Reconstruction of Process Forces in a Five-Axis Milling Center with a LSTM Neural Network in Comparison to a Model-Based Approach
Based on the drive signals of a milling center, process forces can be reconstructed. Therefore, a novel approach is presented to reconstruct the process forces with a long short-term memory neural network (LSTM) using drive signals as an input. The LSTM is evaluated and compared to a model-based app...
Main Authors: | Berend Denkena, Benjamin Bergmann, Dennis Stoppel |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2020-07-01
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Series: | Journal of Manufacturing and Materials Processing |
Subjects: | |
Online Access: | https://www.mdpi.com/2504-4494/4/3/62 |
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