Full Text Available
Note: Clicking the button above will open the full text document at the original institutional repository in a new window.
Improving the interpretability of causality maps for fault identification
Thesis (MEng)--Stellenbosch University, 2020.
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Thesis |
| Language: | en_ZA |
| Published: |
Stellenbosch : Stellenbosch University
2020
|
| Subjects: | |
| Tags: |
No Tags, Be the first to tag this record!
|
Similar Items: Improving the interpretability of causality maps for fault identification
- Improving the performance of causality analysis techniques for automated fault diagnosis in mineral processing plants
- Applying dynamic Bayesian Networks to process monitoring
- On-line fault detection and end-of-batch quality prediction for batch processes incorporating on-line synchronisation and phase identification
- Process monitoring and fault diagnosis using random forests
- Optimised active fault detection for an open loop stable system
- Exploiting process topology for optimal process monitoring