Fault isolation based on residual evaluation and contribution analysis

DOI10.1016/j.jfranklin.2016.09.002zbMath1398.93235OpenAlexW2520623594MaRDI QIDQ1796636

Jinglin Zhou, Jing Wang, Wenshuang Ge, Qibing Jin, Hai-Yan Wu

Publication date: 17 October 2018

Published in: Journal of the Franklin Institute (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jfranklin.2016.09.002

zbMATH Keywords

residual evaluationcontribution plotsfault isolationindustrial processesfault evolutionsmearing effect

Mathematics Subject Classification ID

System identification (93B30) Control/observation systems involving computers (process control, etc.) (93C83) Discrete-time control/observation systems (93C55)

Related Items (4)

Fault detection and diagnosis strategy based on k-nearest neighbors and fuzzy C-means clustering algorithm for industrial processes ⋮ Fault diagnosis for a kind of nonlinear systems by using model-based contribution analysis ⋮ A New Residual Evaluation Function Based Fault Diagnosis for a Kind of Nonlinear Systems ⋮ Multiobjective performance-based designs in fault estimation and isolation for discrete-time systems and its application to wind turbines

Cites Work

• Optimal fault detection for linear discrete time-varying systems
• Reconstruction-based contribution for process monitoring
• Closed-loop subspace identification using the parity space
• Parity Space-Based Fault Estimation for Linear Discrete Time-Varying Systems

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