Numerical simulation identifies bearing faults under varying conditions, suggesting improved maintenance strategies.
Rotating Machinery plays a crucial role across various industrial sectors. Bearings are the most crucial essential part that relies on various operations. Condition monitoring techniques have proven helpful in identifying the fault signatures that occur. This paper represents the vibration analysis of a SKF 6206 deep groove ball bearing. Predictive maintenance and scrutiny of a deep groove bearing under varying speeds, as well as defect size. To imitate the presence of faults, a localized defect of rectangular spall type is generated on the outer race of the bearing. Using the numerical simulation method, MATLAB default signatures are studied and compared with the experimental data obtained from the dedicated test rig. The graphs show the presence of default frequencies in the time domain and frequency domain, along with the effect of noise and vibration on them. The results show that the Numerical simulation method of using MATLAB has been proven useful, as it is time-efficient by reducing the need for an extensive procedure of experimentation and breakdown maintenance of that particular part in the industry.
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Gosavi et al. (2026) studied this question.
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