Speed and skidding rate are crucial parameters for evaluating bearing performance, and their effective monitoring is essential for early fault detection and ensuring reliable equipment operation. Current monitoring methods often face limitations in installation space and insufficient measurement accuracy, making in-situ monitoring difficult and restricting their practical application. To address these challenges, this study proposes a method for synchronous in-situ monitoring of bearing speed and skidding. Two triboelectric nanogenerators (TENGs) are integrated within the confined space of the bearing, employing the snap-fit embedded connection between the cage, inner ring and rotor, thereby enabling precise and reliable monitoring. Utilizing dynamic contact mode, the TENG achieves enhanced durability while maintaining an optimal output performance. Based on this method, a bearing condition monitoring sensor (BCMS) is developed. The BCMS demonstrates exceptional measurement precision across an operational speed range of 600–6000 rpm, achieving a speed monitoring error of less than 0.10% and a skidding error within 0.25%, while still providing effective output after over 8 million cycles. Furthermore, a high-speed bearing working state monitoring system is developed to enable online monitoring of bearing speed and skidding under various operating conditions. This study provides a new method for the development of self-powered smart bearings.