Application of Robust Regression Methods to Rotor Balancing Using High Breakdown Point and Bounded-Influence Estimators

Abstract

In industrial field, the main practical problem of rotating machinery concerns rotor balancing. Balancing masses are often selected by means of weighted least squares method. The weighted method allows reducing the amplitude of vibrations at selected rotating speeds such as critical speeds or operating conditions. Usually these weights are manually selected by the operator. In this paper, an automatic procedure based on robust regression methods is introduced. In particular the analysis is focused on high breakdown point and bounded-influence estimators. Theoretical aspects and properties of these methods are investigated. The effectiveness and robustness of the proposed procedure is shown by means of simulations of a 180 MW gas turbo-generator of a power plant. Different unbalance conditions are considered as well as data corruption.