Working under a wide range of conditions, especially extreme conditions, causes significant energy dissipation and thermal deformation that affect the micro-scale oil film clearances between the piston/cylinder interface of electro-hydrostatic actuator (EHA) pumps. This study aims to provide a tolerance design guideline for the piston/cylinder interface under a wide range of working conditions, including extreme speed, pressure, and temperature domains. The guideline is developed based on the comprehensive consideration of friction force and leakage and the constraint of sticking threshold through a Thermal-Fluid-Structure model. The optimized clearance is presented in the form of tolerance to account for realistic manufacturing precision. The accuracy of the optimal results is further validated through experiments.

为了研究转体施工中球铰应力的计算方法,以实际工程为依托,采用实体有限元软件ABAQUS建立球铰模型,模拟球铰的受力状态,找到在转动阶段球铰应力的分布规律,同时分别采用规范中的简化计算法、简化偏压系数法、弹性力学法、非赫兹接触理论法对球铰进行计算.将模拟的有限元结果与理论计算值进行对比,发现每种方法各有利弊,其中,采用非赫兹接触理论法计算的结果误差最小,较为准确.但也存在不足,在距离球铰中心的0～0.8 m范围内,虽然其结果与有限元结果所呈现的应力分布规律相同,但存在一定的误差,差值为8.2％～13.7％;而在0.8～1.1 m范围内,更是呈现出与有限元结果相反的规律,尤其球铰边缘位置的误差最大,约为43％.针对这一问题,采用MATLAB软件对公式进行修正,结果表明修正后公式具有更好的适用性.

Geoacoustic inversion using moving sensors attracts lots of interest due to the ease of deployment and low cost. However, the well-established techniques, such as matched-field inversion (MFI), may run into difficulties when the sensors are in a range-dependent environment for mismatch issues and increasing unknown parameters. Given a range-dependent environment, the paper focuses on the inversion using a synthetic aperture created by moving sensors in the presence of the Doppler effect. The derivation is given to obtain an equivalent range-independent environmental model for fast inversion, instead of a range-dependent one. The received fields are modified using the Doppler-shifted wavenumbers. The simulations and results of the SWellEx-96 experimental data verify the effectiveness of the proposed inversion method.

A joint processing framework is proposed for distributed multiple-input-multiple-output (MIMO) sonar systems to exploit spatial diversity and array gain for detection of moving targets. An extended moving target consisting of multiple scatterers is illuminated by widely-spaced transmitters from different angles to achieve spatial diversity. Target bearing is first estimated with high resolution by the deconvolved conventional beamforming technique. Then a replica correlation integration processor is utilized to estimate the target’s range and speed in a multipath propagation environment. A MIMO detector is designed with the estimated target position parameters and Doppler factor under the generalized likelihood ratio test framework. The effectiveness of the distributed MIMO sonar system has been validated by the localization of two moving targets in sea experiments.

Well-designed surface textures can improve the tribological properties and the efficiency of the electro-hydrostatic actuator(EHA)pump under high-speed and high-pressure conditions.This study proposes a multi-objective optimization model to obtain the arbitrarily surface textures design of the slipper/swash plate interface for improving the mechanical and volumetric efficiency of the EHA pump.The model is composed of the lubrication film model,the component dynamic model considering the spinning motion,and the multi-objective optimization model.In this way,the arbitrary-shaped surface texture with the best comprehensive effect in the EHA pump is achieved and its positive effects in the EHA pump prototype are verified.Experimental results show a reduction in wear and an improvement in mechanical and volumetric efficiency by 1.4％and 0.8％,respectively,with the textured swash plate compared with the untextured one.

A spatial–temporal processing framework is proposed to forecast the wind turbine blade damage in the early stage. The sparse Bayesian learning beamforming (SBL) is applied to data received by a microphone array for enhancement of weak signals and suppressing interference of environmental noise. Then short-time Fourier transform (STFT) is utilized to create a time–frequency spectrum and analyze the nonstationarity of acoustic emission signals. The period of radiation energy change and the cyclic modulation spectrum (CMS) are respectively calculated from the time–frequency spectrum. Blade fault detection is performed based on whether or not the presence of the periodicity or cyclostationary signatures in acoustic emission signals. Numerical simulations have shown that the natural frequencies of acoustic emission signals tend to decrease when there is a hole on the blade surface. The experimental results have verified the effectiveness and robustness of the proposed blade damage detection method.

Traditional inversion methods, such as the matched field inversion, modal dispersion inversion, have been proposed and got good results. Still, the computing time of these methods is long due to large search space. With the development of artificial intelligence in recent years, deep learning methods have been utilized for geoacoustic inversion. An inversion framework based on neural networks is proposed in this work. The well-trained network can provide accurate inversion results when the processed data for inversion is given as the input of the neural network model. Additionally, the computational time will be shortened when using neural network to inverse geoacoustic parameters.

Mature geoacoustic inversion technologies such as matched-field inversion may encounter mismatching problems and the difficulty of increasing unknown parameters when the array or source is deployed in a range-dependent environment. Considering the range-dependent environment, this paper concentrates on the inversion using an equivalent range-independent environmental profile with “equivalent parameters” for fast inversion. Furthermore, for the equivalent profile, the effectiveness of different objective functions is studied for different array types such as vertical linear array and horrizontal linear array. Simulation results and Swellex-96 experimental data analysis demonstrate the effectiveness of the inversion method.

Target localization by using an Internet of Underwater Things (IoUT) network in three dimensional shallow water is considered in the presence of time synchronization attacks (TSA) which introduce additional delays in the signals received at the attacked sensors. To mitigate the impact of TSAs, we consider the task of joint target localization and attack detection. We show that this task can be formulated as a mix-integer programming problem with the number of optimization variables proportional to the number of multipaths, and hence is formidable when the multipath effect is severe. We show that if the magnitude of the correlation between multipath signals is upper bounded by some constant, which can be easily satisfied in practice, then the mix-integer programming can be simplified, and the number of optimization variables can be reduced and does not depend on the number of multipaths anymore. Next, we employ two computationally efficient algorithms to solve the simplified problem. The numerical results show that as the signal-to-noise ratio increases, the attack detection error of our approaches decreases to zero rapidly, and the target localization performance of our approaches is very close to that of the clairvoyant algorithm which is assumed to know the set of attacked sensors.

预应力混凝土连续刚构桥通常采用悬臂分段浇筑施工,施工监控是保证施工质量的重要手段.以灰色系统理论为基础,针对以往施工控制中传统的GM(1,1)模型参数估计方法与精度检验准则不适配的问题,将平均相对误差最小准则下的参数估计问题转化为线性规划问题,通过Python语言实现,从而得到一种新的理论模型来进行挠度预测,并以陕西境内某1号大桥为工程背景,对混凝土浇筑、预应力张拉两个工况作用后的梁端挠度值进行预测.与传统模型相比,改进后的模型平均相对误差最多可减小28.41％,并能够排除奇异数据的干扰.研究结果表明,基于线性规划法的GM(1,1)模型较传统模型具有更高的预测精度和更好的稳健性,能够在桥梁施工控制中发挥更好的预测作用.

为避免挂篮在桥梁悬臂施工过程中出现安全问题,影响工程质量,结合石川河特大桥的实际情况,采用液压千斤顶推反力架的方式对菱形挂篮进行预压试验,消除了非弹性变形.通过对实时监测获得的施工控制过程中挂篮各测点的标高数据进行分析与研究,得出荷载与挂篮自身的变形曲线,并采用有限元分析软件建立了菱形挂篮的空间力学模型,对挂篮施工状态和行走状态的抗倾覆稳定性进行了计算分析,结果表明:菱形挂篮的总变形与荷载基本呈线性关系,所用挂篮在2种状态下的应力均符合规范要求,并具有良好的抗倾覆安全储备.相关结论可为后续节段的施工提供依据.

为更好地保障高墩连续刚构桥施工安全,以石川河特大桥为工程背景,通过有限元仿真的方法对空心薄壁高墩连续刚构桥展开了复杂工况下的全过程稳定分析,得到了第一阶屈曲特征值和屈曲模态,并对混凝土强度、桥墩高度及高墩壁厚进行了参数敏感性研究.结果表明:只考虑几何非线性,最大悬臂状态的稳定系数为20.39,而考虑双重非线性的稳定系数为6.12,分别较第一类静力稳定降低了16.5％和74.9％;就石川河特大桥15#墩而言,屈曲模态为纵桥向失稳,高墩的破坏属于小偏压破坏,破坏截面发生在距墩底h/8～h/7(h为墩高)的区域;随着桥墩高度增加,桥梁的稳定性逐渐减小且减小的速率逐渐降低,而混凝土强度和高墩壁厚对高墩稳定性影响不大.可见考虑复杂工况的全过程稳定分析具有更好的实际意义.

A high resolution direction-of-arrival (DOA) approach is presented based on deep neural networks (DNNs) for multiple speech sources localization using a small scale array. First, three invariant features from the time-frequency spectrum of the input signal include generalized cross correlation (GCC) coefficients, GCC coefficients in the mel-scaled subband, and the combination of GCC coefficients and logarithmic mel spectrogram. Then the DNN labels are designed to fit the Gaussian distribution, which is similar to the spatial spectrum of the multiple signal classification. Finally, DOAs are predicted by performing peak detection on the DNN outputs, where the maximum values correspond to speech signals of interest. The DNN-based DOA estimation method outperforms the existing high resolution beamforming techniques in numerical simulations. The proposed framework implemented with a four-element microphone array can effectively localize multiple speech sources in an indoor environment.

Multi-layer neural networks (NNs) are combined with objective functions of matched-field inversion (MFI) to estimate geoacoustic parameters. By adding hidden layers, a radial basis function neural network (RBFNN) is extended to adopt MFI objective functions. Specifically, shallow layers extract frequency features from the hydrophone data, and deep layers perform inverse function approximation and parameter estimation. A hybrid scheme of backpropagation and pseudo-inverse is utilized to update the RBFNN weights using batch processing for fast convergence. The NNs are trained using a large sample set covering the parameter interval. Numerical simulations and the SWellEx-96 experimental data results demonstrate that the proposed NN method achieves inversion performance comparable to the conventional MFI due to utilizing big data and integrating MFI objective functions.

The single-receiver geoacoustic inversion attracts a great deal of interest recently. The paper focuses on the inversion based on the synthetic aperture created by a fixed hydrophone and a moving source in the presence of Doppler effect. The data received by a single hydrophone are transformed into the data received by a horizontal linear array (HLA) owing to the reciprocity theory of acoustic. The replica fields in matched field inversion (MFI) can be generated by the normal mode representation, which is modified using the waveguide Doppler-shifted horizontal wave numbers. The numerical simulations and the inversion results of the SWellEx-96 experimental data have verified the effectiveness of the improved inversion framework proposed in this paper.

随着经济全球化进程的不断加快与深入,全球范围内经济结构的不断调整,跨国界的贸易往来越来越频繁,中国也不可避免得参与到经济全球化的风潮中.在跨国际的贸易往来中,由于不同地区文化、民族、语言、思维方式等各种因素存在各种差异,各国、各地区的商人在贸易过程中常常会由于沟通不善而产生冲突乃至争端,导致贸易无法正常进行等情况,在各种影响因素中,文化是一个十分重要的影响因素,很大程度上影响了贸易的过程和沟通的过程,不了解贸易双方所独有的文化会对贸易造成不同程度的影响.本文立足于中国的对外贸易,就不同国家文化上的差异对中国与外界跨国界的贸易所造成的影响进行论述.