Method for extracting fault feature of antifriction bearing based on sliding entropy-ICA algorithm

• Main Authors: SUI XIULIN, ZOU YUNQI, GE JIANGHUA
• Format: Patent
• Language: Chinese; English
• Published: 08.08.2017
• Subjects: MEASURING; PHYSICS; TESTING; TESTING STATIC OR DYNAMIC BALANCE OF MACHINES ORSTRUCTURES; TESTING STRUCTURES OR APPARATUS NOT OTHERWISE PROVIDED FOR

A method for extracting the fault feature of an antifriction bearing based on a sliding entropy-ICA algorithm is provided. The method comprises main steps of: (1) subjecting a single-channel actually measured signal to EMD to obtain respective IMF components; (2) screening out effective IMF components by using a sliding entropy cross correlation coefficient to form a virtual channel signal; (3) integrating the single-channel actually measured signal with the effective IMF components to form a composite signal matrix, separating the composite signal matrix by using a FastICA algorithm to obtain respective source signal estimated values; (4) retaining a source signal containing a bearing fault feature, and extracting a plurality of time-domain feature parameters and frequency-domain feature parameters to form a feature parameter set; and (5) subjecting a high-dimensional feature set to data fusion by using an LLE algorithm to obtain an accurate low-dimensional feature parameter. The method uses the sliding entr