ArticleSensors (Basel, Switzerland)2021
Integrated Diagnostic Framework for Process and Sensor Faults in Chemical Industry.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed.
- Early Fault Diagnosis Method for Batch Process Based on Local Time Window Standardization and Trend Analysis.Sensors (Basel, Switzerland) · 2021Article
- Real-Time Fault Detection and Diagnosis of CaCOSensors (Basel, Switzerland) · 2021Article
- Improved Random Forest Algorithm Based on Decision Paths for Fault Diagnosis of Chemical Process with Incomplete Data.Sensors (Basel, Switzerland) · 2021Article
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Authors and funding
3 authors.
Funding
Abstract
This study considers the problem of distinguishing between process and sensor faults in nonlinear chemical processes. An integrated fault diagnosis framework is proposed to distinguish chemical process sensor faults from process faults. The key idea of the framework is to embed the cycle temporal algorithm into the dynamic kernel principal component analysis to improve the fault detection speed and accuracy. It is combined with the fault diagnosis method based on the reconstruction-based contribution graph to diagnose the fault variables and then distinguish the two fault types according to their characteristics. Finally, the integrated fault diagnosis framework is applied to the Tennessee Eastman process and acid gas absorption process, and its effectiveness is proved.
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Registered trials
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