Pages that link to "Item:Q509342"
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The following pages link to A novel dynamic non-Gaussian approach for quality-related fault diagnosis with application to the hot strip mill process (Q509342):
Displaying 10 items.
- Fault detection and diagnosis of non-linear non-Gaussian dynamic processes using kernel dynamic independent component analysis (Q903581) (← links)
- A new data-driven process monitoring scheme for key performance indictors with application to hot strip mill process (Q1660329) (← links)
- An efficient quality-related fault diagnosis method for real-time multimode industrial process (Q1794265) (← links)
- KPI relevant and irrelevant fault monitoring with neighborhood component analysis and two-level PLS (Q1796752) (← links)
- A practical propagation path identification scheme for quality-related faults based on nonlinear dynamic latent variable model and partitioned Bayesian network (Q1797198) (← links)
- A key performance indicator-based fault detection scheme for marine diesel turbocharging systems (Q2058025) (← links)
- Fault detection and diagnosis strategy based on k-nearest neighbors and fuzzy C-means clustering algorithm for industrial processes (Q2170729) (← links)
- Quality-relevant fault detection and diagnosis for hot strip mill process with multi-specification and multi-batch measurements (Q2263585) (← links)
- Improved key performance indicator-partial least squares method for nonlinear process fault detection based on just-in-time learning (Q2680244) (← links)
- A novel collaborative diagnosis approach of incipient faults based on VMD and SCN for rolling bearing (Q6078837) (← links)
