The invention discloses a bearing early fault diagnosis method for multiple 
noise reduction 
processing. The method comprises the following steps: collecting a vibration 
signal of a bearing; carrying out short-time 
Fourier transform on the 
bearing vibration signal, and preliminarily judging whether the bearing has a fault or not; adopting 
wavelet packet transformation to decompose and reconstruct the 
bearing vibration signal, and carrying out preliminary denoising; decomposing, screening and reconstructing the 
wavelet packet reconstruction signal by using an ensemble empirical mode 
decomposition method; eliminating 
aliasing interference signals contained in the reconstructed signals, and performing multi-layer 
noise reduction on the 
bearing vibration signal; carrying out 
demodulation processing on the reconstructed signal after 
noise reduction, and extracting a bearing fault frequency; and comparing with a theoretically calculated fault frequency, and diagnosing to obtain a fault conclusion of the bearing. According to the method, a 
fault analysis mode combining 
wavelet packet transformation, an ensemble empirical mode 
decomposition method and autocorrelation calculation denoising is adopted, weak fault features are highlighted, bearing abnormity can be diagnosed and recognized as early as possible in the early fault stage of the bearing, and losses caused by equipment faults are avoided or reduced.