Stator fault diagnosis method for marine electrical motors based on wavelet packets transform and rough set theory
Qiu Chi-dong · Journal of Dalian Maritime University · 2007
To discern fault evolution and criticality for marine motors under less sensors and without a priori failure diagnosis knowledge conditions,the discernibility matrix was established and a extraction method for diagnosis rules was developed based on rough set theory.The stator current was decomposed by wavelet packets.The decomposed sub-frequency bands could always cover the fault eigenfrequencies varying together with the slip.The fault eigenvalues were obtained by the mean-squared root method using reconstructed node coefficients.The eigenvalues were clustered based on a self-organizing feature map.The disturbance owing to wavelet overlap was significantly decreased using training samples composed of two meansquared roots for the adjacent nodes.Under the laboratory condition,a artificial motor fault experiment was designed.Experimental results validate the feasibility of the proposed method.