To account for the temperature effect on guided wave signals in complex structures, a significant amount of baseline measurements typically need to be collected over a large temperature range to serve as a library of signals at all possible temperatures, which, if not impossible, is highly impractical. This article presents a data-driven temperature baseline reconstruction approach that is applicable for various structures made from the same material. The influence of temperature on the amplitude and phase of guided wave measurements are experimentally quantified as dimensionless compensation factors. The derived compensation factors are used to reconstruct baselines at various temperatures for guided wave measurements in a simple flat plate and a stiffened panel. With a single baseline measurement at 20°C and the reconstructed baseline using the predetermined temperature compensation factors, impact damage was successfully detected and located when current measurements were up to 25°C and 20°C higher than the baseline temperature, respectively.

This paper proposes a structural health monitoring (SHM) building block (BB) approach for guided wave based structural health monitoring (GWSHM) of large composite stiffened panel subjected to varying temperature conditions. The proposed approach follows a similar philosophy to industrial substantiation of composite structures through BB by conducting SHM analysis and associated tests at different levels of structural complexity, beginning with small coupon specimens and progressing through structural elements and details (mono-stringer) and finally sub-components (large stiffened composited panel). Each level builds on the knowledge gained at previous, less complex levels. The detection of multiple barely visible impact damage (BVID) in the large panels is achieved by outlier analysis using a reference pristine database gathered from simple coupons and mono-stringer panels under a wide range of temperature variation. This approach enables the data utilisation from lower-level structure in the proposed BB test scheme to higher-level structures and hence reduce the number of tests required for large and complex structures. The detected damage is then localised by a proposed two-step multi-damage localisation method, which first confirms the presence of the damage and narrows down the damaged section then provides an enhanced damage imaging for precise location estimation. Damage detection with a true positive rate of 0.909 and a false positive rate of 0.111 as well as accurate multiple damage localisation are achieved in the flat fuselage panels for a temperature range of 25 °C–50 °C.

In this article, a hierarchical approach is proposed for the design and assessment of a guided wave-based structural health monitoring system for the detection and localisation of barely visible impact damage in composite airframe structures. The hierarchical approach provides a systemic and practical way to establish guided wave-based structural health monitoring systems for different structures in the presence of uncertainties and to quantify system performance. The proposed approach is carried out in four steps: (1) determine optimal sensor placement for the target structure and its plausible impact scenarios, (2) set detection threshold for global damage index based on the noise level present in the required environmental and operations conditions, (3) detect damage in critical locations and quantify detection performance by calculating the probability of detection, probability of false alarm and detection accuracy and (4) locate the detected damage while also quantifying the accuracy of location estimation and the probability of correctly indicating if the damage is in an area critical to the integrity of the structure. The proposed approach is demonstrated in aircraft carbon fibre-reinforced polymer structures from coupon level (simple flat panels) to sub-component level (large flat panel with multiple carbon fibre-reinforced polymer stringers and aluminium frames) for the detection and localisation of barely visible impact damage.

Optical fiber sensors (OFSs) represent an efficient sensing solution in various structural health monitoring (SHM) applications. However, a well-defined methodology is still missing to quantify their damage detection performance, preventing their certification and full deployment in SHM. In a recent study, the authors proposed an experimental methodology to qualify distributed OFSs using the concept of probability of detection (POD). Nevertheless, POD curves require considerable testing, which is often not feasible. This study takes a step forward, presenting a model-assisted POD (MAPOD) approach for the first time applied to distributed OFSs (DOFSs). The new MAPOD framework applied to DOFSs is validated through previous experimental results, considering the mode I delamination monitoring of a double-cantilever beam (DCB) specimen under quasi-static loading conditions. The results show how strain transfer, loading conditions, human factors, interrogator resolution, and noise can alter the damage detection capabilities of DOFSs. This MAPOD approach represents a tool to study the effects of varying environmental and operational conditions on SHM systems based on DOFSs and for the design optimization of the monitoring system.