Summary Remote measurements using images are particularly useful in structural health monitoring cases in which the installation of contact sensors is difficult. Some limitations, though, associated with photogrammetry‐type optical metrology involve the application of speckle patterns, which become even more important with variable working distance or when the required resolution and sensitivity are not a priori known which are both very practical common issues. In this context, multispectral sensing can circumvent some of the challenges of acquiring data at different working distances. The objective of this investigation is therefore to use multispectral imaging combined with the method of digital image correlation to demonstrate an approach for remote sensing related to deformation measurements at the structural level. To demonstrate this novel approach, two speckle patterns were designed for measurements at specified working distances; one was set to work in the visible and the second in the ultraviolet spectrum. The results show that the spectral specific reflectivity of the speckle patterns can be used for spatial overlay without affecting imaging in either spectral range considered, which allows the extraction of multiscale deformation information.

The research presented in this article aims to demonstrate how acoustic emission (AE) monitoring can be implemented in an industrial setting to assist with part qualification, as mandated by related industry standards. The combined structural and nondestructive evaluation method presented departs from the traditional pass/fail criteria used for part qualification, and contributes toward a multi-dimensional assessment by taking advantage of AE data recorded during structural testing. To demonstrate the application of this method, 16 composite fixed-wing-aircraft spars were tested using a structural loading sequence designed around a manufacturer-specified design limit load (DLL). Increasing mechanical loads, expressed as a function of DLL were applied in a load-unload-reload pattern so that AE activity trends could be evaluated. In particular, the widely used Felicity ratio (FR) was calculated in conjunction with specific AE data post-processing, which allowed for spar test classification in terms of apparent damage behavior. To support such analysis and to identify damage critical regions in the spars, AE activity location analysis was also employed. Furthermore, recorded AE data were used to perform statistical analysis to demonstrate how AE datasets collected during part qualification could augment testing conclusions by providing additional information as compared to traditional strength testing frequently employed e.g., in the aerospace industry. In this context, AE data post-processing is presented in conjunction with ultimate strength information, and it is generally shown that the incorporation of AE monitoring is justified in such critical part qualification testing procedures.

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