Robust Balancing Approach for Rotating Machines Based on Fuzzy Logic

Abstract

Unbalance is one of the most common malfunctions found in rotating machines generating high vibration amplitudes that can lead to fatigue and wear of rotor elements. There are several well-known balancing techniques wherein one of the most widespread approaches is the so-called influence coefficients method (IC method). Aiming to increase the robustness of the standard IC method, in this paper, a revised IC balancing methodology for rotating machines is proposed. In this sense, a preprocessing stage is applied to access the uncertainties affecting the rotating machine. In this sense, measurement data sets evaluated under the fuzzy logic approach are used. Thus, the rotor vibration responses measured over a long period are considered by means of a fuzzy transformation (defining unbalance fuzzy sets). The unbalance condition of the rotating machine is determined through a defuzzification process. This unbalance condition is then introduced in the IC method algorithm aiming at obtaining correction weights and associated angular positions that increase the balancing robustness as compared with the classical approach. Numerical and experimental studies are used to evaluate the effectiveness of the proposed methodology. The obtained results illustrate the capacity to increase the balancing overall robustness.