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Publication - Dr Robert Hughes

    Performance analysis of single-frequency near electrical resonance signal enhancement (SF-NERSE) defect detection

    Citation

    Hughes, RR & Dixon, S, 2019, ‘Performance analysis of single-frequency near electrical resonance signal enhancement (SF-NERSE) defect detection’. NDT and E International, vol 102., pp. 96-103

    Abstract

    In the search for ever more sensitive non-destructive testing (NDT) techniques to detect progressively smaller defects in increasingly complex industrial materials, environments and geometries, conventional eddy-current testing (ECT) methods, have reached their sensitivity limit. Fortunately, advanced resonance-based techniques, demonstrated in recent years, promise to help extend that limit, but, before such techniques can be implemented with confidence, a detailed understanding of their sensitivity and stability must be achieved. In this study, statistical probability-of-detection (PoD) analysis was performed to assess the sensitivity of a novel single-frequency, near electrical resonance signal enhancement (SF-NERSE) technique relative to an equivalent conventional probe operation. This study was performed on 36 real fatigue defects in Titanium 6V-4Al (Ti6-4) with defects ranging from 0.10−6.48 mm in surface extent. In addition, a critical evaluation of background noise stability in the SF-NERSE technique (a common concern with NERSE-based methods) was also performed to establish the viability of such a technique in relation to industrial inspection and assessment criteria. The results of this study demonstrate a sensitivity enhancement of up to 20% for the SF-NERSE method over conventional operation and, through controls, confirmed that the effect is a result of the resonance-shifting phenomenon and not just an increase in operational frequency. In addition, an examination of background noise implies that a SF-NERSE method exhibits more stable background noise than conventional excitation. This study validates the SF-NERSE technique and methodology as a viable industrial inspection technique, able to significantly improve detection capabilities.

    Full details in the University publications repository