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A fault detection method based on stacking the SAE-SRBM for nonstationary and stationary hybrid processes Cover

A fault detection method based on stacking the SAE-SRBM for nonstationary and stationary hybrid processes

International Journal of Applied Mathematics and Computer Science
Volume 31 (2021): Issue 1 (March 2021)
By: Lei Huang,  Hao Ren,  Yi Chai and  Jianfeng Qu  
Open Access
|Apr 2021

Authors

Lei Huang

School of Computer Science and Technology, Huaiyin Normal University, Huaian City, China

Hao Ren

renhao@cqu.edu.cn

School of Automation, Chongqing University, Chongqing City, China
Peng Cheng Laboratory, Shenzhen City, China

Yi Chai

School of Automation, Chongqing University, Chongqing City, China
Key Laboratory of Complex System Safety and Control Ministry of Education, Chongqing City, China

Jianfeng Qu

School of Automation, Chongqing University, Chongqing City, China
Key Laboratory of Complex System Safety and Control Ministry of Education, Chongqing City, China
DOI: https://doi.org/10.34768/amcs-2021-0003 | Journal eISSN: 2083-8492 | Journal ISSN: 1641-876X
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Language: English
Page range: 29 - 43
Submitted on: Jan 30, 2020
Accepted on: Nov 2, 2020
Published on: Apr 3, 2021
Published by: University of Zielona Góra
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year
Keywords:
fault detection,
sparse auto-encoder,
sparse restricted Boltzmann machine,
hybrid industrial processes
Related subjects:
Mathematics,
Applied mathematics

© 2021 Lei Huang, Hao Ren, Yi Chai, Jianfeng Qu, published by University of Zielona Góra
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

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