Multiple Input CNN Architecture for Tool State Recognition in the Milling Process Based on Time Series Signals
The study presents a tailored application of a multiple-input convolutional neural network (CNN) for tool state recognition in the milling process. Our approach uniquely applies an 11-input CNN to classify tool wear in chipboard milling, utilizing scalogram images derived from time-series signals. T...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wrocław University of Science and Technology
2024-01-01
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| Series: | Operations Research and Decisions |
| Online Access: | https://ord.pwr.edu.pl/assets/papers_archive/ord2024vol34no3_3.pdf |
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