Drivetrain bearings are seen as the most common reason of the wind turbine drivetrain system failures and the consequent downtimes. In this study, the angular velocity error function is used for the condition monitoring of the bearings and gears in the wind turbine drivetrain. This approach benefits from using the sensor data and the dedicated communication network which already exist in the turbine for performance monitoring purposes. Minor required modification includes an additional moderate sampling frequency encoder without any need of adding an extra condition monitoring system. The additional encoder is placed on the low speed shaft and can also be used as the backup for the high speed shaft encoder which is critical for turbine control purposes. A theory based on the variations of the energy of response around the defect frequency is suggested to detect abnormalities in the drivetrain operation. The proposed angular velocity based method is compared with the classical vibration-based detection approach based on axial/radial acceleration data, for the faults initiated by different types of excitation sources. The method is experimentally evaluated using the data obtained from the encoders and vibration sensors of an operational wind turbine.