Rotating Angle Estimation for Hybrid Stepper Motors With Application to Bearing Fault Diagnosis
Xiaoxian Wang, Siliang Lu, Shiwu Zhang
Abstract
Hybrid stepper motors, which convert the input pulse train into rotating angle increments by using an open-loop control strategy, are widely used in industrial applications. The bearing is a key and vulnerable component in stepper motors, and the bearing faults affect the positioning accuracy and output torque of motors. Order analysis is an effective method in bearing fault diagnosis under varying speed conditions. The rotating angle curve is necessary for order analysis, but angle or speed sensors are not installed on hybrid stepper motors. In this article, a method of estimating the rotating angle from motor current is proposed and applied to bearing fault diagnosis. First, a variational nonlinear chirp mode decomposition method is introduced to decompose the current signal and extract a dominant mode that has a strong correlation with motor rotation. Second, the rotating angle is calculated, and the synchronous vibration signal is resampled using the rotating angle curve. Finally, the bearing fault type is identified from the envelope order spectrum of the resampled signal. The proposed method can accurately diagnose bearing faults and has potential applications in condition monitoring of stepper motors.