Abstract: Timely and effective detection of abnormal changes in spacecraft power subsystem (SPS) is an important guarantee for the safe and stable operation of spacecraft. However, due to the complex working environment of SPS and the closed loop structure inside SPS, the telemetry signal characterizing its working state contains noise and cannot reflect the fault information in time. Therefore, in view of the noise and label free problems of SPS telemetry signals, a SPS fault detection method is proposed based on multiresolution singular value decomposition (MSVD) and auto encoder (AE). Firstly, MSVD is applied to the field of wave signal denoising to reduce the influence of noise on telemetry signal. Secondly, aiming at the problem of lack of fault labels in SPS telemetry data, an unsupervised auto encoder algorithm is used to detect the abnormal data after noise reduction. Finally, the proposed algorithm is applied to SPS, and the denoising effects of MSVD, wavelet transform and empirical mode analysis are compared. Then, the SPS is detected by AE. The results show that the proposed algorithm has lower misjudgment rate and higher detection rate.