Techno Press


Smart Structures and Systems   Volume 5, Number 5, September 2009, pages 507-515
DOI: http://dx.doi.org/10.12989/sss.2009.5.5.507
 
Adaptive balancing of highly flexible rotors by using artificial neural networks
M. Villafane Saldarriaga, J. Mahfoud, V. Steffen Jr. and J. Der Hagopian

 
Abstract     [Full Text]
    The present work is an alternative methodology in order to balance a nonlinear highly flexible rotor by using neural networks. This procedure was developed aiming at improving the performance of classical balancing methods, which are developed in the context of linearity between acting forces and resulting displacements and are not well adapted to these situations. In this paper a fully experimental procedure using neural networks is implemented for dealing with the adaptive balancing of nonlinear rotors. The nonlinearity results from the large displacements measured due to the high flexibility of the foundation. A neural network based meta-model was developed to represent the system. The initialization of the learning procedure of the network is performed by using the influence coefficient method and the adaptive balancing strategy is prone to converge rapidly to a satisfactory solution. The methodology is tested successfully experimentally.
 
Key Words
    adaptive balancing; rotating machinery; neural networks; meta-modeling; nonlinear rotor.
 
Address
M. Villafane Saldarriaga; Mechanical Systems Laboratory, School of Mechanical Engineering, Federal University of Uberlandia,38400-902 Uberlandia, Brazil
J. Mahfoud; Laboratoire de Mecanique des Contacts et des Structures, UMR CNRS 5259, Institut National des Sciences Appliquees de Lyon, France
V. Steffen Jr.; Mechanical Systems Laboratory, School of Mechanical Engineering, Federal University of Uberlandia,38400-902 Uberlandia, Brazil
J. Der Hagopian; Laboratoire de Mecanique des Contacts et des Structures, UMR CNRS 5259, Institut National des Sciences Appliquees de Lyon, France
 

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