Identification of Bearing Clearance in Sugar Centrifuge Using Dimension Theory and Support Vector Machine on Vibration Measurement

Abstract

Bearing fatigue life is significantly influenced by bearing clearance. Vibration monitoring of bearing clearance deviations can efficiently reveal bearing wear and give sufficient lead time for maintenance. This study investigates the dynamics of roller bearings utilizing the dimension theory with the support vector machine (SVM) technique for diagnosing the bearing clearance faults of revolving machines. The generation of local defects in rotating machines is closely related to the clearance behavior of the rotor-bearing system. A dynamic model of bearing with dimension theory by matrix method with SVM is developed for characteristics of bearing clearance considering the influence of local defects on the inner and outer bearings races. The characteristics of bearing internal radial clearance considering the impact of the defect on the bearing are analyzed. An experimental study has been performed to capture the vibration signature of radial clearance for different speeds and radial loads of the rotor. The rotor-bearing system equations are numerically integrated, and the results are validated with experimental findings. The collective effects among the four parameters (radial load, speed, defect size, radial clearance) are investigated in detail for the rotor-bearing system. The noisy signal is subsequently eliminated using the modulation signal bispectrum (MSB), and the peaks of the MSB results are represented by the bearing clearance indicator. The efficiency and reliability of the stated approach are evaluated using a specialized bearing test and a run-to-failure sugar centrifuge test. The results suggest that the proposed approach can detect a change in bearing clearance up to 40 µm.