Defects In Aerospace Structures Research Articles

Design of a guided wave absorber for Structural Health Monitoring system development

The objective of this paper is to present and validate an efficient guided wave absorber for increased sensitivity of structural health monitoring systems based on guided wave, and especially for inspection close to structure boundaries. Such an absorber would also help with systematic characterization of guided waves interaction with defects in aerospace structures. A complete numerical parametric study is undertaken using the power flow in the structure to determine the reflection and transmission coefficients and thus the dissipated energy by the absorber. Starting with the determination of the geometry and dimensions using Finite Element Modelling (FEM), and following with an investigation on the influence of the absorber's mechanical properties, a practical and efficient absorber is identified. The dimensions of the developed absorber are minimized to provide optimal results for frequencies ranging from 50kHz to 500kHz for an incident A0 mode. The resulting right triangle cross section absorber of Teflon has been machined and tested experimentally using a piezoelectric wave generator on one side of the absorber, and a tri-dimensional laser Doppler vibrometer (3D-LDV) to measure the transmitted wave on the other side. Using a spatial Fourier transform approach for the determination of the experimental reflection and transmission coefficients, the numerical results have been successfully validated.

Feature extraction and soft computing methods for aerospace structure defect classification

This study concerns the effectiveness of several techniques and methods of signals processing and data interpretation for the diagnosis of aerospace structure defects. This is done by applying different known feature extraction methods, in addition to a new CBIR-based one; and some soft computing techniques including a recent HPC parallel implementation of the U-BRAIN learning algorithm on Non Destructive Testing data. The performance of the resulting detection systems are measured in terms of Accuracy, Sensitivity, Specificity, and Precision. Their effectiveness is evaluated by the Matthews correlation, the Area Under Curve (AUC), and the F-Measure. Several experiments are performed on a standard dataset of eddy current signal samples for aircraft structures. Our experimental results evidence that the key to a successful defect classifier is the feature extraction method – namely the novel CBIR-based one outperforms all the competitors – and they illustrate the greater effectiveness of the U-BRAIN algorithm and the MLP neural network among the soft computing methods in this kind of application.

English

The method of Lamb waves to detect defects in aerospace structures is already known in research environments for its benefits, using an inexpensive equipment. The major benefits are: accurate determination of location and size of the defects in material and the fact that it is a non destructive method. For experiments are used aluminum plates that are willing piezoelectric exciters as follows: a piezoelectric actuator placed on a point on the plate will excite that point and the signal will be received by a piezoelectric receiver placed on another point from the plate. By interpreting the shape, phase and amplitude of the received signal we can determine the shape and location of the defect. The excitation signal frequency should be previously known by determining the amplitude in a frequency band set between 10-800 kHz, for the plate without defects, which is called the tuning procedure. Due to the fact that the structures will work also on flight condition temperature as on high altitude or in space, it is neccesary to check how these extremelly low temperatures influence the defect detection. For this purpose the first step is to determine how the temperature variation affects the tunning results. As preliminary study the first step of the tunning procedure has been performed at different low temperature down to - 70 0 C.