact load reconstruction algorithm using time reversal, which does not require prior information of the mechanical properties of the host component. Furthermore, some of the presented techniques were also combined in order to provide a proof of concept for the estimation of direction and velocity of space debris by using a small composite detector.
The proposed algorithms and methods were validated by performing experimental tests on different metallic and composite aerospace structures, as plates and real wings. The considered structural components were arranged with different typologies and configurations of acoustic emission transducers, either fixed to the specimen surface or embedded into the structure. These tests demonstrated that results were achieved with a high level of accuracy, identified by a negligible difference (often less than 2-3%) between true and calculated values/functions. Therefore, the proposed structural health monitoring algorithms presented in this research work have the potential to provide a reliable and sensitive tool for the in-service inspection of aerospace components.
|Date of Award||20 Nov 2019|
|Supervisor||Michele Meo (Supervisor), Fulvio Pinto (Supervisor) & Francesco Ciampa (Supervisor)|