Tuning dynamic vibration absorbers by using ant colony optimization

  • Authors:

  • Felipe Antonio Chegury Viana;Giovanni Iamin Kotinda;Domingos Alves Rade;Valder Steffen, Jr.

  • Affiliations:

  • Federal University of Uberlíndia, School of Mechanical Engineering, 2121 João Naves de Ávila Av., Campus Santa Mônica, CEP, 38400-902, Uberlíndia, Brazil;Federal University of Uberlíndia, School of Mechanical Engineering, 2121 João Naves de Ávila Av., Campus Santa Mônica, CEP, 38400-902, Uberlíndia, Brazil;Federal University of Uberlíndia, School of Mechanical Engineering, 2121 João Naves de Ávila Av., Campus Santa Mônica, CEP, 38400-902, Uberlíndia, Brazil;Federal University of Uberlíndia, School of Mechanical Engineering, 2121 João Naves de Ávila Av., Campus Santa Mônica, CEP, 38400-902, Uberlíndia, Brazil

  • Venue:
  • Computers and Structures
  • Year:
  • 2008

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Abstract

The present contribution deals with the optimal tuning of two different types of dynamic vibration absorbers (DVA) by using ant colony optimization, namely the vibrating blade DVA and the multi-mode DVA. Dynamic vibration absorbers are mechanical appendages constituted by mass, spring and damping elements, which are coupled to a mechanical system to provide vibration attenuation. The tuning of the dynamic vibration absorber is the procedure that sets the anti-resonance frequency to a given value by adjusting the parameters of the dynamic vibration absorber. Based on this methodology, the optimization problem is defined as the minimization of the objective function that describes the vibration amplitude of the primary structure. To solve the optimization problem, ant colony optimization was used. In the early nineties, when the Ant Colony algorithm was first proposed, it was used as an alternative approach for the solution of combinatorial optimization problems, such as the traveling salesman problem. However, the extension for operating with continuous variables is recent and this feature is still under development. In the present formulation, the optimization technique was extended to handle continuous design variables. Numerical results are reported, aiming at illustrating the success of using the proposed methodology, as applied to mechanical system design.