The gearbox is a vital component for rotating machinery and has been used in many critical engineering applications. Surface wear is a common but inevitable phenomenon during the lifespan of the gearbox. Its propagation can result in some catastrophic failures and cause unexpected economic loss. Therefore, it is vital to evaluate the degradation process of the gear system caused by surface wear propagation in order to make reliable predictive maintenance-based decisions to ensure the safe operation of the gearbox transmission system. The vibration analysis technique is a prevailing tool for rotating machine condition monitoring. However, research on vibration-based gear wear monitoring is relatively rare as the dynamic interactions between gear surface wear and gear system dynamic characteristics would produce complex gear dynamic responses and vibration features. Therefore, this paper presents a novel similarity-based status characterization methodology for gear wear monitoring. In th