Interfacial debonding detection and quantification in rubber-to-metal bonded structures via microwave imaging

Purpose The purpose of this study is to establish a high-resolution and quantitatively reliable microwave imaging framework for detecting and assessing interfacial debonding in rubber-to-metal bonded structures – an issue that directly threatens the operational safety and reliability of aerospace, automotive and industrial components. Traditional non-destructive testing (NDT) techniques often fail to capture weak debonding signatures. Addressing this limitation, this study aims to design an imaging-driven diagnostic approach capable of resolving small-scale debonding defects, extracting meaningful defect features from noisy metal-dominated measurements and providing automated quantitative metrics. Design/methodology/approach This work develops a planar-scanning-based microwave reflection imaging system integrated with a spatial-wavenumber spectrum reconstruction algorithm tailored for subsurface interface inspection. A dual-layer adaptive matched-filter transfer function is constructed to compensate for phase distortions introduced by the heterogeneous layered structure, thereby improving azimuth resolution and contrast. To further suppress strong surface reflections and enhance weak defect signatures, an adaptive singular value decomposition (SVD)-based feature enhancement strategy is incorporated into the imaging pipeline. Following reconstruction, a quantitative evaluation method combining adaptive rapid image segmentation with pixel statistical analysis is introduced to automatically extract defect location, equivalent area and shape features. Findings Experimental validation confirms that the proposed approach can reliably detect and characterize interfacial debonding as small as ∅5 mm within rubber-to-metal bonded structures. The reconstructed images exhibit notably enhanced defect visibility even in the presence of dominant metal reflections, and the quantitative evaluation achieves a defect area error below 10% and a positional error under 2 mm. The results of this study collectively verify the robustness, sensitivity and adaptability of the proposed imaging framework and highlight its suitability for inspecting various bonded structures with differing geometric and material configurations. Originality/value This study presents a novel microwave NDT methodology that addresses the fundamental challenge of detecting weak interface debonding buried beneath strong surface reflections – an area where existing imaging or conventional NDT methods often fail. The integration of a dual-layer adaptive matched filtering strategy with SVD-based defect enhancement introduces a new mechanism for isolating subsurface dielectric discontinuities in complex heterogeneous structures. Moreover, the proposed adaptive quantitative evaluation framework enables automatic and accurate extraction of defect parameters, offering a level of assessment capability rarely achieved in microwave reflection imaging.