TY - JOUR
T1 - On the investigation of nonlinear dynamics of a rotor with rubimpact using numerical analysis and evolutionary algorithms
AU - Abu-Mahfouz, Issam
AU - Banerjee, Amit
N1 - Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2013
Y1 - 2013
N2 - In this paper the dynamics of a rotor-stator system with mass imbalance induced rub-impact interactions is investigated with particular attention on the routes to chaos. The rub-impact interaction is modelled by a Hertz contact radial force and a Coulomb friction tangential force. Extensive numerical experimentation for a wide range of parameters shows the resulting response to be rich in subharmonic, quasiperiodic and chaotic motions. Parameter identification of chaotic systems has become an important topic of research in the past decade. Of particular interest is the problem of identifying or estimating system parameters when the quasiperiodic or chaotic responses of the system are known. The problem of identifying parameters can be cast as an optimization problem and non-traditional optimization methods such as evolutionary algorithms, simulated annealing and others have been developed to identify system parameters. In this paper, three evolutionary algorithms particle swarm optimization, differential evolution and firefly algorithm are presented and compared for the problem of identifying parameters of a rotordynamical system given a chaotic response. The results of this analysis can potentially be of a considerable value as diagnostic tools in assessing condition monitoring signals that are routinely taken on modern rotating machinery.
AB - In this paper the dynamics of a rotor-stator system with mass imbalance induced rub-impact interactions is investigated with particular attention on the routes to chaos. The rub-impact interaction is modelled by a Hertz contact radial force and a Coulomb friction tangential force. Extensive numerical experimentation for a wide range of parameters shows the resulting response to be rich in subharmonic, quasiperiodic and chaotic motions. Parameter identification of chaotic systems has become an important topic of research in the past decade. Of particular interest is the problem of identifying or estimating system parameters when the quasiperiodic or chaotic responses of the system are known. The problem of identifying parameters can be cast as an optimization problem and non-traditional optimization methods such as evolutionary algorithms, simulated annealing and others have been developed to identify system parameters. In this paper, three evolutionary algorithms particle swarm optimization, differential evolution and firefly algorithm are presented and compared for the problem of identifying parameters of a rotordynamical system given a chaotic response. The results of this analysis can potentially be of a considerable value as diagnostic tools in assessing condition monitoring signals that are routinely taken on modern rotating machinery.
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U2 - 10.1016/j.procs.2013.09.252
DO - 10.1016/j.procs.2013.09.252
M3 - Conference article
AN - SCOPUS:84896915717
SN - 1877-0509
VL - 20
SP - 140
EP - 147
JO - Procedia Computer Science
JF - Procedia Computer Science
T2 - 2013 Complex Adaptive Systems Conference, CAS 2013
Y2 - 13 November 2013 through 15 November 2013
ER -