Causal intervention graph neural network for fault diagnosis of complex industrial processes

Ruonan Liu; Quanhu Zhang; Di Lin; Weidong Zhang; Steven X. Ding

doi:10.1016/j.ress.2024.110328

ScienceGate Book Chapters

JOURNAL ARTICLE

Causal intervention graph neural network for fault diagnosis of complex industrial processes

Ruonan Liu Quanhu Zhang Di Lin Weidong Zhang Steven X. Ding

Year: 2024 Journal: Reliability Engineering & System Safety Vol: 251 Pages: 110328-110328 Publisher: Elsevier BV

DOI: 10.1016/j.ress.2024.110328

Get Full-Text PDF Get Analytical Report

Keywords:

Artificial neural network Fault (geology) Intervention (counseling) Computer science Graph Artificial intelligence Machine learning Theoretical computer science Psychology Geology Psychiatry

Metrics

Cited By

24.81

FWCI (Field Weighted Citation Impact)

Refs

0.99

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Fault Detection and Control Systems

Physical Sciences → Engineering → Control and Systems Engineering

Engineering Diagnostics and Reliability

Physical Sciences → Engineering → Mechanics of Materials

Machine Fault Diagnosis Techniques

Physical Sciences → Engineering → Control and Systems Engineering

Causal intervention graph neural network for fault diagnosis of complex industrial processes

Metrics

Citation History

Topics

Related Documents

Causal-Trivial Attention Graph Neural Network for Fault Diagnosis of Complex Industrial Processes

Causal Disentangled Graph Neural Network for Fault Diagnosis of Complex Industrial Process

Information-based Gradient enhanced Causal Learning Graph Neural Network for fault diagnosis of complex industrial processes

Deep Graph Convolutional Neural Network for Fault Diagnosis of Complex Industrial Processes

Causal Regularization Graph Attention Network for Stable Variables Decoupling and Fault Diagnosis of Complex Industrial Processes