Balancing multiple speeds flexible rotors without trial weights using multi-objective optimization

Abstract This paper proposes a multi-objective optimization method for the optimal balancing of flexible rotors without using trial weights. Finite elements are first used to develop a dynamic model of the flexible rotor. An optimization method and an inverse identification approach are then used to minimize the objective function by considering constraints and vibration levels of the flexible rotor during balancing. Finally, an optimal balancing scheme is solved by using a genetic algorithm. The optimization process here described consists in a global multi-objective optimization framework transformed into single-objective (SO) and dual-objective (DO) optimizations. Simulations and experiments are carried out on a three-discs flexible rotor balancing rig without trial weights, to benchmark the multi-objective optimization technique proposed here. The results show that the method is efficient to avoiding multiple starts and stops during the balancing process, and also provides an enhanced balancing effect.