Model-based fault detection and isolation using neural networks: An industrial gas turbine case study

Proceedings - ICSEng 2011: International Conference on Systems Engineering

Volumn , Issue , 2011, Pages 26-31

  Nozari, Hasan Abbasi ^a   Banadaki, Hamed Dehghan ^a   Shoorehdeli, Mehdi Aliyari ^b   Simani, Silvio ^c  

^a ISLAMIC AZAD UNIVERSITY   (Iran)

^b K N TOOSI UNIVERSITY OF TECHNOLOGY   (Iran)

^c UNIVERSITY OF FERRARA   (Italy)

Author keywords

Fault detection and isolation; industrial gas turbine; Multi layer perceptron; Neural network; Nonlinear predictor model; System identification

Indexed keywords

COMPARATIVE STUDIES; FAULT DETECTION AND ISOLATION; FDI METHOD; INDUSTRIAL GAS TURBINES; MLP MODEL; MLP NEURAL NETWORKS; MODEL-BASED FAULT DETECTION; MULTI LAYER PERCEPTRON; NON-LINEAR DYNAMIC SYSTEMS; NONLINEAR PREDICTOR MODEL; NONLINEAR SIMULATIONS; STEADY-STATE CONDITION; THRESHOLDING;

COMPUTER SIMULATION; DYNAMICAL SYSTEMS; GAS TURBINES; GASES; INDUSTRY; NEURAL NETWORKS; NONLINEAR DYNAMICAL SYSTEMS; SYSTEMS ENGINEERING; TURBOMACHINERY;

FAULT DETECTION;

EID: 80055108342     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICSEng.2011.13     Document Type: Conference Paper

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