Vibration-Based Detection of Axlebox Bearing Considering Inner and Outer Ring Raceway Defects

Abstract

The occurrence of an axlebox bearing ring raceway defect is an inevitable and commonly observed phenomenon in railway wheels. It not only leads to surface damage but also poses the potential threat of further damage and degradation, thereby increasing the risks associated with running safety and maintenance costs. Hence, it becomes imperative to detect raceway defects at an early stage to mitigate safety hazards and reduce maintenance efforts. In this study, the focus lies in investigating the effectiveness of vibration-based detection techniques for identifying raceway defects in high-speed train axlebox bearing systems. To achieve this, a dynamic model that accurately represents the coupling dynamics between the vehicle and the track is developed. This model incorporates various dynamic factors, such as traction transmission, gear transmission, and track geometry irregularities. By using the comprehensive dynamic model, the dynamic responses of the axlebox can be accurately calculated. The proposed methodology primarily revolves around analysing the vertical vibrations of the axlebox caused by raceway defects in both the time and frequency domains. Additionally, an envelope analysis using a developed band-pass filter is also employed. The results obtained from this study clearly demonstrate the successful detection of raceway defects in a more realistic vehicle model, thereby providing an efficient approach for the detection of axlebox bearing raceway defects. Consequently, this research contributes significantly to the field of high-speed train systems and paves the way for enhanced safety and maintenance practices.