International Journal of Mechanical Engineering

With the widespread application of rotating machinery across industries, the reliability and stability of mechanical equipment have become critical factors. As a vital component in rotating machinery, bearings directly impact operational performance through their condition. Vibration analysis, serving as an effective monitoring method, can provide real-time insights into bearing health status, thereby offering data-driven support for predictive maintenance. This study establishes a vibration-based predictive maintenance strategy for rotating machinery bearings through feature extraction and analysis of vibration signals. The research demonstrates that vibration analysis not only enables early detection of bearing failures but also facilitates trend prediction to formulate rational maintenance plans, thereby extending equipment lifespan and reducing repair costs. Optimized predictive maintenance strategies enhance operational efficiency in rotating machinery, ensuring both production efficiency and safety.

Vibration analysis; Bearing premaintenance; Rotating machinery; Fault diagnosis; Condition monitoring