Crack Fault Diagnosis of Gun Automatic Mechanism Based on Multifractal Features
In order to make better use of vibration signals to diagnose the crack faults of gun automatic mechanism,a fault diagnosis method based on multifractal features of vibration signals is proposed.The proposed method uses Wavelet Leader to estimate the multifractal spectrum of vibration signals.6 feature quantities are used to describe the morphological features of multifractal spectrum,and the dimensionality reduction of multifractal spectrum is realized.A classifier based on Mahalanobis distance is used to classify different crack faults.This method is applied to diagnose the crack faults of locking mechanism in a 12.7 mm antiaircraft machine gun,and the diagnostic accuracy is up to 82.5％,which verifies the feasibility of applying the multifractal features of vibration signals to the crack fault diagnosis of gun automatic mechanism.
NETL
NSTL
万方数据
维普
