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A novel knowledge enhanced graph neural networks for fault diagnosis with application to blast furnace process safety

  • Published:2022-10 Issue: Volume:166 Page:143-157
  • ISSN:0957-5820
  • Container-title:Process Safety and Environmental Protection
  • language:en
  • Short-container-title:Process Safety and Environmental Protection

Author:

Han Yinghua,Li Qing,Wang Chen,Zhao Qiang

Publisher

Elsevier BV

Subject

Safety, Risk, Reliability and Quality,General Chemical Engineering,Environmental Chemistry,Environmental Engineering

Reference51 articles.

1. A novel data-driven methodology for fault detection and dynamic risk assessment;Amin;Comput. Chem. Eng.,2020

2. A bibliometric review of process safety and risk analysis;Amin;Process. Saf. Environ. Prot.,2019

3. Risk-based fault detection and diagnosis for nonlinear and non- Gaussian process systems using R-vine copula;Amin;Process Saf. Environ. Prot.,2021

4. Robust process monitoring methodology for detection and diagnosis of unobservable faults;Amin;Ind. Eng. Chem. Res.,2019

5. A data-driven Bayesian network learning method for process fault diagnosis;Amin;Process Saf. Environ. Prot.,2021

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