This paper focuses on the problem of fault characteristic frequency (FCF) estimation of rolling bearing.Teager-Kaiser
energy operator (TKEO) demodulation has been applied widely to rolling bearing fault detection.FCF can be extracted from
vibration signals,which is pre-treatment by using TEKO demodulation method. However, because of strong noise background
of fault vibration signal, it is difficult to extract FCF with high precision.In this paper, the improved method of
rolling bearing fault diagnosis is analyzed. Based on the envelope analysis by TKEO demodulation, it combines zero
padding technique and the improved iterative windowed interpolation DFT (IIWIpDFT) algorithm to correct demodulated
signal. Experiment result shows that under most circumstance, especially for short data length, the proposed algorithm
displays higher accuracy to identify FCF, compared to the application of traditional TEKO demodulation method alone.