Article ID Journal Published Year Pages File Type
561344 Mechanical Systems and Signal Processing 2012 20 Pages PDF
Abstract

This article investigates the role of bearing preloads on the modal characteristics of a shaft-bearing assembly with a double row angular contact ball bearing. First, an analytical model is developed to comparatively evaluate the effects of axial bearing preloads on the vibratory responses of alternate double row configurations. The analytical model includes bearings via a five dimensional stiffness matrix. Changes in the resonant amplitudes with respect to the bearing preloads are examined for preload-independent and preload-dependent viscous damping models. The bearing preloads significantly affect the vibration characteristics of the shaft-bearing assembly due to major changes in both diagonal and off-diagonal elements of the stiffness matrix, and such effects depend on the bearing configuration. Second, a new experiment consisting of a vehicle wheel bearing assembly with a double row angular contact ball bearing in a back-to-back arrangement is designed. The bearing is subjected to axial or radial preloads in a controlled manner. Experiments with two preloading mechanisms show that the nature and extent of the bearing preloads considerably affect the natural frequencies and resonant amplitudes, thus influencing the vibration behavior of the bearing assembly. Finally, the new bearing stiffness model is validated using measurements from the modal experiment. Suggestions for further work are briefly discussed.

► Analytical model is developed to evaluate effects of axial bearing preloads on vibratory responses. ► Bearing preloads significantly affect the vibration characteristics of the shaft-bearing assembly. ► Experiment with double row angular contact ball bearing in back-to-back arrangement is designed. ► The bearing is subjected to axial or radial preloads in a controlled manner. ► The new bearing stiffness model is validated using measurements from the modal experiment.

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Physical Sciences and Engineering Computer Science Signal Processing
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