Multi-characteristic combination based reliability enhancement of optical bidirectional thermal wave radar imaging for GFRP laminates with subsurface defects. (April 2021) - Gong, Jinlong; Liu, Junyan; Yu, Yanting; Zheng, Yi
Abstract: In this paper, the detection reliability of optical bidirectional thermal wave radar imaging (BTWRI) for glass fiber reinforced polymer (GFRP) laminates with subsurface defects using various imaging algorithms was quantitatively investigated. A set of GFRP laminates with artificial defects were prepared and inspected. Three frequently-used imaging algorithms (cross-correlation, CC; chirp lock-in, CLI; and Hilbert transform mean, HTM) were applied to construct characteristic images. An analysis for probability of detection (POD) was carried out based on the hit/miss data obtained by comparing the defect contrasts and noise thresholds of characteristic images. A multi-characteristic combination (MCC) method integrating the advantages of each algorithm was proposed. The reliability assessment of optical BTWRI for inspecting GFRP laminate defects was compared by the defect diameter-to-depth ratio ( r 90/95 ) at 90% POD with 95% confidence level and detection rates (DRs). The comparison results show that the MCC method exhibits enhanced reliability with smaller r 90/95 and higher DRs at a series of determination thresholds compared with CLI, HTM, and CC algorithms.