As Europe’s bridge infrastructure continues to age, ensuring its safety and resilience has become an increasing priority for infrastructure owners.
Research based on European Union Road Federation data estimates that almost half of Europe’s approximately one million bridges have reached or exceeded their original 50-year design life. Meanwhile, the European Commission’s Joint Research Centre has highlighted that many bridges across the Trans-European Transport Network exhibit structural deficiencies or are approaching the end of their intended service life. Against this backdrop, Structural Health Monitoring (SHM) is evolving from periodic inspection towards continuous, data-driven assessment.
Traditional bridge monitoring combines visual inspections with sensors such as strain gauges, accelerometers and displacement transducers. Although these techniques provide reliable measurements, they typically require direct access to the structure, the installation of instrumentation and, frequently, traffic or railway possessions. As infrastructure owners increasingly adopt digital asset management strategies, they require richer structural datasets capable of accurately representing how bridges behave under operational loading.
Recent advances in non-contact optical sensing are helping to address this need. By remotely measuring displacement, vibration and, more recently, continuous structural strain, multi-channel Laser Doppler Vibrometry (LDV) provides the engineering information required to validate structural models, build reliable digital twins and support predictive maintenance.
Technical Method
Laser Doppler Vibrometry is a well-established optical technique that measures structural vibration and displacement remotely using laser interferometry. While LDV directly measures vibration and displacement, the engineering innovation of Ommatidia’s Q-Series LDV lies in its ability to estimate vibration, deflection and structural strain from tens of points on the surface of a bridge simultaneously.
The methodology is based on classical Euler-Bernoulli beam theory, which relates structural curvature to bending strain. The measured deflection profile along the bridge is processed to calculate curvature through numerical differentiation. Knowing the bridge geometry, the corresponding surface strain can then be calculated continuously along the monitored section.
Unlike conventional strain gauges, which provide measurements only at discrete locations, the laser-based approach generates a dense strain distribution over the monitored span, effectively creating a network of virtual strain gauges without installing any sensors on the structure.
Strain is one of the most informative parameters for structural assessment because it is directly related to the stresses developed within structural members. Under normal operating conditions, bridges exhibit characteristic strain distributions determined by their geometry, material properties and load paths. Changes in these distributions may indicate stiffness loss resulting from cracking, fatigue, corrosion, joint degradation or altered support conditions. Monitoring strain therefore provides engineers with direct evidence of whether a bridge continues to perform as expected under service loads.
Together, these parameters provide a comprehensive description of structural behaviour from a single remote deployment, forming a high-quality dataset for structural assessment.
Field Example: La Marota High-Speed Railway Viaduct
The methodology has been demonstrated on the La Marota Viaduct, located on Spain’s Córdoba-Málaga high-speed railway line. As part of an innovation programme led by the Spanish railway infrastructure manager ADIF, with support from CDTI, Ommatidia deployed four Q1S Laser Radar units to monitor the bridge entirely from the pillars towards the soffit of the structure.
The laser radars were triggered by simple optical sensors that switched the systems on and off as each train arrived and departed. The units simultaneously acquired dense displacement measurements across the structure during train passages. Communication electronics uploaded the data to a cloud server. These measurements were then processed to obtain vibration characteristics, structural deflections and continuous strain distributions before being incorporated into the bridge’s digital twin.
The resulting dataset enabled measured structural behaviour to be compared directly with numerical models, supporting model calibration, long-term condition assessment and the identification of changes in structural response over time.
The project demonstrates how non-contact optical measurements can provide the high-quality engineering data required to maintain an operational digital twin while avoiding many of the logistical challenges associated with installing conventional sensor networks on operational railway infrastructure.
Limitations
Like any measurement technique, non-contact strain estimation has practical limitations that should be considered during deployment. The strain calculation is based on beam theory and is therefore most applicable to structural elements whose behaviour can be reasonably approximated using Euler-Bernoulli assumptions. Complex local effects or highly three-dimensional structural responses may require complementary analysis or additional instrumentation.
Accurate strain estimation also depends on the quality and spatial density of the displacement measurements, since numerical differentiation amplifies measurement noise. Appropriate signal processing, spatial sampling and measurement planning are therefore essential. Although remote optical systems eliminate the need for physical sensors, they require an unobstructed line of sight between the instrument and the monitored structure, as well as suitable environmental conditions.
Consequently, laser-based strain estimation should be regarded as a complementary component of an integrated Structural Health Monitoring strategy rather than a replacement for all conventional instrumentation.
Conclusion
Europe’s ageing bridge infrastructure demands monitoring technologies capable of providing more informative structural data while minimising operational disruption. By combining multi-channel Laser Doppler Vibrometry with beam-theory-based strain estimation, non-contact optical systems can generate continuous strain distributions alongside displacement and vibration measurements from a single remote deployment. Because strain is directly related to the stresses carried by a structure, its evolution over time provides one of the clearest indicators of structural condition.
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Author:
Eduardo Margallo
Chief Executive Officer, Ommatidia LiDAR Specialist in LiDAR, optical sensing and non-contact structural measurement technologies. |
