Balancing of flexible rotors based on evolutionary algorithms

An unbalance in a rotating flexible rotor causes excessive vibration and elastic deformations with subsequent malfunction and failure. In spite of different techniques deployed to reduce or eliminate rotor unbalance, it is impossible to remove the unbalance completely. The unbalance will only be reduced to a residual level. Hence, any other method that can reduce this residual level further can be considered as an alternative. In this article, Differential Evolution (DE) and Genetic Algorithm (GA) were successfully applied as optimization techniques to balance rotating flexible rotors. The unbalancing challenge is formulated as an optimization problem with an objective function of minimizing the rotor unbalance by identifying the optimum correction parameters. Modeling and response analyses were performed in ANSYS while optimizations were conducted in MATLAB. The results of four balancing cases show that the approaches are robust at both balancing speed and beyond. Also, the results obtained show that GA performs slightly better than DE in terms of optimization time and effective reduction of vibration amplitude.