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Titel:

Deep learning-based position detection for hydraulic cylinders using scattering parameters

Dokumenttyp:
Zeitschriftenaufsatz
Autor(en):
Xin, Chen; Motz, Thomas; Fuhl, Wolfgang; Hartel, Andreas; Kasneci, Enkelejda
Abstract:
Position detection of hydraulic cylinder pistons is crucial for numerous industrial automation applications. A typical traditional method is to excite electromagnetic waves in the cylinder structure and analytically solve the piston position based on the scattering parameters measured by a sensor. The core of this approach is a physical model that outlines the relationship between the measured scattering parameters and the targeted piston position. However, this physical model has shortcomings i...     »
Stichworte:
Deep learning, Convolutional neural network, Complex-valued neural network, Frequency encoding, Position detection, Scattering parameter
Zeitschriftentitel:
Expert Systems with Applications
Jahr:
2023
Band / Volume:
232
Seitenangaben Beitrag:
120892
Volltext / DOI:
doi:10.1016/j.eswa.2023.120892
WWW:
https://www.sciencedirect.com/science/article/pii/S0957417423013945
Print-ISSN:
0957-4174
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