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Stochastic Modeling Strategies for the Simulation of Large (Spatial) Distributed Systems
Published in Gabriel A. Wainer, Pieter J. Mosterman, Discrete-Event Modeling and Simulation, 2018
Alexandre Muzy, David R.C. Hill
We have also used an observer pattern to notify the view when we have a state change in the fire model. Indeed, the observer patterns helps in maintaining a list of observers automatically notified of any state change. This is particularly useful in implementing distributed event handling systems. The strategy pattern has also been used to implement a dynamic swap of algorithm particularly when we tested different variants of fire spread. More details on this use for fire spread can be found in [46].
Detection and Characterization of Bearing Faults from the Frequency Domain Features of Vibration
Published in IETE Journal of Research, 2018
P. Arun, S. Abraham Lincon, N. Prabhakaran
Dubey and Agrawal [20] used features of the Hilbert transform of intrinsic mode functions (IMFs) of bearing vibration. The IMF was obtained via empirical mode decomposition (EMD). Average of dynamic time warped, IMF had been illustrated by Sharma and Parey [21] as useful for finding faults in gearbox. Osman and Wang [22] developed a technique based on normalized Hilbert–Huang transform (NHHT) for analyzing non-stationarity of the vibration so as to predict the bearing faults. In this technique, the vibration signal was denoised via maximum kurtosis deconvolution filter to demodulate the effect of impulses in signal transmission path. The most distinctive IMFs were selected with NHHT. The characteristic fault frequencies obtained via universal models were compared with the magnitude spectrum of Hilbert–Huang Transform (HHT) of vibration in Mendel et al. [23]. This was used as the input to sequential forward selection strategy pattern matching algorithm for the fault classification. In another approach termed as morphological Hilbert—Huang, introduced by Osman and Wang [24], the vibration signal was filtered using a structural element for denoising and extracting impulses. The most distinctive envelops obtained via normality measure of IMF. Soualhi et al. [25] compared the IFs obtained from HHT with characteristic frequencies computed by universal models, for characterizing the bearing faults. Saidi et al. [26] also employed the bi-spectrum of the IMFs.