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Sensor and Actuator Fault Diagnosis for Robot Joint Based on Deep CNN
This paper proposes a data-driven method-based fault diagnosis method using the deep convolutional neural network (DCNN). The DCNN is used to deal with sensor and actuator faults of robot joints, such as gain error, offset error, and malfunction for both sensors and actuators, and different fault ty...
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| Veröffentlicht in: | Entropy (Basel) |
|---|---|
| Hauptverfasser: | , , |
| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
MDPI
2021
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| Schlagworte: | |
| Online Zugang: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8232324/ https://ncbi.nlm.nih.gov/pubmed/34203708 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/e23060751 |
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