Self-referenced robust guided wave based defect detection: application to woven composite parts of complex shape
Résumé
The use of a reference state, i.e. a baseline, for data analysis in guided wave based structural health monitoring is limiting the range of applicability of such approaches. This has been largely demonstrated in the literature in the presence of temperature changes, but is also true in the presence of other varying environmental and operational conditions, as well as aging effects. This paper presents a novel self-referenced methodology, which is built to be intrinsically robust to the influence of external effects, allegedly including the ones not identified during system design. The method relies on the concept of instantaneous baseline, i.e. the comparison of multiple measurements acquired on structures with a high degree of similarity from a guided wave perspective. The subtlety of the approach is the detection of flaws of small influence on the measurements, in the presence of extrinsic and intrinsic variabilities of comparatively larger influence over several similar samples. The method includes also a dimension reduction through the extraction of quantities of interest from the acquired signals, potentially enabling the analysis of several samples with limited data volume.
The proposed method is successfully validated on 12 aluminum plates, each with a through-hole crack from 1 to 30 mm in length in a laboratory environment with limited external parameters. Next, the approach is tested on 2 woven composite samples of complex shape with up to 7 similar paths from a guided wave perspective. At low frequency (50 kHz), an added mass is detected over the entire temperature range under consideration, i.e. between -30°C and 30°C. At higher frequency (>100 kHz) the approach remains functional but less robust, which highlights the material variability between and within the samples.