A key challenge in Fiber Bragg Grating (FBG) interrogation for Structural Health Monitoring (SHM) is the simultaneous achievement of high wavelength resolution, high sensing capacity, and high interrogation rate within a compact and scalable system. In this work, an Optical Time Stretch (OTS)-based FBG interrogator is proposed to relax this trade-off by combining a recirculating-loop dispersion module with a Time-to-Digital Converter (TDC)-based electronic readout. The architecture enables large accumulated dispersion and direct real-time temporal acquisition, while remaining compatible with future extensions toward combined TDM–WDM multiplexing. Static validation on strain and temperature sensing yields equivalent time–strain and time–temperature sensitivities of 25.85 ± 0.81 ps/μϵ and 0.85 ± 0.06 ns/°C, respectively, with picometer-level wavelength resolution. A first dynamic proof-of-concept also demonstrates impact detection at a scan rate of 51 kHz, confirming the potential of the proposed system for high-resolution SHM and acoustic/impact monitoring.

The rapid development in the field of the Internet of Things (IoT) has paved the way for integration of wireless low-power electronic sensors, typically in the range of milli to micro watt in Structural Health Monitoring (SHM) systems.Energy harvesting of ambient sources present in the SHM systems' environment can potentially generate enough power to target wireless sensor autonomy. Vibrations are an energy source found in abundance in civil engineering structures, such as a bridge, due to various reasons including environmental phenomena, traffic load and human activities. While piezoelectric and electromagnetic energy harvesters are employed to real-world applications such as powering-up sensors deployed in bridges and in marine buoys respectively, Triboelectric Nanogenerators (TENGs) are attracting significant attention due to their cost effectiveness, high conversion efficiency and wide material versatility. This makes TENGs suitable for creating cheap and efficient low-frequency vibration energy harvesters. In this work, a novel architecture of a contact-separation freestanding tribolayer TENG (CFTENG) is demonstrated. In a low frequency (2 Hz) and a low amplitude environment (5 μm) the CFTENG was able to demonstrate an open-circuit voltage of 213.9 V. When connected to an optimal resistance of 50 MΩ, an output voltage of 104.49 V a short-circuit current of 2.09 μA, a peak power of 115.3 μW and energy per contact separation of 3.09 μJ were observed. The results demonstrate that the CFTENG offers a reliable and cost effective alternative solution to harvest energy from low-frequency vibrations and act as a sustainable power source for low-power SHM sensor nodes. The integration of TENGs in a SHM sensor node enables the development of a reliable, cost effective alternative solution lays the groundwork for autonomous self-powered SHM systems.

Ultrasonic-based Structural Health Monitoring (SHM) systems generate massive datasets that quickly exceed the capabilities of embedded/low power sensing systems. Additionally, in the case of distributed sensing with thousands of sensors, acquiring, storing, and transmitting the signals becomes a serious hurdle for traditional monitoring pipelines. Since SHM data is typically redundant, the problem can be alleviated through data reduction methods that filter irrelevant signal contributions in the sensors before they get transmitted or even recorded. Conventional Singular Value Decomposition (SVD)–based compression methods rely on fixed sub-spaces that fail to adapt to evolving environmental or operational conditions, leading to false alarms or missed detections of damage. To overcome these limitations, this work introduces a low-rank, frequency-domain subspace compression and adaptive update framework based on the Incremental SVD combined with Frequency Stretching applied to Direct Wave Interferometry (DWI) for damage detection and velocity change monitoring. A correlation-triggered mechanism is used to selectively update the baseline subspace only when Environmental and Operational Conditions (EOCs)/damage-induced variations exceed defined thresholds, forming a self-adjusting reference as a background task. This allows hardware-level switching between compressed sensing
and full acquisition modes, ensuring efficient data reduction without loss of sensitivity. The proposed low-rank spectral subspace approach successfully distinguishes the damage-induced variations from environmental effects, where the measurement data is approximated with a small number of coefficients within an adaptive, low-dimensional subspace that is first learned from baseline reference data and continuously updated to retain structural information. This compressed form can be obtained directly in hardware through linear projections, enabling in-situ (“on-the-fly”) spectral sensing data reduction before transmission or storage. As EOC variations or damage arise, the incremental SVD adaptively updates the baseline subspace representation without requiring full recomputation, ensuring stable performance over long-term monitoring. This framework enables robust SHM systems by integrating effective dimensionality reduction with adaptive performance under realistic environmental conditions.

Environmental and operational conditions (EOCs) strongly influence guided wave propagation, often masking structural damage in Structural Health Monitoring (SHM) applications. In particular, temperature variations significantly affect the propagation of guided waves in composite materials – a critical issue in the aeronautical field, where composites materials are increasingly used for primary structures. Changes in EOCs introduce variations into measured signal characteristics that are often comparable with those caused by damage, potentially leading to false positives or missed detections, ultimately limiting the applicability of SHM systems in real operational scenarios. These considerations highlight the need to compensate for environmental effects in order to ensure reliable damage detection, always bearing in mind that damage detectability depends on the specific scenario and SHM technique applied. This study investigates these effects and evaluates a time-stretching based compensation method currently used in civil engineering structures, applied here to an aeronautical structure.

In guided wave propagation applied to thin plates, A₀ and S₀ represent the two fundamental Lamb modes, characterized respectively by antisymmetric and symmetric displacement profiles. The experimental campaign was designed with a dual objective: first, to evaluate the dispersion of the fundamental A₀ mode under the specific test conditions, and second, to compensate temperature-induced variations affecting this mode.

The experimental test was conducted within the USES² doctoral network, whose focus is on ultrasonic and seismic embedded sensors for non-destructive evaluation. Tests were performed at Université Gustave Eiffel (UGE) on an undamaged Carbon Fiber Reinforced Plastic (CFRP) thin panel manufactured by Universidad Politécnica de Madrid (UPM). The setup consisted of an ultrasonic piezoelectric probe measuring seismograms with forty sensors placed on the panel and operating in out-of-plane excitation at 100 kHz (A₀ dominant behaviour). Measurements were acquired in a climatic chamber with temperature ranging from 20 °C to 70 °C at constant humidity.

Because the test reproduces an A₀-dominant impact-like excitation at 100 kHz, frequency at which the A₀ mode is particularly dispersive compared to S₀, group velocities were computed at fixed temperature steps by aligning the first and last peaks of the transient wave packet for each sensor pair. The analysis was supported by our dispersion-curve calculation model for composite materials, ensuring consistency between experimental and theoretical trends. Dispersion-induced shifts were found to be an order of magnitude smaller than those caused by temperature. It indicates a limited influence under the tested conditions and particular structure. A correlation-based time stretching method was then applied, where a scaling factor ε compensates temperature-induced waveform distortions, highlighting the potential transferability of this compensation method between civil and aerospace SHM applications.