Rotor Balancing with Turbine Blade Assembly Using Ant Colony Optimization for Aero-Engine Applications

Abstract

The purpose of this paper is to present a novel turbine balancing using Ant Colony Optimization method. Results are compared against well known optimization methods available at open literature. With the new approach, turbine blade set can be separated in to two blade sets as heavy and light blades. This approach makes possible the application of Ant Colony Optimization methodology. ACO methodology is compared with Steepest Descent and Exchange Heuristic methods using nine different initial blade placements. And results are presented. Performance of the three evaluated methods is affected by the initial blade placement. Exchange Heuristics method was quick and provided good results in most of the cases. Ant colony optimization was able find better results than the Steepest Descent method. The approach of separating blades into two sets decreased the solution time of Steepest Descent algorithm. Ant colony optimization method can be used for turbine blade assembly and balancing for aircraft gas turbine applications. This approach is used for the first time in this area and not seen at the open literature