Instantaneous angular speed signal estimation using adaptive local frequency demodulation

Abstract

The instantaneous angular speed (IAS) signal reflects the operating condition of the rolling bearing, and its estimation accuracy determines the performance of bearing fault diagnosis. Under variable-speed conditions, Frequency Demodulation struggles with fixed-bandwidth bandpass filters, resulting in significant residual noise in the estimated IAS signal. To address this limitation, this paper proposes an Adaptive Local Frequency Demodulation (ALFD). By constructing an adaptive bandpass filter that tracks the instantaneous frequency variation of the encoder signal, ALFD maintains a narrowband filter, thereby effectively suppressing residual noise in the estimated IAS signal. Furthermore, the parameter sensitivity of the ALFD is investigated. Results indicate that the sliding step length balances frequency resolution against tracking accuracy, while the threshold factor provides a broad range of stable performance. Finally, the analysis of the experimental encoder signal demonstrates that the ALFD significantly improves the accuracy of IAS signal estimation.