A new high-frequency eddy current technique for detection and imaging of flaws in carbon fibre-reinforced polymer materials

Using a high-frequency (50 kHz-4 MHz) alternating current field measurement (ACFM)-style inspection, non-destructive imaging of carbon fibre-reinforced polymers (CFRPs) was performed for the detection and evaluation of flaws developed during their manufacture or in-service use. This was achieved using quantum well Hall-effect (QWHE) sensors, which have proven suitability for use in different non-destructive testing and evaluation (NDT&E) applications based on their high sensitivity (they require lower strength applied fields and can detect smaller perturbations in the magnetic field), high linearity (high contrast and imaging evaluation capabilities), wide dynamic range (making them less sensitive to offset and lift-off variations), wide frequency operating range (DC to MHz) and compact size (5-70 microns depending on the application). Their advanced III-V semiconductor materials and design enable these characteristics. Their low capacitance allows them to be operated at significantly higher frequencies than coils of comparable sensitivity or size. As such, the inherent advantages of QWHE sensors have been used in conjunction with a high-frequency ACFM-style magnetic imaging inspection technique, which is referred to as quantum well eddy current field measurement (QW-ECFM) in this paper. Here, the fundamentals of this new technique are outlined, as well as the outcomes of such a technique for evaluating CFRP materials, where individual fibre bundles have been resolved in high detail with high contrast. In addition, the ability to detect fibre misalignment has been shown, suggesting technique sensitivity to 3D orientations of fibre for better material qualification and the detection of delamination down to 2 mm in diameter. Therefore, this paper aims to provide an overview of this new QW-ECFM technique and summarise its performance for the detection and evaluation of various CFRP material flaws that are commonly found during manufacture and service.