مقایسه عملکرد سیگنال‌های صوتی و ارتعاشی در عیب‌یابی یاتاقان غلتشی

Rolling element bearings are key components of rotating machinery, and their faults can lead to system downtime. This study compares the performance of sound (non-contact) and vibration (contact) signals in detecting faults in rolling element bearings using a laboratory dataset. The data utilized include healthy and faulty conditions of the rolling element bearing (faults in the inner and outer races). To this end, 12 statistical features in the time and frequency domains were extracted from the sound and vibration signals. The results indicate that features derived from vibration signals were more sensitive to changes in health status; however, features such as root mean square and peak values obtained from sound signals also responded effectively to changes in bearing health status. Time and frequency analysis also revealed clear differences in amplitude and signal patterns between sound and vibration signals. It was determined that, if environmental noise does not significantly affect sound signals, sound analysis can effectively determine the equipment’s health status, comparable to vibration analysis.