It is difficult to diagnose the early weak fault of rolling bearing because it is easily affected by noise. In view of the shortcomings of the original ITD and cubic spline interpolation improved ITD algorithm and the difficulty in selecting the filter length parameters of the maximum correlation kurtosis decomposition (MCKD) algorithm, an improved ITD (QH-ITD) algorithm based on the quartic Hermite interpolation and an improved MCKD (AMCKD) algorithm based on variable step length search parameters optimization are proposed. Firstly, QH-ITD algorithm is used to decompose the fault signal of the original rolling bearing, then the kurtosis index and the correlation number are used to screen the corresponding component signals for reconstruction, then the AMCKD algorithm is used to reduce the noise of the reconstructed signal, finally, the Teager-Kaiser energy operator is used for demodulation, the fault characteristic information is extracted and the fault type is determined. It is verified that the proposed method can effectively diagnose and identify the early weak fault of the rolling bearing by simulating the damage fault diagnosis experiment and the early weak fault diagnosis experiment of the bearing with the whole life cycle.