Holobalancing Method and Its Improvement by Reselection of Balancing Object

Abstract

Based on the idea of multi-sensor information fusion, one of the main problem—insufficient utilization of rotor vibration information—existing in the traditional rotor balancing methods is solved. By integration of all the amplitude, frequency and phase information, the Holobalancing method can help to correct the rotor balancing state more accurately and efficiently than other traditional methods. The field balancing capability has been greatly improved therefore. Since the Holobalancing method truly considers the characteristics of system support stiffness anisotropy, the unreasonable isotropic assumption adopted in traditional balancing methods is no longer required therefore. The balancing result of the Holobalancing method is more reliable and fewer number of trial runs is needed. Recently, the Holobalancing method is further improved by reselection of balancing object. With the Initial Phase Vector (IPV) being replaced by its forward precession component (IPV+), the impact of probe orientation on the balancing analysis and calculation is completely eliminated and the computational procedure is greatly simplified without sacrificing the balancing accuracy. The experiments and field application cases verify the effectiveness and reliability of this method.