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Aircraft structural damage detection is becoming of increased importance. Technologies such as acousto-ultrasonic have been suggested for this application; however, an optimization strategy for sensor network design is required to ensure a high detection probability while minimizing sensor network mass. A methodology for optimizing acousto-ultrasonic transducer placement for adhesive disbond detection on metallic aerospace structures is presented. Experimental data sets were acquired using three-dimensional scanning laser vibrometry enabling in-plane and out-of-plane Lamb wave components to be considered. This approach employs a novel multi-sensor site strategy which is difficult to achieve with physical transducers. Different excitation frequencies and source–damage–sensor paths were considered. A fitness assessment criterion which compared baseline and damaged data sets using cross-correlation coefficients was developed empirically. Efficient sensor network optimization was achieved using a bespoke genetic algorithm for different network sizes with the effectiveness assessed and discussed. A comparable numerical data set was also produced using the local interaction simulation approach and optimized using the same methodology. Comparable results with those of the experimental data set indicated a good agreement. As such, the numerical approach demonstrates that acousto-ultrasonic sensor networks can be optimized using simulation (with some further refinement) during an aircraft design phase, being a useful tool to sensor network designers.

In order to overcome the difficulties in applying traditional Time-Of Arrival (TOA) techniques for locating Acoustic Emission (AE) events in complex structures and materials, a technique termed “delta-t mapping” was developed. This paper presents a significant improvement on this, in which the difficulties in identifying the precise arrival time of an AE signal are addressed by incorporating the Akaike Information Criteria (AIC). The performance of the TOA, the delta-t mapping and the AIC delta-t mapping techniques is assessed by locating artificial AE sources, fatigue damage and impact events in aluminium and composite materials respectively. For all investigations conducted the improved AIC delta-t technique shows a reduction in average Euclidean source location error irrespective of material or source type. For locating H-N sources on a complex aluminium specimen the average source location error (Euclidean) is 32.6, (TOA), 5.8 (delta-t) and 3mm (AIC delta-t). For locating fatigue damage on the same specimen the average error is 20.2, (TOA), 4.2 (delta-t) and 3.4mm (AIC delta-t). For locating H-N sources on a composite panel the average error is 19.3, (TOA), 18.9 (delta-t) and 4.2mm (AIC delta-t). Finally the AIC delta-t mapping technique had the lowest average error (3.3mm) when locating impact events when compared with the delta-t (18.9mm) and TOA (124.7mm) techniques. Overall the AIC delta-t mapping technique is the only technique which demonstrates consistently the lowest average source location error (greatest average error 4.2mm) when compared with the delta-t (greatest average error 18.9mm) and TOA (greatest average error 124.7mm) techniques. These results demonstrate that the AIC delta-t mapping technique is a viable option for AE source location, increasing the accuracy and likelihood of damage detection, irrespective of material, geometry and source type.

A modified cohesive zone model (CZM) has been developed to simulate damage initiation and evolution inGlare™ Fibre-Metal Laminate (FML) specimens containing both splice and doubler features under high-cycle fatigue loading. The model computes the cohesive stiffness degradation under mixed-mode loading based on user-defined crack growth rate data and is implemented in a VUMAT subroutine for the FEA software Abaqus/Explicit. To validate the model experimental data has been obtained for a number of Glare 4B specimens containing splice and doubler features monitored using digital image correlation (DIC) to provide full-field displacement and strain data and Acoustic Emission (AE) monitoring to detect damage initiation and propagation. The model was used to predict the initiation and growth of damage in splice joints under quasi-static loading. The results were verified against the cohesive zone model available in Abaqus and then validated against experimental data on Glare specimens. The codes are currently being extended to incorporate a mixed-mode fatigue damage evolution model based on input Paris laws, which have been extracted from high cycle fatigue experiments on Glare specimens containing both splice and doubler joints.

One of the major considerations currently affecting the design of composite aircraft structures is the damage resulting from lightning attachment. Full-field measurements of the displacement of materials under lightning attachment would provide a greater understanding of the forces induced by the high current waveform. Furthermore the understanding of the forces involved would allow for the validation of finite element models to simulate the effects of lightning attachment, therefore aiding in the design of solutions to reduce damage to aircraft structures. The study aimed to develop a pseudo-stereo high speed digital image correlation technique in order to obtain full-field information during lightning attachment based on a 100kA initial strike over a 500μs duration, the most severe waveform experienced. The technique that was developed gave full-field measurements for a 550x550x2mm 6082-T6 aluminium panel under a 100kA lightning attachment. Two correlation measurements were recorded at 3000 and 5000 frames per second. The displacement results are comparative with the theory of a cylindrical pressure expansion arising from the acoustic shockwave on attachment to the material. Further developments to this system could allow for more reliable results and higher frame rates which can be used to develop finite element simulations based on measured physical data.

Carbon fibre reinforced polymers (CFRP) have been used significantly more in\ud recent years due to their increased specific strength over aluminium structures. One major area\ud in which their use has grown is the aerospace industry where many now use CFRP in their\ud construction. One major problem with CFRP’s is their low resistance to impacts. Structural\ud health monitoring (SHM) aims to continually monitor a structure throughout its entire life and\ud can allow aircraft owners to identify impact damage as it occurs. This means that it can be\ud repaired prior to growth, saving weight with the repair and the time that aircraft is grounded.\ud Two areas of SHM being researched are Acoustic Emission (AE) monitoring and AcoustoUltrasonics\ud (AU) both based on an understanding of the propagation of ultrasonic waves. 3D\ud Scanning laser vibrometry was used to monitor the propagation of AU waves with the aim of\ud gaining a better understanding their interaction with delamination in carbon fibre reinforced\ud polymers. Three frequencies were exited with a PZT transducer and the received signal\ud analysed by a cross correlation method. The results from this and the vibrometer scans revealed\ud 100 kHz as the most effective propagating frequency of the three. A high resolution scan was\ud then conducted at this frequency where it could be seen that only the out of plane component of\ud the wave interacted with the damage, in particular the A0 mode. A 3D Fast Fourier Transform\ud was then plotted, which identified the most effective frequency as 160 kHz.