Fault Severity Classification and Size Estimation for Ball Bearings Based on Vibration Mechanism

Abstract

Severity identification and size estimation is a crucial part of the quantitative diagnosis for ball bearing faults. In this paper, novel fault severity classification rules and the size estimation model based on vibration mechanism for ball bearings are proposed for more accurate estimation of the fault size. A nonlinear dynamic model, with geometric properties and deformation of the ball considered, is established to analyze the vibration characteristics of ball bearing with outer race fault. It turns out that there are different features in vibration responses with different fault sizes, and then the fault severity is classified with vibration features. Based on the vibration mechanism analysis, functional relations and mathematical expressions between the vibration characteristics and fault sizes are inferred to realize the quantitative diagnosis of faulty bearings. The experiments are performed to verify the effectiveness of the proposed method of fault severity classification and size estimation. Deep groove ball bearings designated as 6308, with seeded square-shaped surface defects of different sizes, are chosen for the experiments. The results show that the proposed method can accurately estimate the fault sizes within the acceptable error range.

Keywords

• Ball bearing
• nonlinear dynamic modeling
• vibration mechanism
• fault severity classification
• fault size estimation