TY - JOUR A1 - Köppe, Enrico A1 - Bartholmai, Matthias A1 - Daum, Werner A1 - Gong, Xing A1 - Hofmann, Detlef A1 - Basedau, Frank A1 - Schukar, Vivien A1 - Westphal, Anja A1 - Sahre, Mario A1 - Beck, Uwe T1 - New self - diagnostic fiber optical sensor technique for structural health monitoring N2 - Fiber optic sensors have gained increasing importance in recent years and are well established in many areas of industrial applications. In this paper, we introduce a concept of a self-diagnostic fiber optic sensor. The presented sensor is to resolve the problems of embedded fiber optic sensors in complex structures and to enable the validation under operational conditions. For this purpose, different magnetostrictive coated fiber optic sensors were developed and various experiments were performed to verify their mode of Operation and to determine the respective reproducibility. The measuring principle is illustrated by obtained experimental results, which showed a change in wavelength from 1 pm at a magnetic field strength change of 0.25 mT. In addition, the temperature characteristics of the implemented magnetostrictive sensor were analyzed and an experimental factor of 1.5 compared to a reference fiber optic sensor was determined. T2 - 32nd DANUBIA ADRIA SYMPOSIUM on Advances in Experimental Mechanics CY - Starý Smokovec, Slovakia DA - 22.09.2015 KW - Self-diagnostic fiber optical sensor KW - Magnetostrictive metal coating KW - Magnetic field KW - Fiber bragg grating PY - 2016 U6 - https://doi.org/10.1016/j.matpr.2016.03.038 SN - 2214-7853 VL - 3 IS - 4 SP - 1009 EP - 1013 AN - OPUS4-37131 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Schukar, Vivien A1 - Köppe, Enrico A1 - Hofmann, Detlef A1 - Westphal, Anja A1 - Sahre, Mario A1 - Beck, Uwe A1 - Gong, Xing A1 - Bartholmai, Matthias ED - Aulova, Alexandra ED - Rogelj Ritonja, A. ED - Emri, I. T1 - A contribution to intelligent automatic validation of structure-integrated fibre optic strain sensors N2 - Sensors integrated into devices and structures provide essential data to control, optimize or manage machines and structural components. In the last years, processes, applications and machine parts became more and more intelligent. Consequently, the need for sensor validation increased significantly in order to rely on sensor data and measurement results. Structure-integrated fibre optic strain sensors, such as fiber Bragg gratings (FBG), are of special interest in the composite manufacturing industry. This type of sensor makes it possible to gain information and to collect measurement data about entire production processes and whole life-time cycles of composite-made machine parts and structures. However, validation concepts and approaches for this type of sensors are barely reported in literature. Furthermore, all the reported activities have the drawback that the sensor diagnosis strategy is implemented as limited mathematical models and/or complex time-consuming spectral analysis tools which are applied in data post-processing loops. However, to automate sensor validation and to apply real-time and in-field sensor fault detection, it is necessary to acquire measurement data and information about the measurement reliability at the same time. T2 - 33rd Danubia- Adria Symposium on Advances in Experimental Mechanics CY - Portorož, Slovenia DA - 20.09.2016 KW - Fiber bragg grating KW - Magnetic field KW - Magnetostrictive metal coating KW - Self-diagnostic fiber optical sensor PY - 2016 SN - 978-961-94081-0-0 SP - 180 EP - 181 CY - Ljubljana AN - OPUS4-37645 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -