International Journal of Rotating Machinery

In order to study the influence of pitting on meshing stiffness, the normal distribution function is used to simulate the pitting location of pitting gear, and the potential energy method is used to analyze the influence of pitting on meshing stiffness. At the same time, the meshing stiffness of pitting gears with different degrees is analyzed by finite element method, and the validity of the calculation results with potential energy method is verified. On the basis of meshing stiffness, the dynamic model of gear system is established, and the vibration response of pitting gear system with different degrees is analyzed. The results show that with the increase of pitting area, the meshing stiffness decreases; the closer the meshing area of the driving wheel is to the pitting line, the more the meshing stiffness decreases, resulting in the intensification of vibration response and periodic impact; and in the time history diagram, there is a small spurious frequencies near the meshing frequency; in the phase diagrams and the Poincare diagram, trajectory and discrete point aggregation area is gradually increased.

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The shape characteristic of the axis orbit plays an important role in the fault diagnosis of rotating machinery. However, the original signal is typically messy, and this affects the identification accuracy and identification speed. In order to improve the identification effect, an effective fault identification method for a rotor system based on the axis orbit is proposed. The method is a combination of ensemble empirical mode decomposition (EEMD), morphological image processing, Hu invariant moment feature vector, and back propagation (BP) neural network. Experiments of four fault forms are performed in single-span rotor and double-span rotor test rigs. Vibration displacement signals in the and directions of the rotor are processed via EEMD filtering to eliminate the high-frequency noise. The mathematical morphology is used to optimize the axis orbit including the dilation and skeleton operation. After image processing, Hu invariant moments of the skeleton axis orbits are calculated as the feature vector. Finally, the BP neural network is trained to identify the faults of the rotor system. The experimental results indicate that the time of identification of the tested axis orbits via morphological processing corresponds to 13.05 s, and the identification accuracy rate ranges to 95%. Both exceed that without mathematical morphology. The proposed method is reliable and effective for the identification of the axis orbit and aids in online monitoring and automatic identification of rotor system faults.

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To investigate the thermal unstable vibration caused by journal whirls with large amplitude in journal bearing, an analysis model of lubricant film thickness is established. The journal surface temperature distribution is solved, and the reason for journal surface temperature difference appearance and its influence on rotor vibration are analyzed. Taking a turbogenerator as an example, the journal surface temperature difference and the induced rotor thermal bending under synchronous whirl in the bearing are calculated. Meanwhile, an engineering vibration fault with its treatment is presented. Results show that, the journal surface circumferential temperature difference is caused by viscous shearing within lubricant film under journal whirls with large amplitude in journal bearing. The direction of temperature difference is related to the direction of unbalanced force acting on journal. The temperature difference causes rotor thermal bending, which can be converted to a thermal unbalance on the rotor. The rotor vibration is caused by both thermal and initial unbalance. When the rotor is running below or at the critical speed, the vibration is on the increase until it leads to instability of the rotor eventually. When the rotor is running above the critical speed, the rotor vibration fluctuates periodically. Reducing the initial (mechanical) unbalances decreases the rotor vibration and the journal surface circumferential temperature difference.

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The presence of cavitation in the oil film seriously affects the bearing lubrication performance and bearing capacity. Now the research of this phenomenon mostly focuses on the model of Reynolds equation (R-E equation) or Navier-Stokes equation (N-S), the influence of the two computation models is less analyzed, and the effect of noncondensable gas (NCG) mass fraction on the bearing performance is seldom studied. In the manuscript, the cavitation mechanism is studied using the mixed model of three-dimensional N-S equation and Jakobsson-Floberg-Olsson (JFO) condition of two dimensional Reynolds equation, and the influence of rotational speed and NCG mass fraction on the cavitationoil film pressure, and bearing capacity was studied. The results show that the change trend of cavitation with the rotational speed is basically consistent for N-S equation and R-E equation. The bearing capacity calculated by N-S equation is greater than that calculated by R-E equation. The peak pressure and bearing capacity of film can be improved by increasing the NCG mass fraction of lubricant and rotational speed.

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The present paper proposes a methodology to design and manufacture optimized turbomachinery components by leveraging the potential of Topology Optimization (TO) and Additive Manufacturing (AM). The method envisages the use of TO to define the best configuration of the rotoric components in terms of both static and dynamic behavior with a resultant reduction of overall weight. Eventually, the topology-optimized component is manufactured by using appropriate materials that can guarantee valid mechanical performances. The proposed strategy has been applied to a 2D impeller used for centrifugal compressors to prove the effectiveness of a TO+AM-based approach. Although this approach has never been extensively used before to centrifugal compressors and expanders, its application on rotor and stator components might unlock several benefits: tuning the natural frequencies, a reduction in the stress level, and a lighter weight of the rotating part. These objectives can be reached alone or in combination, performing a single analysis or a multiple analyses optimization. Finally, the introduction of AM technologies as standard manufacturing resources could bring sensible benefits with respect to the time to production and availability of components. Such aspects are essential in the Oil and Gas context, when dealing with new projects but also for service operations.

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This paper performs a systematic numerical study to investigate the effect of rotation friction ratio on the power extraction performance of a passive rotation H-type vertical axis wind turbine (H-VAWT). In contrast to the previous literature, the present work does not impose rotation velocity on the turbine, and the rotation friction ratio which reflects the effect of external load characteristics on the turbine is introduced to the governing equation of the turbine. During each iteration, the rotation velocity of the turbine is computed after having determined the aerodynamic torque exerted on the blade of the turbine. This is more consistent with the actual working environment of the H-VAWT. A novel numerical coupling model was developed to simulate the interaction between the fluid and the passive rotation of the H-VAWT; then, the power extraction performance of the turbine with different rotation friction ratio was systematically analyzed. The results demonstrate that the power extraction performance of H-VAWT will be enhanced when the H-VAWT has appropriate rotation friction ratio. It is also found that the flow separation induced by large angle of attack is alleviated essentially if the H-VAWT has appropriate rotation friction ratio, which makes the H-VAWT have better energy extraction performance.

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