Traction rectifier fault diagnosis based on multi-band and multi-scale fuzzy entropy fusion
MAO Xiang-de
DONG Hai-ying
LIANG Jin-ping
Abstract：Aiming at the traction rectifier with the highest failure rate in the traction transmission system of electric locomotive,a fault diagnosis method based on multi-band and multi-scale fuzzy entropy fusion algorithm is proposed.Firstly,based on the optimal wavelet basis function,wavelet packet decomposes fault signals under different working conditions and different operating modes,and a series of optimal frequency bands information are obtained.Secondly,the sequences of each frequency band are coarse-granulated and multi-scale fuzzy entropy is calculated.Finally,the energy value of multi-scale fuzzy entropy of each frequency band is solved,which is used as the fault feature vector.The results show that the multi-band fuzzy entropy feature based on the optimal wavelet basis function has a certain robustness to noise,and according to the proposed multi-scale fuzzy entropy fusion algorithm,the fault diagnosis rate can be further improved.Compared with other methods,the proposed method has higher diagnosis rate and stronger robustness.
Keywords：traction rectifierenergy entropy ratiomulti-scale fuzzy entropyenergymulti-information fusion
Publication Date：2025-07-30
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：10( 1313-1322 )