A data-based framework for fault detection and diagnostics of non-linear systems with partial state measurement

Engineering Applications of Artificial Intelligence

Volumn 26, Issue 1, 2013, Pages 446-455

  Subrahmanya, Niranjan ^a   Shin, Yung C ^a  

^a PURDUE UNIVERSITY   (United States)

Author keywords

Condition monitoring; Fault detection and diagnostics; Non linear stochastic observer; Partial state measurement; Recurrent neural networks

Indexed keywords

DYNAMIC NEURAL NETWORKS; FAULT DETECTION AND DIAGNOSTICS; GENERIC SYSTEM; NON-LINEAR OBSERVER; NON-LINEAR STOCHASTIC OBSERVER; OFF-LINE ANALYSIS; OFFLINE; PARTIAL STATE; REAL TIME; STATE VARIABLES; SYNTHETIC PROBLEM; TRAINING DATA;

BENCHMARKING; CHEMICAL INDUSTRY; NONLINEAR SYSTEMS; OBSERVABILITY; PROCESS MONITORING; RECURRENT NEURAL NETWORKS;

CONDITION MONITORING;

EID: 84870056189     PISSN: 09521976     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.engappai.2012.09.004     Document Type: Article

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