Applicability Evaluation of Fault Diagnosis Characteristics of Freight Car Axle Bearings through Comparison of Modeling and Laboratory Test Results

To secure the safety and operational reliability of rail freight transportation, there is a growing need for technologies that can detect faults in key freight car components at an early stage and prevent failures in advance. Wheel cracks and axle bearing abnormalities can rapidly deteriorate and lead to catastrophic failures during operation, thereby increasing the risk of serious accidents. However, inspection frameworks centered on periodic maintenance alone have limitations in timely reflecting the occurrence and progression characteristics of such defects, which underscores the need to establish an in-service early detection scheme. In this study, signals generated from a theoretical bearing fault model and field data acquired during freight car operation were processed using the same frequency-domain fault-signal analysis pipeline. The reproducibility of defect-related characteristic frequency components and impulsive responses was then compared to assess field applicability.