Monitoring and Control of Hydrocyclones by Use of Convolutional Neural Networks and Deep Reinforcement Learning
The use of convolutional neural networks for monitoring hydrocyclones from underflow images was investigated. Proof-of-concept and applied industrial considerations for hydrocyclone state detection and underflow particle size inference sensors were demonstrated. The behaviour and practical considera...
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| Format: | Thesis |
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Curtin University
2022
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| Online Access: | http://hdl.handle.net/20.500.11937/91828 |
| Summary: | The use of convolutional neural networks for monitoring hydrocyclones from underflow images was investigated. Proof-of-concept and applied industrial considerations for hydrocyclone state detection and underflow particle size inference sensors were demonstrated. The behaviour and practical considerations of model-free reinforcement learning, incorporating the additional information provided by the sensors developed, was also discussed in a mineral processing context. |
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