Abstract
Capacitive Imaging (CI) sensors are capable of non-destructively detecting both surface and hidden defects in dielectric materials and characterizing conducting surfaces through a relatively thick insulation layer. However, the complex Measurement Sensitivity Distribution (MSD) of CI sensors render the sensor capacitance variation with lift-off highly non-linear, which may lead to misinterpretation of defect indications. This work systematically studied the lift-off effect using both Finite Element (FE) analysis and experimental approaches. Sensor MSD was used as a tool to predict the imaging performance. Normalized Variation Ratio (NVR) was introduced and used to characterise sensor responses due to defects for a CI sensor. Both the FE analysis and experiments suggest that the lift-off effect for a CI sensor is specimen type and condition dependent. For a given defect, the NVR may vary non-monotonically with increased lift-offs. A case study on a glass-fibre composite/aluminium hybrid structure with multiple artificial defects demonstrated the feasibility of defects discrimination using multiple CI scans with increased lift-offs.
Highlights
Non-destructive evaluation (NDE) techniques have been widely used in various applications, i.e., crack detection, material degradation evaluation, weld joint diagnosis, etc., to ensure system safety and reliability [1,2]
This paper explores the lift-off effects for coplanar Capacitive Imaging (CI) sensors based on Finite Element (FE) and experimental investigations
Measurement Sensitivity Distribution (MSD) variations due to non-conducting and conducting boundaries with increased lift-offs can be visualized in the FE models
Summary
Non-destructive evaluation (NDE) techniques have been widely used in various applications, i.e., crack detection, material degradation evaluation, weld joint diagnosis, etc., to ensure system safety and reliability [1,2]. Fu presented a new approach based on the dynamic trajectories of the fast Fourier process can eliminate lift-offsignals in PECfordefect classification in both time thefound domain frequency transform (FFT) of thethe received reducing the lift-off effect [12]. Fan presented a model-based inversion method in terms of lift-off reduction for eddy process can eliminate the lift-off in PEC defect classification in both time the domain and frequency current characterization of a aplate [14] andinversion investigated theinbehaviors of LOIreduction due to afor plate with domain [13]. It is important to carry out a systematic investigation of the lift-off effect and to propose an efficient way to use information arising from varying lift-offs for defect characterisation.
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