Measurement of guided waves at high temperatures is a major challenge
in SHM for several critical applications in aerospace, nuclear and other industries.
Classic piezoelectric sensors are based on lead zirconium titanate
which have a Curie temperature around 350 °C preventing the use of these
transducers at higher temperatures. Optical fiber sensors, based on fused
silica, are intrinsically more stable at high temperatures. Particularly, regenerated
and femtosecond microvoid-based Fiber Bragg Gratings (FBGs)
were demonstrated to operate at temperatures exceeding 1000 °C.
Ultrasonic wave measurement with FBGs can be realised using the edge filtering
method, consisting of placing a narrow-band light source on the edge
of the reflection peak of the grating. Strain applied to the FBG will modify
the grating reflection spectrum and hence change the reflected power at the
source wavelength. This power is measured and constitutes the ultrasonic
signal. Among the advantages of this method, it provides a high-enough
sensitivity to measure sub-micron strain and it enables high sampling rates,
both being required to measure guided-waves. As FBGs are also sensitive
to quasi-static strain and temperature changes, it is advantageous to use a
tunable laser with a tracking algorithm to lock the laser on the edge of the
grating. A home-made interrogation based on the aforementioned principles
was developed.

To this day, high temperature measurements of ultrasonic waves remains
challenging. Particularly, the sensor’s lifespan will depend on the amplitude
loss and wavelength drift of the grating, but also on its attachment especially
on structures with high thermal dilatation. Hence, coupling strategies
for the fiber will be discussed: indeed careful choice of the adhesive should
be made. Removing the coating of the fiber can also be considered as offthe-
shelf coatings have temperature limits below the one of the fiber. In
this contribution, we will present measurements of ultrasonics guided waves
performed at high temperatures (up to 1000 °C) in a tubular oven (cf. attached figure) with femtosecond microvoid FBGs, using the edge-filtering based
interrogation system. Especially, we will illustrate its ability to measure
acoustic emission signals in severe conditions hardly achievable by current
monitoring solutions.

In Austria, a new railway bridge with a composite design has been constructed in an area characterized by complex geological conditions. To obtain detailed insights into the bridge’s structural behaviour from the initial state on, an integrated monitoring concept based on distributed fibre optic sensing (DFOS) was implemented during the construction process. The bridge features a steel truss superstructure combined with a reinforced concrete deck. Fibre optic sensors were embedded directly within the composite joint, in the concrete slab, and along the steel framework to enable spatially continuous, high-resolution measurements of strain and temperature throughout the construction phase and ongoing operation. The initial measurements covered key stages starting from concreting to proof load testing. Subsequent periodic measurements are planned to capture long-term changes in the internal strain state of the bridge, including longtime effects of the structure and surroundings.

The chosen monitoring approach enables spatially continuous detection of both strain and temperature in the different bridge components. To ensure reliable strain evaluation, a temperature compensation model was developed through laboratory calibration using climate chamber tests on representative steel and concrete specimens with embedded fibres. These tests facilitated the derivation of material-specific temperature–strain relationships and allowed for the separation of thermally and mechanically induced strain components in the field data. The resulting compensation model is applied to the distributed measurements, ensuring accurate assessment of structural strain under varying environmental conditions.

This paper presents the overall concept and exemplary results obtained during the construction phase, demonstrating the feasibility and performance of the monitoring system under real-world conditions. The recorded data provide valuable insights into the evolution of the structural response during key construction stages, including concreting, composite activation when removing the auxiliary supports and proof load tests just before starting the operation. Initial findings show a clear correlation between measured strain patterns and construction activities, validating both the sensor placement and the overall measurement concept. The presented results represent an important step toward the practical application of distributed fibre optic sensing in large-scale composite bridge structures under complex site conditions. The insights gained will serve as a foundation for further evaluation during the operational phase, supporting continuous structural health monitoring, early detection of potential damage, and an improved understanding of the long-term behaviour of steel–concrete composite systems.

In this paper, we use distributed fiber optic sensing (DFOS) for traffic load monitoring on a newly constructed bridge instrumented with a network of embedded optical fibers. Specifically, the optical fibers are embedded longitudinally in all bridge girders at two depths, forming a looped sensing configuration that enables the measurement of different stress states when a vehicle passes. The measurements presented here were conducted before the bridge was opened to traffic, using a mobile crane weighing approximately 36 metric tons, with the load distributed evenly across three axles. We show that our DFOS system can effectively capture the bridge structural response to the moving mobile crane and provide estimates of axle weight distribution and spacing. Finally, the results indicate that, although the fibers located in the girders beneath the loaded lane are strongly affected by the traffic, the fibers beneath the unloaded lane show only a negligible response, highlighting the ability to separate the effects of vehicles traveling in neighboring lanes.

Rockfall hazards have increasingly drawn global attention due to their devastating impacts on human lives, infrastructure, and the environment. Traditional monitoring approaches for these events typically rely on ground-based radar, video surveillance, and point sensors such as accelerometers and strain gauges. Although these methods provide valuable insights into ground motion and event characteristics, they are often constrained by sparse spatial coverage, limited resolution, susceptibility to environmental interference, and high installation and maintenance expenses. Distributed Acoustic Sensing (DAS) technology mitigates these issues by converting optical fiber cables, extending tens of kilometers, into a continuous array of virtual sensors with meter spatial resolution. Previous studies have demonstrated that DAS can capture high-frequency seismic signals generated by artificially triggered rockfalls, exhibiting strong correlation with conventional seismic records. In this study, we conducted an extensive DAS data collection campaign that captured routine operational signals from various highway segments, diverse vehicle types, and different time periods. The testing section, approximately 1 km long, is situated along an highway in Quzhou, Zhejiang Province, China. Subsequently, we manually simulated rockfall events by allowing wooden stakes of varying weights to fall naturally at different locations, thereby emulating the characteristics of real rockfall incidents. Given the substantial daily sample size and the rigorous requirements for a low false alarm rate, a single model proved insufficient. Therefore, by integrating features from the time-frequency domain and spatial resolution, we fused an audio classification model- PANNs with Self-Attention and Convolution to develop a DAS-based long-range rockfall monitoring and early warning system. This model delivers accurate, real-time monitoring over extensive distances, achieving a recall rate exceeding 92% while maintaining a false alarm rate of only 0.058%. Moreover, the system can provide timely alerts regarding incidents, offer recommendations to road maintenance departments, and significantly mitigate secondary disasters such as traffic accidents and congestion triggered by rockfalls.

Structural health monitoring has traditionally been applied primarily to existing structures that already exhibit damage or load-bearing deficits. In such cases, a customized monitoring concept is typically developed to address the specific condition of the structure. This reactive approach, however, contrasts with the objectives of predictive infrastructure management, which aim to detect changes at an early stage and support long-term planning. For new bridge constructions, a shift toward proactive and integrated monitoring is therefore highly desirable.

Key requirements for such an approach include the permanent availability of pre-installed sensing technology, reliable power supply and data transmission, measurement procedures without traffic disruptions, on-demand data retrieval, and the implementation of a reference or baseline measurement immediately after construction. This baseline allows any subsequent structural changes throughout the lifecycle of the bridge to be identified with high accuracy. Moreover, comprehensive monitoring supports efficient maintenance planning by combining sensor data with traditional inspection results. New bridge structures offer ideal conditions for embedded monitoring systems, as modern, robust, and cost-effective sensors can be installed permanently and non-invasively in all relevant components, including those that will later become difficult to access.

Continuous monitoring provides several key benefits as early detection of damage such as corrosion or cracking, improved planning of maintenance interventions, optimization of inspection intervals, and reduction of costs and traffic restrictions. Furthermore, real structural loads resulting from variable influences such as traffic, temperature, or wind can be recorded and analyzed in detail, supporting fatigue assessments, remaining service life predictions, and the development of digital twins. Additional advantages include the detection of overloads and unauthorized heavy transports, as well as faster structural assessment following exceptional events such as fires or slope failures.

This paper presents the instrumentation of a newly constructed prestressed concrete bridge using distributed fiber optic sensing (DFOS). The fiber optic sensors were integrated into all major components of the structure, including the deck slab, abutments, and all precast girders. The fiber optic sensing cables were designed to allow flexible configuration of measurement sections. During the construction phase, verification measurements and a load test were performed to evaluate installation quality, sensor performance, and data reliability. The results demonstrate that DFOS is a powerful and practical technology for structural health monitoring of new bridge constructions and represents a key enabler for predictive maintenance management.