Fault Diagnosis of Tennessee Eastman Process with XGB-AVSSA-KELM Algorithm

Fault Diagnosis of Tennessee Eastman Process with XGB-AVSSA-KELM Algorithm

In fault detection and the diagnosis of large industrial systems, whose chemical processes usually exhibit complex, high-dimensional, time-varying and non-Gaussian characteristics, the classification accuracy of traditional methods is low. In this paper, a kernel limit learning machine (KELM) based...

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Bibliographic Details
Main Authors: Mingfei Hu, Xinyi Hu, Zhenzhou Deng, Bing Tu
Format: Article
Language:English
Published: MDPI AG 2022-04-01
Series:Energies
Subjects:
fault diagnosis
Tennessee Eastman process
KELM
XGBOOST
AVSSA
feature selection
Online Access:https://www.mdpi.com/1996-1073/15/9/3198

Internet

https://www.mdpi.com/1996-1073/15/9/3198

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