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Keywords: transfer learning
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Proceedings Papers

Proc. ASME. IDETC-CIE2022, Volume 3A: 48th Design Automation Conference (DAC), V03AT03A048, August 14–17, 2022
Paper No: DETC2022-89932
... Abstract Phononic metamaterials are widely used to attenuate wave propagation. However, designing the structure of phononic metamaterial remains a challenge. In this work, we proposed a transfer learning-based design framework to accelerate the design of phononic metamaterials with wide...
Proceedings Papers

Proc. ASME. IDETC-CIE2022, Volume 2: 42nd Computers and Information in Engineering Conference (CIE), V002T02A082, August 14–17, 2022
Paper No: DETC2022-88223
... utilized to conduct GT design space exploration and condition monitoring. However, ML has not been implemented to improve the efficiency of GT manufacturing processes, mainly due to data scarcity. The authors propose a combined feature learning and transfer learning technique to leverage the data resources...
Proceedings Papers

Proc. ASME. IDETC-CIE2022, Volume 2: 42nd Computers and Information in Engineering Conference (CIE), V002T02A013, August 14–17, 2022
Paper No: DETC2022-89300
... becomes an obstacle to achieve high quality models. Transfer learning (TL) is a new and promising approach that the model of one product (source) may be reused for another product (target) with limited new data on the target. This paper focuses on reviewing applications of TL in AM modeling in order...
Proceedings Papers

Proc. ASME. IDETC-CIE2022, Volume 2: 42nd Computers and Information in Engineering Conference (CIE), V002T02A003, August 14–17, 2022
Paper No: DETC2022-89452
... Abstract This contribution introduces a Transfer Learning (TL) approach for the diagnostic task to distinguish the ingredients of a typical production machine element: metalworking fluid (MWF). Metalworking fluids are oil or water-based fluids used during machining and shaping of metals...
Proceedings Papers

Proc. ASME. IDETC-CIE2021, Volume 10: 33rd Conference on Mechanical Vibration and Sound (VIB), V010T10A012, August 17–19, 2021
Paper No: DETC2021-67773
... DISTINCT DATASET TRANSFER LEARNING Justin Larocque-Villiers, Patrick Dumond University of Ottawa Ottawa, Canada ABSTRACT 1. INTRODUCTION Through the intelligent classification of bearing faults, The development of data-driven techniques and machine predictive maintenance provides for the possibility...
Proceedings Papers

Proc. ASME. IDETC-CIE2021, Volume 8B: 45th Mechanisms and Robotics Conference (MR), V08BT08A049, August 17–19, 2021
Paper No: DETC2021-69006
...Abstract Abstract In this paper, an artificial neural network (ANN) based transfer learning approach of inverse displacement analysis of robot manipulators is studied. ANNs with different structures are applied utilizing data from different end effector paths of a manipulator for training...
Proceedings Papers

Proc. ASME. IDETC-CIE2021, Volume 3A: 47th Design Automation Conference (DAC), V03AT03A038, August 17–19, 2021
Paper No: DETC2021-67963
... Proceedings of the ASME 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference IDETC-CIE2021 August 17-19, 2021, Virtual, Online DETC2021-67963 POINT-CLOUD NEURAL NETWORK USING TRANSFER LEARNING-BASED MULTI-FIDELITY METHOD FOR THERMAL...
Proceedings Papers

Proc. ASME. IDETC-CIE2020, Volume 10: 44th Mechanisms and Robotics Conference (MR), V010T10A093, August 17–19, 2020
Paper No: DETC2020-22508
...NEURAL NETWORK BASED TRANSFER LEARNING OF MANIPULATOR INVERSE DISPLACEMENT ANALYSIS Houcheng Tang1, Leila Notash Queen s University, Kingston, ON, Canada ABSTRACT In this paper, a neural network based transfer learning approach of inverse displacement analysis of robot manipulators is studied...
Proceedings Papers

Proc. ASME. IDETC-CIE2020, Volume 11A: 46th Design Automation Conference (DAC), V11AT11A041, August 17–19, 2020
Paper No: DETC2020-22203
... bearing fault diagnosis optimization transfer learning sensor fusion convolutional neural network Abstract Abstract Accurate fault defection of bearing is critical in condition-based maintenance to improve system reliability and reduce operational cost. This paper introduces a deep...