Bearing fault characteristic frequencies contain weak energy when the early fault occurs, and they are often overwhelmed in noise. According to the research results on the fault mechanism of rolling bearings, the demodulation of bearing resonance frequency is helpful in improving SNR and extracting the characteristic frequencies. Based on time-frequency analysis and information entropy, Frequency Band Entropy (FBE) is introduced to find the bearing resonance frequency. At first, the Short Time Fourier Transform (STFT) is utilized to calculate the time-frequency distribution of signal. Then the amplitude spectrum entropy of every frequency is estimated, which discover the complexity of every frequencies changing with time. This property provides a way of blindly designing of optimal filter parameters. The bearing characteristic frequencies can be extracted effectively from the signal after filtering. The simulation and experiment verify the validity of the proposed method.