Automated analysis and advanced defect characterisation from ultrasonic scans of composites

Abstract

With the rapidly escalating usage of composite materials, not only in military aircraft but in civil airliners as well, production NDT throughput is already stretched to its limit internationally. NDT data analysis is set to become the bottleneck preventing the required rise in production rates of composite civil aircraft in the next few years. Thus there is an urgent requirement for rapid, automated analysis of up to a Terabyte of data per airliner, escalating to over 200 Terabytes per year-worldwide. The primary aim of automated analysis is to release operators from the time-consuming analysis of all scans and focus operator attention on non-compliant structures. A secondary aim is to provide threedimensional quantitative information that lightens the operator's decision-making burden. Through advanced characterisation methods, NDT also has the potential to provide crucial feedback to control the composite production process, increase production yield and decrease costs. Current analysis methods for ultrasonic scans produce through-thickness average parameters, which provide little useful information to assist the stress analysis for defects, or the production process. Three-dimensional characterisation of defects can increase yield by informing the concession/disposition process for defects. For future process control, information is required about the 3D distribution of material properties in the structures on the production line, providing comprehensive long-term trend analysis. 'ANDSCAN' is a Registered Trademark of QinetiQ Ltd. 'StackScan', 'Ply Fingerprinting' and 'PinPoint' are Trademarks of QinetiQ Ltd. 'MLM-PropMat' is a Trademark of the University of Nottingham. Patents have been filed by QinetiQ Ltd covering the technology described in this paper.

Phononic band gaps and phase singularities in the ultrasonic response from toughened composites

“…A desire to increase confidence in the manufacture of complex carbon-fiber composite components [1][2][3] has resulted in improved three-dimensional (3D) ultrasonic characterization methods to determine out-of-plane ply orientation and wrinkling [4][5][6][7][8][9][10][11][12][13][14] as well as in-plane fiber orientation and waviness [7][8][9][10]. These methods exploit the weak resonances formed by reflections at the periodic resin-layer boundaries between plies in the laminate.…”

Acoustic characterization of void distributions across carbon-fiber composite layers

“…Figure 1 presents an example of a 3D profile of a porosity-related FIGURE 1. Example of a 3D profile of a porosity-related ultrasonic parameter demonstrating depth-dependence of scattering [4].…”

“…ultrasonic parameter [4] illustrating some layer porosity and some distributed porosity. The detection of porosity as well as its level is important for the NDT techniques.…”

“…Using a decomposition method, the work by Smith et al [13] proposes an interesting method for decomposing the measured frequency spectrum into a series of basis functions representing porosity, thick resin layers and good structure, resulting in a coefficient for each basis function. This coefficient can then fully characterize the ultrasound response of the composite and can be used to estimate the porosity or a change of resin layer thickness or fiber-resin change [14]. Their method is shown to be effective provided porous plies are always separated by porosity-free plies.…”

Design and demonstration of automated data analysis algorithms for ultrasonic inspection of complex composite panels with bonds

“…However, the ultrasonic inspection of large composite structures requires significant manpower and production time. To address this inspection burden and ideally increase inspection reliability, software tools and automated data analysis (ADA) algorithms [4][5][6][7][8][9] have been developed to support the assessment of ultrasonic data from composite components. Recent work on the design of ADA algorithms [7][8][9] follows standard procedures for analyzing signals for time-of-flight indications and backwall amplitude dropout.…”