no code implementations • 8 Oct 2021 • Paolo Climaco, Jochen Garcke, Rodrigo Iza-Teran
We introduce an approach for damage detection in gearboxes based on the analysis of sensor data with the multi-resolution dynamic mode decomposition (mrDMD).
no code implementations • 31 Aug 2020 • Sara Hahner, Rodrigo Iza-Teran, Jochen Garcke
For sequences of complex 3D shapes in time we present a general approach to detect patterns for their analysis and to predict the deformation by making use of structural components of the complex shape.
no code implementations • 10 Mar 2020 • Skylar Sible, Rodrigo Iza-Teran, Jochen Garcke, Nikola Aulig, Patricia Wollstadt
The proposed descriptor provides a novel approach to the parametrization of geometric deformation behavior and enables the use of state-of-the-art data analysis techniques such as machine learning to engineering tasks concerned with plastic deformation behavior.
no code implementations • ICLR 2020 • Amin Abbasloo, Jochen Garcke, Rodrigo Iza-Teran
Long short-term memory (LSTM) networks allow to exhibit temporal dynamic behavior with feedback connections and seem a natural choice for learning sequences of 3D meshes.