Weak fault feature extraction method based on selective integration and improved local feature decomposition

The invention discloses a weak fault feature extraction method based on selective integration and improved local feature decomposition. The method specifically comprises the steps that collecting vibration signals and carrying out normalization processing; adopting a boundary continuation method based on mirror image continuation symmetric points to carry out continuation on two ends of the normalized signal; decomposing the extended signal into a plurality of ISC components by adopting an SEILCD method; estimating the energy of each ISC component at the confidence of 95% and 99%; judging whether each ISC component belongs to noise or not, if yes, denoising the ISC by adopting a minmax threshold denoising method, and otherwise, denoising the ISC by adopting an AWOGS method; and normalizingand orthogonalizing the denoised ISC and carrying out time-frequency analysis. According to the method, the LCD interpolation mean value curve and the adaptive signal denoising can be adaptively selected, the complex vibrati