以先进的制造技术和管理取得竞争优势

针对如何提高机械加工的生产效率,改进生产管理结合实际工作做了论述,提出了自己的观点。     

正态-复合非时齐Poisson过程模型结构可靠性当量正态设计

讨论强度R～N（μ_R，_R），应力｛S（t），t∈［0，T］｝为非时齐Poisson过程模型结构可靠性当量正态设计。获得应力在设计基准期［0，T］内的最大值概率分布及统计参数估计；正态－复合非时齐Poisson过程模型结构可靠度及结构可靠性当量正态设计表达式。     

多功能实验室环境条件保障装置的设计

介绍了维持计量检定工作环境条件保障装置的设计方法，该装置可实现实验室温，湿度的测量与控制，有方便的通讯接口便于与计算机连接，并附加有多点时间控制电路以实现提前预热仪器设备提高工作效率的功能。     

EXPERIMENT RESEARCH ON DYNAMIC LOAD IDENTIFICATION TECHNOLOGY BASED ON GENERALIZED ORTHOGONAL POLYNOMIAL THEORY (GOPT)

Dynamicloadisoneoftheimportantoriginalparametersinstructuraldynamicanalysis.Ithasobviousinfluencestodynamicsdesign,vibrationcontrols,activecontroltechnologyandsoon.Sincel97O,manyresearchitemsinthisfieldhavebeenaccomplishedintheworld-Sometheoriesandexperimentalmethodsofdynamicloadidentificationhadbeencreatedinfrequencydomain[l'2J-Howeverftherearesomedisadvantagesthattheycouldbeadaptedonlytoidenti-fythesteady-stateloadandnottoidentifythetransientload,suchasshockloadwithshortsampling.Forvarious…     

小卫星非常规动力学分析与控制

针对小卫星研制中出现的一些非常规动力学问题进行研究,并提出解决办法。针对小卫星组件最大冲击谱量级超出常规冲击试验规范谱的分析与验证困难,通过研究提出了能够分析评估组件高量级冲击的方法。针对小卫星随机振动下强度设计方法还存在较大误差,分析了系统模态质量比与模态频率在一定频段的影响规律,认为忽略模态质量耦合会带来误差,提出了考虑模态质量耦合的准静态载荷计算方法。最后,针对小卫星整星开展了减振研究,分析了正弦和随机减振效果,对于对称安装减振系统,提出了减振系统的主频率计算公式。     

低轨卫星缺失时序数据的模式识别方法

在航天应用中，低轨卫星经常会由于原始数据缺失而影响卫星时序数据模式识别结果，降低准确率。针对该问题提出了一种新型MR-GRU模型，可有效处理缺失时序数据，并获得较好的模式识别准确率。区别于传统模型的补全缺失数据的方法，MR-GRU模型直接在缺失时序数据上运用循环神经网络进行训练，对传统门控循环单元结构进行了改进，增加了两个新变量：掩蔽项和衰减项。掩蔽项作用于输入，衰减项作用于输入和隐层单元输出。MR-GRU模型不仅能够保持时序数据固有的时间特性，还能有效提高模式识别精度。在卫星时序数据上的模式识别试验表明，MR-GRU模型准确率优于传统模型。     

仿生正弦前缘对翼面动态失速的影响

动态失速导致叶片气动载荷急剧变化，造成振动载荷激增，桨叶寿命大幅衰减。针对动态失速问题，从座头鲸胸鳍在动态倾转下取得良好的流动特性获得启示，据此模化出仿生正弦前缘翼面（包含3种波峰和2种波长），旨在实现动态失速控制。借助三维非定常数值模拟方法，采用运动网格技术，基于SC1095旋翼翼型，研究了仿生前缘动态失速流动控制机理及运动参数和来流速度的影响。结果表明：正弦前缘大幅度降低俯仰力矩系数峰值和阻力系数峰值；前缘波峰越大、波长越小，阻力系数峰值与俯仰力矩系数峰值的抑制效果越明显，虽然升力系数峰值减小，但其减小量远小于前两者，例如其中一种仿生翼使俯仰力矩系数峰值减小了47.7%，阻力系数峰值减小了36.4%，升力系数峰值减小14.1%；在最大迎角附近，正弦前缘能够缓和失速特性，使载荷变化更为平缓；在高平均迎角、低俯仰频率、低马赫数下，仿生翼动态失速控制效果更强，相比较而言迎角振幅的影响较小。     

Evaluation of SARAL/AltiKa performance using GNSS/IMU equipped buoy in Sajafi,Imam Hassan and Kangan Ports

Performance of SARAL/AltiKa mission has been evaluated within 2016 altimeter calibration/validation framework in Persian Gulf through three campaigns conducted in the offshore waters of Sajafi, Imam Hassan and Kangan Ports, while the altimeter overflew the passes 470, 111 and 25 on 13 Feb, 7 March and 17 June 2016, respectively. As the preparation, a lightweight buoy was equipped with a GNSS receiver/choke-ring antenna and a MEMS-based IMU to measure independent datasets in the field operations. To obtain accurate sea surface height (SSH) time series, the offset of the onboard antenna from the equilibrium sea level was predetermined through surveying operations as the buoy was deploying in the onshore waters of Kangan Port. Accordingly, the double-difference carrier phase observations have been processed via the Bernese GPS Software v. 5.0 so as to provide the GNSS-derived time series at the comparison points of the calibration campaigns, once the disturbing effects due to the platform tilt and heave have been eliminated. Owing to comparing of the SSH time series and the associating altimetry 1?Hz GDR-T datasets, the calibration/validation of the SARAL/AltiKa has been performed in the both cases of radiometer and ECMWF wet troposphere corrections so as to identify potential land contamination. An agreement of the present findings in comparison with those attained in other international calibrations sites confirms the promising feasibility of Persian Gulf as a new dedicated site for calibration/validation of ongoing and future altimetry missions.     

A new bearing fault diagnosis method based on modified convolutional neural networks

Fault diagnosis is vital in manufacturing system. However, the first step of the traditional fault diagnosis method is to process the signal, extract the features and then put the features into a selected classifier for classification. The process of feature extraction depends on the experimenters’ experience, and the classification rate of the shallow diagnostic model does not achieve satisfactory results. In view of these problems, this paper proposes a method of converting raw signals into two-dimensional images. This method can extract the features of the converted two-dimensional images and eliminate the impact of expert’s experience on the feature extraction process. And it follows by proposing an intelligent diagnosis algorithm based on Convolution Neural Network (CNN), which can automatically accomplish the process of the feature extraction and fault diagnosis. The effect of this method is verified by bearing data. The influence of different sample sizes and different load conditions on the diagnostic capability of this method is analyzed. The results show that the proposed method is effective and can meet the timeliness requirements of fault diagnosis.     

Analysis and design of Cubesat constellation for the Mediterranean south costal monitoring against illegal immigration

Costal monitoring is focused on fast response to illegal immigration and illegal ship traffic. Especially, the illegal ship traffic has been present in media since April 2015, as the number of reported deaths of immigrants crossing the Mediterranean significantly increased. Satellite images provide a possibility to at least partially control both types of events. This paper defines the principal criteria to select the best satellite constellation architecture for maritime and coastal monitoring, filling the gaps of imagery techniques in term of real-time control. The primary purpose of a constellation is to obtain global measurement improving the temporal resolution. The small size and low-cost are the main factors, which make CubeSats ideal for use in constellations. We propose a constellation of 9 Cubesats distributed evenly in 3 different planes. This reduces the revisit time enhancing the coverage duration. In addition, it also allows observing fire, damage on building and similar disasters. In this analysis, the performance criteria were reported such as the revisit time, the vision duration and the area coverage.