Fault detection based on augmented kernel Mahalanobis distance for nonlinear dynamic processes

Computers & Chemical Engineering ◽

10.1016/j.compchemeng.2017.11.010 ◽

2018 ◽

Vol 109 ◽

pp. 311-321 ◽

Author(s):

Jun Shang ◽

Maoyin Chen ◽

Hanwen Zhang

Keyword(s):

Fault Detection ◽

Mahalanobis Distance ◽

Nonlinear Dynamic ◽

Dynamic Processes ◽

Nonlinear Dynamic Processes

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Fault detection of nonlinear dynamic processes using dynamic kernel principal component analysis

2008 7th World Congress on Intelligent Control and Automation ◽

10.1109/wcica.2008.4593402 ◽

2008 ◽

Author(s):

Ting Wang ◽

Xiaogang Wang ◽

Yingwei Zhang ◽

Hong Zhou

Keyword(s):

Principal Component Analysis ◽

Fault Detection ◽

Nonlinear Dynamic ◽

Principal Component ◽

Component Analysis ◽

Kernel Principal Component Analysis ◽

Dynamic Processes ◽

Nonlinear Dynamic Processes

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Fault detection and identification based on explicit polynomial mapping and combined statistic in nonlinear dynamic processes

IEEE Access ◽

10.1109/access.2021.3124948 ◽

2021 ◽

pp. 1-1

Author(s):

Liangliang Shang ◽

Kexin Shi ◽

Chen Ma ◽

Aibing Qiu ◽

Liang Hua

Keyword(s):

Fault Detection ◽

Nonlinear Dynamic ◽

Dynamic Processes ◽

Polynomial Mapping ◽

Detection And Identification ◽

Fault Detection And Identification ◽

Nonlinear Dynamic Processes

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Fault detection based on auto-regressive extreme learning machine for nonlinear dynamic processes

Applied Soft Computing ◽

10.1016/j.asoc.2021.107319 ◽

2021 ◽

Vol 106 ◽

pp. 107319

Author(s):

Yang Chen ◽

Chudong Tong ◽

Yinghui Ge ◽

Ting Lan

Keyword(s):

Fault Detection ◽

Extreme Learning Machine ◽

Nonlinear Dynamic ◽

Dynamic Processes ◽

Auto Regressive ◽

Learning Machine ◽

Nonlinear Dynamic Processes

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Generalized Polynomial Chaos-Based Fault Detection and Classification for Nonlinear Dynamic Processes

Industrial & Engineering Chemistry Research ◽

10.1021/acs.iecr.5b04694 ◽

2016 ◽

Vol 55 (7) ◽

pp. 2069-2082 ◽

Author(s):

Yuncheng Du ◽

Thomas A. Duever ◽

Hector Budman

Keyword(s):

Fault Detection ◽

Nonlinear Dynamic ◽

Polynomial Chaos ◽

Dynamic Processes ◽

Generalized Polynomial Chaos ◽

Fault Detection And Classification ◽

Generalized Polynomial ◽

Nonlinear Dynamic Processes

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Vibration-Based Diagnostics and Structural Analysis of Research on Nonlinear Dynamic Processes in Maglev-Suspension Rotor Turbomachines

Дефектоскопия ◽

10.1134/s0130308218070059 ◽

2018 ◽

Keyword(s):

Structural Analysis ◽

Nonlinear Dynamic ◽

Dynamic Processes ◽

Nonlinear Dynamic Processes

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Robust end-point optimizing feedback for nonlinear dynamic processes

International Journal of Control ◽

10.1080/00207179608921734 ◽

1996 ◽

Vol 65 (6) ◽

pp. 995-1014 ◽

Author(s):

PETER TERWIESCH ◽

ALESSANDRO ASTOLFI

Keyword(s):

Nonlinear Dynamic ◽

Dynamic Processes ◽

End Point ◽

Nonlinear Dynamic Processes

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Nonlinear Dynamic Processes in Laser-Induced Transitions to Low-Dimensional Carbon Nanostructures in Bulk Graphite Unit

New Trends in Nonlinear Dynamics ◽

10.1007/978-3-030-34724-6_14 ◽

2020 ◽

pp. 131-139

Author(s):

Kirill Khorkov ◽

Dmitriy Kochuev ◽

Ruslan Chkalov ◽

Valery Prokoshev ◽

Sergei Arakelian

Keyword(s):

Nonlinear Dynamic ◽

Carbon Nanostructures ◽

Dynamic Processes ◽

Bulk Graphite ◽

Low Dimensional ◽

Nonlinear Dynamic Processes

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Nonlinear Dynamic Processes

General Biophysics ◽

10.1016/b978-0-12-723002-3.50007-2 ◽

1983 ◽

pp. 125-208

Author(s):

M.V. Volkenstein

Keyword(s):

Nonlinear Dynamic ◽

Dynamic Processes ◽

Nonlinear Dynamic Processes

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OPTIMAL SCHEDULING FOR LINEAR AND NONLINEAR DYNAMIC PROCESSES

Automatic Control 1990 ◽

10.1016/b978-0-08-041263-4.50089-0 ◽

1991 ◽

pp. 517-521

Author(s):

W. Wajs

Keyword(s):

Nonlinear Dynamic ◽

Optimal Scheduling ◽

Dynamic Processes ◽

Linear And Nonlinear ◽

Nonlinear Dynamic Processes

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Near-Epoch Dependence

10.1093/oso/9780192844507.003.0018 ◽

2021 ◽

pp. 368-398

Author(s):

James Davidson

Keyword(s):

Theoretical Result ◽

Nonlinear Dynamic ◽

Dynamic Processes ◽

Related Concept ◽

Mixing Processes ◽

Special Result ◽

Nonlinear Dynamic Processes

Near‐epoch dependence (NED) is a generalized dependence concept for functions of mixing processes. This chapter gives definitions and examples, and considers the application to nonlinear dynamic processes. The relation to mixingales is the key theoretical result. Results on the preservation of NED under various transformations and a special result for the adapted sequence case are considered next. Finally, the related concept of approximability is defined which, unlike NED, can hold in the absence of integer moments.

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