Development of multiple-step soft-sensors using a Gaussian process model with application for fault prognosis-Reference-Cited by-同舟云学术

Development of multiple-step soft-sensors using a Gaussian process model with application for fault prognosis

Published:2016-10 Issue: Volume:157 Page:85-95
ISSN:0169-7439
Container-title:Chemometrics and Intelligent Laboratory Systems
language:en
Short-container-title:Chemometrics and Intelligent Laboratory Systems

Author:

Liu Yiqi,Xiao Hongjun,Pan Yongping,Huang Daoping,Wang Qilin

Funder

National Natural Science Foundation of China

National Natural Science Foundation of Guangdong, China

Science and Technology Planning Project of Guangdong Province, China

University of Queensland Early Career Research Grant

Philanthropic Grant for Early Career Engineering Researcher

Publisher

Elsevier BV

Subject

Spectroscopy,Process Chemistry and Technology,Computer Science Applications,Software,Analytical Chemistry

Reference40 articles.

1. Plant-wide detection and diagnosis using correspondence analysis;Detroja;Control. Eng. Pract.,2007

2. Statistical signal processing approaches to fault detection;Gustafsson;Annu. Rev. Control.,2007

3. Estimation and diagnosis using multi-models with application to a wastewater treatment plant;Nagy-Kiss;J. Process Control,2013

4. Monitoring nitrate concentrations in the denitrifying post-filtration unit of a municipal wastewater treatment plant;Corona;J. Process Control,2013

5. Semiadaptive fault diagnosis via Variational Bayesian mixture factor analysis with application to wastewater treatment;Hongjun;J. Control Sci. Eng.,2016

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