Shock and Vibration

膜材料被广泛应用于建筑工程与小的质量和高的柔韧性，在振动呈现强几何非线性。在本文中，使用一种改进的多尺度扰动方法通过定量几何非线性效应对单模气动弹性不稳定性风速的影响来解决封闭式和开放式结构的膜屋顶的空气静力学稳定性。结果表明，两种模式的临界风速是当膜材料的几何非线性被忽略较小。此外，在正常风负载下，在屋顶上的空气动力学稳定性，膜的几何非线性的影响可以忽略不计。然而，强风荷载作用下，当车顶变形达到跨度的3％，几何非线性的影响，应考虑与横向的降低和顺风跨度膜屋顶的影响增大。本文所获得的结果具有用于设计膜结构具有重要的理论参考价值。

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acc的健康监测和管理epted in modern industrial machinery for an intelligent industrial production. To timely and reliably assess the bearing performance degradation, a novel health monitoring method called feature clustering analysis (FCA) has been proposed in this study. Along with the working time going, this new monitored chart picked by FCA aims to describe the feature clustering distribution transition by a series of reference models. First, the data provided by the reference state (healthy data) and the one from the monitor state (monitor data) are fused together to construct a reference model, which is to explore the active role of healthy status and activate the difference between healthy status and unhealthy status. Manifold learning is later implemented to mine the discriminated features for good class-separable clustering measure. In this manner, heterogeneous information hidden in this reference model will appear once degradation happened. Finally, a clustering quantification factor, named as feature clustering indicator (FCI), is calculated to assess distribution evolution and migration of the monitor status as compared to the consistent healthy status. Furthermore, a single Gaussian model (SGM) based on these FCIs is used to provide a smooth estimate of the healthy condition level. The corresponding negative log likelihood probability (NLLP) and the fault occurrence alarm are developed for an accurate and reliable FCC. And it can well depict a comprehensibility of the real bearing performance degradation process for its whole life. Meanwhile, as compared to other health profiles based on the classical health indicators, the proposed FCC has provided a much more accurate degradation level and rather monotonic profile. The experimental results show the potential in machine health performance degradation assessment.

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When the vibration signals of the rolling bearings contain strong interference noise, the spectrum division of the vibration signals is seriously disturbed by the noise. The traditional empirical wavelet transform (EWT) decomposes signals into a large number of components, and it is difficult to select suitable components that contain fault information. In order to address the problems above, in this paper, we proposed the improved empirical wavelet transform (IEWT) method. The simulation experiment proved that IEWT can solve the problem of a large number of EWT components and separate the impact component effectively which contains bearing fault information from noise. The IEWT method is combined with the support vector machine (SVM) to diagnosis the fault of the rolling bearings. The permutation entropy (PE) is used to construct feature vectors for its strong induction ability of dynamic changes of nonstationary and nonlinear signals. The crucial parameter penalty factorCand kernel parameterof SVM are optimized by quantum genetic algorithm (QGA). Compared with traditional EWT and variational mode decomposition (VMD) methods, the effectiveness and advantages of this method are demonstrated in this study. The classification prediction ability of SVM is also better than that of K-nearest neighbor (KNN) and extreme learning machine (ELM).

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耦合车辆/轨道动态model is formulated through integrating a high-speed rail vehicle model with a slab track model via the wheel/rail contact model. The sliding window method is improved using the least square criterion to simulate the vehicle travelling along the infinite long track. The steady-state responses of a high-speed vehicle induced by the discrete sleepers and slab segments are investigated through numerical simulation and analysis of the experimental results. Also the validity of the coupled vehicle/track model is examined through comparing the simulation results with those acquired from field test measurements. The experimental and numerical results show that the wheel/rail contact forces fluctuate considerably as long as the sleeper passing frequency approaches the frequency of P2 resonance (wheelset and rail bouncing in phase on the slab). Increasing the damping of rail pads and primary suspension can lower the steady-state response amplitudes at the resonance region. The oscillations in the wheel/rail normal forces arising from the discrete slab segment excitation can be reduced by increasing the support stiffness of the CAM (cement asphalt mortar) layer under the slab.

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In this study, we attempt to analyze the influence of different excitation factors on the dynamic behavior of a gear transmission system in a braiding machine. In order to observe nonlinear characteristics, a mathematical model is established with a six-degrees-of-freedom gear system for consideration of multiple excitation factors. Iterative results are used to study the nonlinear characteristics of the gear system with respect to contact temperature, varying levels of friction, and disturbance of yarn tension using bifurcation diagrams, maximum Lyapunov exponents, phase diagrams, Poincare maps, and the power spectrum. The numerical results show that excitation factors such as temperature and surface friction, among others, have considerable influence on the nonlinear characteristics of the gear system in a braiding machine, and the model is evaluated to show the key regions of sensitivity. The analysis of associated parameters can be helpful in the design and control of braiding machines.

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The paper studies the characterization and evaluation technology of rotation accuracy of hydrostatic spindle under the influence of unbalance. The dynamic model of the motion error of the hydrostatic spindle is established based on the dynamic parameters. The variation law of motion error of spindle rotor is analyzed under the unbalanced mass. The paper finds that with the increase of the spindle speed, the amplitude of the spindle error motion will increase, and the inclination angleθ的错误是在旋转速度的变化更敏感。在总合成精度，同步误差的比例随着转速的增加而减小。最后，最小平方评估算法被用来评估静压主轴的旋转误差，并提出了一种用于评估具有高的计算精度和计算效率的静压主轴的旋转精度的方法。

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