TY - JOUR A1 - Petrat, T. A1 - Kersting, R. A1 - Graf, B. A1 - Rethmeier, Michael T1 - Embedding electronics into additive manufactured components using laser metal deposition and selective laser melting N2 - The paper deals with the integration of a light emitting diode (LED) into an additive manufactured metal component. Selective laser melting (SLM) and laser metal deposition (LMD) are used. The material used is the chrome-nickel steel 316L. The basic component is manufactured by means of SLM and consists of a solid body and an area with grid structure. The solid body includes a duct in the shape of a groove with a recess for the positioning of the power cable. The LED is embedded in the grid structure via an inlet from the solid body. In further processing, the groove is filled with LMD. Two strategies with different parameter combinations were investigated. It shows that a high energy input near the power cable leads to its destruction. By using multiple parameter combinations during the manufacturing process, this destruction can be prevented. There was a comparison of both strategies with regard to the necessary number of tracks and duration of welding time. KW - Additive manufacturing KW - Condition monitoring KW - Process chain KW - Laser-metal-deposition KW - Selektive-laser-melting KW - Embedded electronics PY - 2018 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-479469 DO - https://doi.org/10.1016/j.procir.2018.08.071 SP - 168 EP - 171 PB - Elsevier Ltd. AN - OPUS4-47946 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 - TY - JOUR A1 - Hussels, Maria-Teresa A1 - Chruscicki, Sebastian A1 - Arndt, Detlef A1 - Scheider, Swen A1 - Prager, Jens A1 - Homann, Tobias A1 - Habib, Abdel Karim T1 - Localization of transient events threatening pipeline integrity by fiber-optic distributed acoustic sensing N2 - Pipe integrity is a central concern regarding technical safety, availability, and environmental compliance of industrial plants and pipelines. A condition monitoring system that detects and localizes threats in pipes prior to occurrence of actual structural failure, e.g., leakages, especially needs to target transient events such as impacts on the pipe wall or pressure waves travelling through the medium. In the present work, it is shown that fiber-optic distributed acoustic sensing (DAS) in conjunction with a suitable application geometry of the optical fiber sensor allows to track propagating acoustic waves in the pipeline wall on a fast time-scale. Therefore, short impacts on the pipe may be localized with high fidelity. Moreover, different acoustic modes are identified, and their respective group velocities are in good agreement with theoretical predications. In another set of experiments modeling realistic damage scenarios, we demonstrate that pressure waves following explosions of different gas mixtures in pipes can be observed. Velocities are verified by local piezoelectric pressure transducers. Due to the fully distributed nature of the fiber-optic sensing system, it is possible to record accelerated motions in detail. Therefore, in addition to detection and localization of threatening events for infrastructure monitoring, DAS may provide a powerful tool to study the development of gas explosions in pipes, e.g., investigation of deflagration-to-detonation-transitions (DDT). KW - Distributed acoustic sensing (DAS) KW - Distributed vibrations sensing (DVS) KW - Fiber-optic sensing KW - Condition monitoring KW - Pipeline integrity KW - Gas explosion PY - 2019 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-488555 DO - https://doi.org/10.3390/s19153322 SN - 1424-8220 VL - 19 IS - 15 SP - 3322, 1 EP - 20 PB - MDPI CY - Basel, CH AN - OPUS4-48855 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -