TY - JOUR A1 - Lu, Xin A1 - Königsbauer, Korbinian A1 - Hicke, Konstantin T1 - Improved phase retrieval method for system simplification or fading suppression in interferometer-based φOTDR systems N2 - Phase sensitive optical time domain reflectometry (φOTDR) systems based on different types of interferometers for phase retrieval typically require two or three photodetectors to record the outputs from the interferometer. A novel signal processing principle is proposed for phase retrieval by taking the difference between two outputs as the quadrature component and reconstructing the in-phase component via Hilbert transformation of the Q component for IQ demodulation. Thus, only one balanced photodetector or two standard photodetectors are need, reducing system complexity and data volume. This principle can also be used to suppress fading effect for the traditional three-detector φOTDR systems by selecting optimal phases across detector pairs. Experiments with a φOTDR systems based on an imbalanced Mach-Zehnder interferometer validate the feasibility of this method and demonstrate a high fading suppression of about 90%. KW - Phase retrieval KW - Distributed fiber sensing KW - Structural health monitoring PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-652630 DO - https://doi.org/10.1364/OE.580984 SN - 1094-4087 VL - 33 IS - 26 SP - 54733 EP - 54746 PB - Optica Publishing Group AN - OPUS4-65263 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schackmann, Oliver A1 - Márquez Reyes, Octavio A1 - Memmolo, Vittorio A1 - Lozano, Daniel A1 - Prager, Jens A1 - Moll, Jochen A1 - Kraemer, Peter T1 - Intelligent damage detection in composite pressure vessels under varying environmental and operational conditions N2 - Despite proven approaches available in the literature, structural health monitoring by ultrasonic guided waves under varying environmental and operational conditions is still challenging. The use of machine learning approaches is discussed in this work, considering the complex problem of experimental damage detection under varying load conditions in a composite overwrapped pressure vessel for hydrogen storage. Specifically, unsupervised methods originally developed for image and time series classification are combined with ensemble voting to conceive reliable damage detection technique. This enables the effective combination of the predictions of multiple transducer pairs, even with a limited number of strong individual classifiers. A performance demonstration of the technique is presented using a real damage scenario dataset. T2 - IEEE 12th International Workshop on Metrology for AeroSpace (MetroAeroSpace) CY - Napoli, Italy DA - 18.06.2025 KW - Guided ultrasonic waves KW - Structural health monitoring KW - Artificial intelligence KW - Hydrogen storage PY - 2025 SN - 979-8-3315-0152-5 DO - https://doi.org/10.1109/MetroAeroSpace64938.2025.11114628 SN - 2575-7490 SP - 608 EP - 613 AN - OPUS4-64894 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Lu, Xin A1 - Christensen, J. A1 - Thomas, P. A1 - Failleau, G. A1 - Eisermann, R. A1 - Hicke, Konstantin A1 - Krenek, S. T1 - Fiber artefact for performance evaluation of time domain distributed fiber sensor interrogators N2 - Distributed fiber sensing (DFS) is a powerful tool for structural health monitoring (SHM), allowing continuous and seamless measurements of temperature and strain along the fiber. The spatial accuracy of a DFS interrogator, as a key parameter of the system, is vital for precisely locating structural perturbations or defects. Its evaluation and calibration methods however attract little attention. A fiber optic artefact based on a fiber loop is developed to evaluate distance accuracy and signal quality for both self-developed and commercial sensing systems based on Rayleigh, Raman, and Brillouin scattering effects, respectively. The measured distance is corrected to remove the influence of the pulse width. Additionally, the obtained SNRs are compared for different loop trips and pulse widths, assisting to assess signal quality for SHM applications. KW - Structural health monitoring KW - Distributed fiber sensing KW - Distributed temperature sensing KW - Fiber artefact KW - Spatial correction PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-648966 DO - https://doi.org/10.1088/1361-6501/ae214e VL - 36 IS - 11 SP - 1 EP - 10 PB - IOP Publishing Ltd CY - Bristol, UK AN - OPUS4-64896 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Prager, Jens T1 - Technological and Regulatory Constraints on the Use of Structural Health Monitoring - Our Experience with SHM for Hydrogen Pressure Vessels N2 - Structural Health Monitoring (SHM) is seen as a key component of NDT 4.0. The aim is to replace labour- and cost-intensive periodic inspections with integrated sensor technology and automated data evaluation, and to increase the operational safety and reliability of critical components. Although SHM is already being used to monitor infrastructure components, approaches for technical structures and components have not yet left the laboratory scale, despite intensive efforts. This is particularly the case for aircraft components, pipelines and components in the chemical and process industries. As part of a publicly funded joint project, BAM has attempted to supplement or replace the legally required periodic inspection of high-pressure hydrogen storage tanks with SHM. With regard to a real laboratory "hydrogen refuelling station", different sensor concepts were applied to type IV pressure vessels and the vessels were subjected to accelerated ageing by pressure cycling. The applied monitoring methods were validated against different failure mechanisms. The contribution presents the results of the project and discusses the specific challenges of using SHM approaches in practice. In addition to describing the technological challenges of replacing periodic inspections with SHM, the talk addresses the legal aspects for the operation of pilot plants and real laboratories. As artificial intelligence and machine learning methods are favoured for signal processing, evaluation and assessment of SHM measurement data, the impact of the European AI Act as the first legal framework for AI is also discussed. T2 - SYSINT 2025 CY - Bremen, Germany DA - 04.06.2025 KW - Pressure vessels KW - Structural health monitoring KW - Ultrasound PY - 2025 AN - OPUS4-64526 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Liao, Chun-Man T1 - Assessment of prestress loss in a large-scale concrete bridge model under outdoor condition N2 - The presentation shows that subtle variations in coda wave velocity can capture minor temperature effects, offering a good understanding of how a outdoor prestressed concrete structure responds to environmental conditions over time. Ultimately, this work contributes to development of more comprehensive and resilient structural health monitoring strategies for prestressed concrete infrastructure. T2 - EVACES 2025 CY - Porto, Portugal DA - 02.07.2025 KW - Coda wave interferometry KW - Damage detection KW - Prestress loss KW - Seismic interferometry KW - Structural health monitoring PY - 2025 AN - OPUS4-64211 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Epple, Niklas A1 - Schumacher, Thomas A1 - Murtuz, A. K. M. Golam A1 - Niederleithinger, Ernst A1 - Dusicka, Peter T1 - Combined passive and active ultrasonic stress wave monitoring of a full‑scale laboratory reinforced concrete bridge column subject to reverse‑cyclic lateral loading N2 - Effective monitoring of reinforced concrete structures requires techniques that detect early-stage material change and active, localized cracking. This study investigates a combined structural health monitoring approach using passive acoustic emission and active ultrasonic methods on a full-scale reinforced concrete bridge column subjected to reverse-cyclic lateral loading. Active monitoring, based on coda wave interferometry, was used to track changes in wave velocity and waveforms, while passive acoustic emission monitoring was used to detect crack activity. The instrumentation consisted of three embedded ultrasonic transducers and three surface-mounted acoustic emission sensors. The results show that active ultrasonic monitoring is most effective prior to visual damage, successfully detecting the onset of internal cracking via wave velocity decreases exceeding 0.4%, and distinguishing load-induced effects from permanent damage. However, its utility diminished in later stages of damage progression, as strong signal decorrelation hindered further data interpretation. Additionally, active US measurements allowed a comparison of damage severity in different parts of the column. Conversely, passive acoustic emission monitoring effectively tracked the formation of concrete cracks throughout the experiment, with distinct event clusters and high-amplitude signals (> 60 dB) confirming ongoing fracture processes in all damage states. This study confirms that combining these methods results in a more robust structural health monitoring strategy by leveraging their complementary strengths. Active techniques excel at tracking continuous material changes in early damage states, while passive methods are superior for detecting discrete cracking events as damage progresses. Importantly, both methods can utilize the same measurement equipment, enabling a cost-effective approach to continuous damage tracking. KW - Coda wave interferometry KW - Active ultrasonic monitoring KW - Acoustic emission KW - Structural health monitoring KW - Nondestructive evaluation PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-638689 DO - https://doi.org/10.1007/s13349-025-00996-w SN - 2190-5479 SP - 1 EP - 24 PB - Springer Nature AN - OPUS4-63868 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Simon, Patrick A1 - Schneider, Ronald A1 - Baeßler, Matthias A1 - Morgenthal, Guido T1 - Parallelized adaptive Bayesian updating with structural reliability methods for inference of large engineering models N2 - The reassessment of engineering structures, such as bridges, now increasingly involve the integration of models with realworld data. This integration aims to achieve accurate ‘as-is’ analysis within a digital twin framework. Bayesian model updating combines prior knowledge and data with models to enhance the modelling accuracy while consistently handling uncertainties. When updating large engineering models, numerical methods for Bayesian analysis present significant computational challenges due to the need for a substantial number of likelihood evaluations. The novelty of this contribution is to parallelize adaptive Bayesian Updating with Structural reliability methods combined with subset simulation (aBUS) to improve its computational efficiency. To demonstrate the efficiency and practical applicability of the proposed approach, we present a case study on the Maintalbrücke Gemünden, a large railway bridge. We leverage modal property data to update a linear-elastic dynamic structural model of the bridge. The parallelized aBUS approach significantly reduces computational time, making Bayesian updating of large engineering models feasible within reasonable timeframes. The improved efficiency allows for a wider implementation of Bayesian model updating in structural health monitoring and maintenance decision support systems. KW - Bayesian model updating KW - Bayesian updating with structural reliability methods KW - Structural health monitoring KW - Parallelization KW - Modal analysis KW - Railway bridge PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-633686 DO - https://doi.org/10.1177/13694332251346848 SN - 1369-4332 SN - 2048-4011 SP - 1 EP - 26 PB - Sage AN - OPUS4-63368 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lu, Xin A1 - Schukar, Marcus T1 - Humidity response analysis of optical fibers with hygroscopic coatings based on Lamé’s equations N2 - Optical fibers with hygroscopic coatings are widely used for humidity sensing, where the coating expands upon absorbing water, inducing strain in the fiber. This strain is then used to determine humidity. However, previous studies have oversimplified the strain generation process. A comprehensive three-dimensional model of the mechanical interaction between the coating and the fiber is built based on Lamé’s equations. An analytical expression for the induced strain is derived. The proposed model predicts larger humidity-induced strain compared to the reported ones, given the same Young’s modulus or coefficient of humidity expansion for the coating. Interestingly, the effect of coating thickness on strain response are quite similar for both methods. Experimental validation using fibers with a polyimide coating shows strong agreement with the theoretical predictions. T2 - 29th International Conference on Optical Fiber Sensors CY - Porto, Portugal DA - 26.05.2025 KW - Reflectometry KW - Distributed fiber sensing KW - Humidity sensors KW - Lamé’s equations KW - Optical fiber sensors KW - Structural health monitoring KW - Rayleigh scattering PY - 2025 SN - 978-1-5106-9188-9 DO - https://doi.org/10.1117/12.3060891 VL - 13639 SP - 1 EP - 4 PB - SPIE AN - OPUS4-63257 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Lu, Xin T1 - Humidity response analysis of optical fibers with hygroscopic coatings based on Lamé’s equations N2 - Optical fibers with hygroscopic coatings are widely used for humidity sensing, where the coating expands upon absorbing water, inducing strain in the fiber. This strain is then used to determine humidity. However, previous studies have oversimplified the strain generation process. A comprehensive three-dimensional model of the mechanical interaction between the coating and the fiber is built based on Lamé’s equations. An analytical expression for the induced strain is derived. The proposed model predicts larger humidity-induced strain compared to the reported ones, given the same Young’s modulus or coefficient of humidity expansion for the coating. Interestingly, the effect of coating thickness on strain response are quite similar for both methods. Experimental validation using fibers with a polyimide coating shows strong agreement with the theoretical predictions. T2 - 29th International Conference on Optical Fiber Sensors CY - Porto, Portugal DA - 26.05.2025 KW - Distributed fiber sensing KW - Humidity sensors KW - Lamé’s equations KW - Reflectometry KW - Optical fiber sensors KW - Rayleigh scattering KW - Structural health monitoring PY - 2025 AN - OPUS4-63261 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Karapanagiotis, Christos T1 - Toward a Digital Twin of Hydrogen Pressure Vessels Enabled by Distributed Fiber Optic Sensors N2 - We present a digital replica of a hydrogen pressure vessel enabled by distributed fiber optic sensors (DFOS). This digital replica dynamically displays and updates the vessel’s structural condition by calculating strain residuals defined as the difference between the measured DFOS strain and the expected strain based on pressure data. As an example, we show the ability of the DFOS to detect and localize damage caused by drilling six holes into the vessel’s body. This digital replica represents a foundational step toward a fully integrated digital twin for predictive maintenance and remaining lifetime prognosis. T2 - Sensor and Measurement Science International 2025 CY - Nuremberg, Germany DA - 06.05.2025 KW - Fiber optic sensors KW - Hydrogen KW - Digital twins KW - Structural health monitoring KW - Machine learning KW - Predictive maintenance PY - 2025 AN - OPUS4-63087 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -