Analyzing Vibration Mechanism of Angular Contact Ball Bearing with Compound Faults on Inner and Outer Rings

Abstract

This paper investigates a method to dynamically model compound faults on the inner and outer rings of an angular contact ball bearing as well as their effects on its dynamic behavior. Gupta’s dynamic modeling method is used to consider changes in the deformation and direction of the contact load when the ball passes through the damaged area and to develop a dynamic model of compound faults in the angular contact ball bearing. The step-changing fourth-order Runge–Kutta method is used to solve the dynamic compound fault model. The time-domain signal of vibration responses in the case of a single fault in the inner and outer rings exhibited a certain periodicity, and the frequency of faults in the envelope spectrum was clear. By comparison, the periodicity of compound faults was not clear. The signals of compound faults were decomposed by the dual-tree complex wavelet transform to identify their characteristic frequency. Errors occurred between the characteristic frequency of the theoretical fault and its simulated value. They increased with the rotational speed and decreased with an increase in axial load, whereas the influence of radial load on them was minor. For compound faults on the inner and outer rings of an angular contact ball bearing, this study provides a modeling method that can describe changes in the deformation and direction of the contact load when the ball passes through the damaged area of the inner and outer rings. The work here can provide an important foundation for fault identification in angular contact ball bearings.

Defect Size Evaluation of Cylindrical Roller Bearings with Compound Faults on the Inner and Outer Races

“…If the roller does not enter the damaged area, the contact deformations of the roller and the race can be computed following Chen et al [7]. If it does enter the damaged area, the contact deformations need to be computed, considering the additional deformation resulting from the damage.…”

“…To decrease the possible damage caused by localized defects of the bearings to the system, precise and early recognition is vital. Many di erent signal processing technologies have been applied in identifying the characteristic frequencies of localized defects according to the impulse characteristics of the vibration signals in defective bearings [1], including wavelet and correlation ltering [2,3], time-frequency ridge enhancement [4], intrinsic time-scale decomposition [5], integrated spectral coherence [6], spectral kurtosis [7], and the sparsity-based algorithm [8]. ese methods and relevant variants can inspect faults of rolling-element bearings (REBs), but details concerning defect size are inaccessible.…”