Analytical Modeling and Experimental Validation of Wear and Frictional Noise Under Lubricated Conditions

Abstract

Understanding the dynamics of friction, wear, and noise under lubricated conditions is crucial for the predictive maintenance of mechanical systems; however, existing models often overlook the role of lubrication in modulating these interactions. This research presents an analytical model that combines single-degree-of-freedom (SDOF) vibration theory, Hertz contact mechanics, the Archard wear model, and the principles governing acoustic emission to predict both wear depth and sound pressure level emitted in a lubricated pin-on-disc system. Contact stiffness and wear-induced geometric changes are dynamically updated by the model, considering viscous damping from thin-film lubrication. Experiments were conducted using an Anton Paar TRB3 tribometer under lubricated conditions at realistic loads of 15, 20, and 30 N and a rotational speed of 300 rpm (corresponding to a linear sliding velocity of approximately 0.314 m/s at a 10-mm track radius). The friction noise was recorded by a microphone that was free-standing. The analytical predictions were closely aligned with the measurements taken during the tests. For mild steel, wear depth errors remained below 22%, while sound pressure predictions deviated by 14-21%. Due to its softer nature, aluminum exhibited higher wear deviations (up to 32%). Track analyses showed that lubrication decreases wear depth compared to dry sliding, and sound pressure levels are closely related to wear depth. Track analysis revealed that lubrication decreases wear depth by up to 50% compared to dry sliding, and sound pressure levels closely follow wear progression. This work improves prognostic health management systems by incorporating lubrication dynamics and tribo-acoustic phenomena, which allow for effective real-time wear and noise monitoring in industrial applications.