Abstract—Early fault identification in rolling-element bearings is critical for averting failures. While measuring overall vibration levels at the bearing housing offers a simple diagnostic method, spectrum analysis provides a more advanced and precise early warning. This study introduces an innovative approach to detecting, analyzing, and diagnosing bearing defects by comparing time-domain, frequency-domain, and spectrum plot analyses. By examining spectral variations under normal conditions and in the presence of outer and inner race faults, this research enhances the accuracy and reliability of fault diagnosis.

Keywords—detection of rolling element bearing flaws, time domain, frequency domain, spectrum plot approaches

Cite: Vinayak V. Kulkarni and Shylesha Channapattana, "Advanced Diagnosis of Bearing Defects: A Multi-Domain Approach," International Journal of Mechanical Engineering and Robotics Research, Vol. 14, No. 4, pp. 436-444, 2025. doi: 10.18178/ijmerr.14.4.436-444

Copyright © 2025 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).