AbstractNonlinear imaging techniques have recently emerged which have the potential to detect cracks at a much earlier stage than was previously possible. This thesis describes a group of novel nonlinear phased array imaging techniques for non-destructive testing. In contrast to conventional nonlinear techniques, these techniques have the potential to reliably image tightly closed cracks and quantify their nonlinearities without bespoke and complicated setups. The underlying engineering science, the experimental procedure and the fundamental findings for each technique are discussed.
The nonlinear ultrasonic diffuse energy imaging (NUI) technique was recently proposed to allow nonlinearity to be isolated and located in an image. Its performance for monitoring fatigue crack growth is first investigated. The results suggest that NUI is more sensitive than conventional ultrasonic imaging to the microscale changes occurring at the early stages of failure. The potential for NUI to deliver accurate sizing of fatigue cracks is also demonstrated. In addition, an investigation into the performance of NUI by optimising the key parameters with the proposed methodology is presented. The results suggest that the performance of NUI significantly depends on the parameters and the adaptive optimisation methods can be used to select the optimum parameters and expand the applications of NUI for different structures and materials.
A family of nonlinear coherent imaging (NCI) techniques are explored and developed based on the coherently scattered amplitude subtraction at the fundamental or subharmonic frequency of two focusing modes. The novel nonlinear phenomena in the form of phase change or amplitude loss are investigated and exploited to yield two separate NCI metrics (phase and amplitude). The NCI methods using pulse-echo and pitch-catch configurations are then examined on a broad range of fatigue cracks grown in multiple samples. The results suggest that the NCI techniques, in conjunction with the proposed noise compensation approach, significantly enhance selectivity, sensitivity and practicality of crack detection and characterisation.
|Date of Award||23 Jan 2019|
|Supervisor||Bruce W Drinkwater (Supervisor)|