Abstract

The aim of this work is to propose a methodology to optimize the performance of a flexible rotor-bearing system taking into account parameter uncertainties. The idea of the optimization problem is to find the values of a set of parameters (e.g. stiffness of the bearing, diameter, etc.) for which the natural frequencies of the system are as far away as possible from the rotational speeds of the machine. For this purpose, the Campbell diagram is used and penalty functions are introduced to penalize natural frequencies close to the rotational speeds of the machine. Parameter uncertainties are taken into account (e.g. in the stiffness of the bearing, in the elasticity modulus of the material, etc.) and several probabilistic models are considered in the analysis (Gamma, Normal, Uniform, etc.). The global and bounded Nelder–Mead optimization algorithm is employed to minimize the proposed multi-objective function. The methodology proposed in this work is directly extended to complex rotor-bearing systems.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.