Elman's recurrent neural network applications to condition monitoring in nuclear power plant and rotating machinery

A Review Study on Mathematical Methods for Fault Detection Problems in Induction Motors

“…Data acquisition system has a low-pass filter with the cutoff frequency at 4 kHz. The coherence function (Fig.8) indicates that the most dominant frequency values, where motor current and vibration signals are correlated, are located at 234 Hz and 469 Hz (8)(9) . The side-band frequency due to the dynamic eccentricity is fecc = 60 + 6(29.03) = 234 Hz.…”

“…Air gap eccentricity may be the consequence of bearing, wear or bearing failure, bad motor assembly with rotor unbalance or a rotor which is not perfectly centered (4,(8)(9) . This eccentricity causes anomalies in the air gap flux density and creates frequency side bands at around the supply frequency of the stator current signal for each phase.…”

“…(1)(2)(3)(4)(5)(6)(7) This paper addresses fault detection methods in induction motors together with theory and applications on experimental data acquired during performance test of the motors subjected to accelerated aging (6)(7) . Detection of eccentricity fault (7)(8)(9) , bearing fault (10)(11)(12)(13)(14)(15)(16)(17)(18) , and stator insulation fault (19)(20) is considered. Applications of statistical methods, power spectral density analysis, coherence analysis, continuous and discrete wavelet transform, autoregressive modeling method, adaptive neuro-fuzzy inference system, artificial neural network is presented by means of the experimental data.…”

Case Studies for Applications of Elman Recurrent Neural Networks

“…Learning and generalization ability, fast real time operation and ease of implementation features have made RNNs popular in the last decade. Recent works by nuclear engineering researchers demonstrated the ability of RNNs in identification of complex nonlinear plants like nuclear reactor cores (Boroushaki et al, 2002;Adalı et al, 1997;Boroushaki et al, 2003;Şeker et al, 2003;Ortiz & Requena, 2004). Übeyli & Übeyli (2007) used the Elman RNNs for the estimation of the neutronic parameters of a thorium fusion breeder.…”

Elman neural network for modeling and predictive control of delayed dynamic systems

“…they may be used to estimate pilot workload [8], to monitor condition in nuclear power plant and rotating machinery [29], to predict geomagnetic storms from solar wind data [31], for electric load forecasting [32], for short-term temperature forecasting [17], for modeling the flow of passengers in subway [18] and for identification of the grammatical structure of literary works [19]. A comparison of MLP, RBF and Elman dynamic models is given in [4].…”