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On the basis of the principal components analysis-particle swarm optimization-least squares support vector machine (PCA-PSO-LSSVM) algorithm, a fault diagnosis system is proposed for the compressor system. The relationship between the working principle of a compressor system, the fault phenomenon, and the root cause is analyzed. A fault diagnosis model is established based on the LSSVM optimized using PSO, the compressor fault diagnosis test experimental platform is used to obtain the fault signal of various fault occurrence states, and the PCA algorithm is employed to extract the characteristic data in the fault signal as input to the fault diagnosis model. The back-propagation neural network, the LSSVM algorithm, and the PSO-LSSVM algorithm are analyzed and compared with the proposed fault diagnosis model. Results show that the PCA-PSO-LSSVM fault diagnosis model has a maximum fault recognition efficiency that is 10.4% higher than the other three models, the test sample classification time is reduced by 0.025 s, the PCA algorithm can effectively reduce the input dimension, and the PSO-LSSVM fault diagnosis model based on the PCA algorithm for extracting features has a high recognition rate and accuracy. Therefore, the proposed fault diagnosis system can effectively identify the compressor fault and improve the efficiency of the compressor.

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The past research on the supercavity flow mostly focused on the homogeneous fluid medium, ignoring the influence of the sudden change of the medium density. We present results from numerical study of moving projectile passing density change zone, both from low-density zone to high-density zone and from high-density to low-density. Particular attention is given to the cavity variation when projectile voyaging through different liquid density areas. And the influence of the cavitation number on the cavity variation is also studied. Research results show that there is a ‘diameter shrinkage’ phenomenon when the projectile moving pass the density jump area. The location of ‘diameter shrinkage’ is relative to the density change model: moving from high density side to low, it appears at the interface of liquids; while moving from low density side to high side, it occurs at low density side not the interface. And the degree of ‘necking’ have something to do with the density difference of two sides. However the effect of cavitation number is much complex, the ‘necking’ phenomenon at the interface showed disorder maybe due to the sample limit, but the re-development of the cavity after passing through the interface showing obvious regularity with the cavitation number.

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