A residual autoencoder-based transformer for fault detection of multivariate processes-Reference-Cited by-同舟云学术

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A residual autoencoder-based transformer for fault detection of multivariate processes

Published:2024-09 Issue: Volume:163 Page:111896
ISSN:1568-4946
Container-title:Applied Soft Computing
language:en
Short-container-title:Applied Soft Computing

Author:

Shang Jilin^ORCID,Yu Jianbo^ORCID

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

National Key Research and Development Program of China

National Key Research and Development Program of China Stem Cell and Translational Research

Publisher

Elsevier BV

Reference50 articles.

1. Monitoring and diagnosis process of abnormal consumption on smart power grid;Wan;Neural Comput. Appl.,2018

2. Fault diagnosis and classification framework using multi-scale classification based on kernel Fisher discriminant analysis for chemical process system;Md Nor;Appl. Soft Comput.,2017

3. Fault detection for non-Gaussian processes using generalized canonical correlation analysis and randomized algorithms;Chen;IEEE Trans. Ind. Electron.,2017

4. Adversarial autoencoder based feature learning for fault detection in industrial processes;Jang;IEEE Trans. Ind. Inform.,2022

5. Fault detection for dynamic processes based on recursive innovational component statistical analysis;Ma;IEEE Trans. Autom. Sci. Eng.,2023

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