One-dimensional convolutional auto-encoder-based feature learning for fault diagnosis of multivariate processes-Reference-Cited by-同舟云学术

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One-dimensional convolutional auto-encoder-based feature learning for fault diagnosis of multivariate processes

Published:2020-03 Issue: Volume:87 Page:54-67
ISSN:0959-1524
Container-title:Journal of Process Control
language:en
Short-container-title:Journal of Process Control

Author:

Chen Shumei,Yu Jianbo,Wang Shijin

Funder

National Natural Science Foundation of China

Publisher

Elsevier BV

Subject

Industrial and Manufacturing Engineering,Computer Science Applications,Modelling and Simulation,Control and Systems Engineering

Reference73 articles.

1. Localized fisher discriminant analysis based complex process monitoring;Yu;AIChE J.,2011

2. A data-driven multidimensional visualization technique for process fault detection and diagnosis;Gajjar;Chemom. Intell. Lab. Syst.,2016

3. Distributed PCA model for plant-wide process monitoring;Ge;Ind. Eng. Chem. Res.,2013

4. Process pattern construction and multi-mode monitoring;Zhu;J. Process Control.,2012

5. Multivariate statistical monitoring of process operating performance;Kresta;Can. J. Chem. Eng.,1991

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