TY - CONF A1 - Auersch, Lutz T1 - A mid-frequency component of train-induced ground vibration due to scattered axle impulses and the irregularities of the soil and ballast N2 - The passage of the train is dominated by the impulses of the static axle loads. The response of the regular homogeneous and irregular soils has been calculated by the finite-element method in frequency domain. The superposition of the impulse responses yields the quasi-static component of the ground vibration which is restricted to very low frequencies and to the close near-field of the track. In case of an irregular soil or ballast of which the stiffness varies randomly in space, a mid-frequency ground vibration component is generated by the scattering of the axle impulses. Measurements will be shown which prove the existence of the mid-frequency ground vibration component and the unique explanation by the scattered axle impulses: many international measurements with a raised mid-frequency component, axle-box measurements with a too low mid-frequency dynamic load, amplitude-speed dependencies which are incompatible with irregularity-induced dynamic loads, and ground vibration reductions due to stiff track elements. T2 - International Conference on Noise and Vibration Engineering (ISMA/USD) CY - Online meeting DA - 07.09.2020 KW - Ground vibration KW - Railway KW - Irregular soil KW - Irregular ballast KW - Axle impulses PY - 2020 SP - 2611 EP - 2625 PB - KULeuven CY - Leuven AN - OPUS4-51210 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Auersch, Lutz T1 - A mid-frequency component of train-induced ground vibration due to scattered axle impulses and the irregularities of the soil and ballast N2 - The passage of the train is dominated by the impulses of the static axle loads. The response of the regular homogeneous and irregular soils has been calculated by the finite-element method in frequency domain. The superposition of the impulse responses yields the quasi-static component of the ground vibration which is restricted to very low frequencies and to the close near-field of the track. In case of an irregular soil or ballast of which the stiffness varies randomly in space, a mid-frequency ground vibration component is generated by the scattering of the axle impulses. Measurements will be shown which prove the existence of the mid-frequency ground vibration component and the unique explanation by the scattered axle impulses: many international measurements with a raised mid-frequency component, axle-box measurements with a too low mid-frequency dynamic load, amplitude-speed dependencies which are incompatible with irregularity-induced dynamic loads, and ground vibration reductions due to stiff track elements. T2 - International Conference on Noise and Vibration Engineering (ISMA/USD 2020) CY - Online meeting DA - 07.09.2020 KW - Ground vibration KW - Railway KW - Irregular soil KW - Irregular ballast KW - Axle impulses PY - 2020 AN - OPUS4-51212 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Herrmann, Ralf T1 - SHM system integration and experiments at a high speed railway bridge N2 - The long-term preservation of our infrastructure requires not only intelligent sensor technology and highly developed monitoring procedures, but also innovative digital tools for analyzing, evaluating and utilizing the results. This includes mathematical and, in particular, probabilistic methods for damage detection and tracking as well as for calculating service life and maintenance cycles and data management. The example project Maintal Bridge Gemuenden as part of the AISTEC project shows the workflow for the implementation of structural health monitoring and experimental tests with a train of Deutsche Bahn. The influence lines, as one possible way for damage detection, were measured with a highly accurate GNSS System to locate the trains position when crossing the bridge. The results were compared to measurements from 1987 just before the bridge went in operation. T2 - Structural Health Monitoring Using Statistical Pattern Recognition CY - Berlin, Germany DA - 20.03.2023 KW - SHM KW - Maintal Bridge Gemuenden KW - Load Test KW - Damage Detection KW - Railway PY - 2023 AN - OPUS4-57242 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Baasch, Benjamin A1 - Groos, Jörn A1 - Heusel, Judith A1 - Noll, Martin T1 - Data-driven sparse coding for onboard condition monitoring of railway tracks N2 - Continuous monitoring of the rail condition plays an important role in railway maintenance and the planning of noise- and vibration-reducing measures. Rail monitoring can be carried out efficiently using vibro-acoustic measurements with onboard sensors. However, this approach generates large amounts of acoustic and vibration data, which makes real-time transmission, processing and storage a challenge. This paper presents a sparse coding framework applied in the time–frequency domain that aims to overcome these challenges by significantly reducing the amount of data while preserving important information for rail defect detection and diagnosis. The Short-Time Fourier Transform is used as a preprocessing step to transform raw signals into a time–frequency representation, capturing the non-stationary characteristics of the signals. The spectrum at each time window is then represented by a sparse linear combination of basis spectra, which form a dictionary. Online sparse dictionary learning is used to create a data-driven, adaptive representation tailored to the frequency characteristics of vibro-acoustic signals related to rail defects. Experimental data acquired with a microphone and an accelerometer mounted on the wheelset of a tram are used to evaluate the framework. The experimental results show that the framework is able to achieve high compression rates and reduce noise. A reduction in data size of 98% was obtained without loss of relevant information. The proposed approach offers significant advantages for modern railway condition monitoring systems. It is scalable for large amounts of data, energy efficient and suitable for real-time implementation. By reducing data bottlenecks, it enables efficient track monitoring with on-board sensors. This work thus contributes to the development of intelligent and cost-effective solutions for infrastructure management. KW - Railway KW - Noise and vibration KW - Condition monitoring KW - Sparse coding KW - Sparse dictionary learning KW - Compressed sensing PY - 2025 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-645038 DO - https://doi.org/10.1016/j.ymssp.2025.113542 SN - 0888-3270 VL - 241 SP - 1 EP - 13 PB - Elsevier Ltd. AN - OPUS4-64503 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -