For the feature extraction requirements of complex and non-stationary vibration sensor signal, this paper researches Hermite interpolation based on triangular Shepard(TSHI) and LMD method based on TSHI for vibration sensor signal feature extraction. TSHI combines binary Hermite interpolation functions with osculatory triangular Shepard basis functions. Then it creates the envelope curve interpolation polynomial of complex and scattered vibration sensor signal. It can adjust the local interpolation curve according to the time distance between the interpolation point and every vertex of the triangle, so that the envelope estimation curve is more suitable. The LMD method based on TSHI decomposes the vibration sensor signal into several Product Functions(PF) which has time-frequency characteristic scale of the signal. Then the method combines the energy of the main PFs to form the signal characteristic vector. The experimental results show that TSHI for complex and high frequency vibration sensor signal’s envelope curve can avoid phase difference, over envelope and under envelope. The RMSE of the TSHI result is smaller. If Relevance Vector Machine(RVM) fault diagnosis model applies the LMD method based on TSHI, its diagnostic accuracy of vibration sensor is close to 100%.