Research of Mechanical Fault SVM Intelligent Recognition Based on EEMD Sample Entropy

The extraction of fault information is the key of fault intelligent recognition of support vector machine for rolling bearing. Because of the non-adaptive and mode mixture of wavelet transform and empirical mode decomposition, ensemble empirical mode decomposition (EEMD) and sample entropy have been adopted to extract fault information of rolling bearing. For three kinds of conditions and pitting diameters, the vibration signal of rolling bearing has been acquired by experiment. Then by wavelet transform to reduce noise, the noise reduction signal has been decomposed into several intrinsic mode function components by EEMD, and the complexity of major components has been described by sample entropy. In addition, a SVM rolling bearing fault classification recognizer which EEMD sample entropy has been adopted as training and recognition samples is proposed. The experiment result shows that under small sample, the inner race, outer race and ball fault of bearing can be accurately recognized and the accuracy for reorganization enhance with the number of samples increasing

Effects of oblique shock waves on turbulent structures and statistics of supersonic mixing layers

A supersonic mixing layer at a convective Mach number of 0.8 was investigated by large eddy simulation. Turbulent structures and statistics of the mixing layer interacting with an oblique shock at different strengths in the self-preserving stage were investigated and compared with the shock-free mixing layer. An inflection point arises on the velocity profiles in the self-preserving region where the incident shock wave impinges, in addition to the three inflection points existing in the shock-free mixing layer. It is caused by the hairpin vortices induced through the baroclinic mechanism of the interaction of the incident shock wave. However, the induced hairpin vortices disappear quickly within a short distance. The vorticity thickness of the shocked-mixing layer experiences a sudden decrease in the vicinity of the shock impingement point, which is due to the induced hairpin vortices, followed by a more rapid growth than that of the shock-free mixing layer. So the incident shock has positive effects on the growth of the mixing layer. Both the hairpin vortices and the vortices originated from the hairpin vortices can result in a double-peak profile of the streamwise Reynolds stress in the transient stage of the mixing layer. In addition, the asymmetric profiles for the Reynolds stress are due to the hairpin vortices breakup earlier in the upper stream. The amplitudes of the Reynolds stress increase slightly and their peak positions move toward the center of the mixing layer even in the self-preserving stage. Moreover, the profiles of the transverse Reynolds stress and Reynolds shear stress have two peaks for the shocked-mixing layer which are caused by the reflected shock waves and the mixing layer. The incident shock increases energy transport and convection between the mixing layer and the mainstream. As a result, the mixing process of the shocked-mixing layer is enhanced.</p