J
Jochen Moll
Researcher at Goethe University Frankfurt
Publications - 155
Citations - 1609
Jochen Moll is an academic researcher from Goethe University Frankfurt. The author has contributed to research in topics: Structural health monitoring & Radar. The author has an hindex of 15, co-authored 130 publications receiving 1177 citations. Previous affiliations of Jochen Moll include University of Siegen.
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Efficient temperature compensation strategies for guided wave structural health monitoring
TL;DR: In this paper, the authors quantitatively describe two different methods to compensate for the temperature effect, namely optimal baseline selection (OBS) and baseline signal stretch (BSS), and investigate the effect of temperature separation between baseline time traces in OBS and the parameters used in the BSS method.
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Multi-site damage localization in anisotropic plate-like structures using an active guided wave structural health monitoring system
TL;DR: In this article, a distributed sensor network is proposed for structural health monitoring using guided waves in plate-like structures, where each piezoelectric sensor acts in turn as an actuator and a local linear neural network is used to model the nonlinear dispersion curves.
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Open Guided Waves: online platform for ultrasonic guided wave measurements:
Jochen Moll,Jens Kathol,Claus-Peter Fritzen,Maria Moix-Bonet,Marcel Rennoch,Michael Koerdt,Axel S. Herrmann,Markus G. R. Sause,Martin Bach +8 more
TL;DR: In this article, the authors used ultrasonic guided waves to detect damage in isotropic and composite materials with simple and complex geometry, but the limitation of this method was that it was not suitable for structural health monitoring systems.
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Radar-based structural health monitoring of wind turbine blades: The case of damage detection:
Jochen Moll,Philip Arnold,Moritz Mälzer,Viktor Krozer,Dimitry Pozdniakov,Rahmi Salman,Stephan Rediske,Markus Scholz,Herbert Friedmann,Andreas Nuber +9 more
TL;DR: In this paper, the authors introduce a radica-based approach for wind turbine health monitoring with respect to wind turbine blades, which is challenging due to its large dimensions, as well as the complex and heterogeneous material system.
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Towards Three-Dimensional Millimeter-Wave Radar With the Bistatic Fast-Factorized Back-Projection Algorithm—Potential and Limitations
TL;DR: The BiFFBP-approach yields similar results to the GBP with respect to dynamic range in the image and the overall image quality, and it is shown that a resolution of 2 cm can be achieved with relatively few elements, no scanning, and over a large field-of-view.