Fault Diagnosis for TE Process Using RBF Neural Network

Fault Diagnosis for TE Process Using RBF Neural Network

Fault diagnosis of industrial process has long been a challenging issue owing to the industrial system that exhibits nonlinearity, coupled parameters and time-varying in the production process. This paper presents a novel dynamic fault diagnosis model (AUKF-RBF) based on radial basis function (RBF)...

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Bibliographic Details
Main Authors: Xin Liu, Hai He
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Fault diagnosis
radial basis function
unscented Kalman filter
Tennessee Eastman process
dynamic modeling
Online Access:https://ieeexplore.ieee.org/document/9521500/

Internet

https://ieeexplore.ieee.org/document/9521500/

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