Fault Detection and Identification Based on Explicit Polynomial Mapping and Combined Statistic in Nonlinear Dynamic Processes

Fault Detection and Identification Based on Explicit Polynomial Mapping and Combined Statistic in Nonlinear Dynamic Processes

Single traditional multivariate statistical monitoring methods, such as principal component analysis (PCA) and canonical variate analysis (CVA), are less effective in nonlinear dynamic processes. Monitoring approaches based on radial basis kernel function have been intensively applied. However, an i...

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Autores principales: Liangliang Shang, Kexin Shi, Chen Ma, Aibing Qiu, Liang Hua
Formato: article
Lenguaje:EN
Publicado: IEEE 2021
Materias:
Canonical variate
combined statistic
explicit polynomial mapping
fault detection
fault identification
principal component analysis
Electrical engineering. Electronics. Nuclear engineering
TK1-9971
Acceso en línea:https://doaj.org/article/5608a1053a7f46e3abed2bf0875bacff
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https://doaj.org/article/5608a1053a7f46e3abed2bf0875bacff

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