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。     

基于虚拟仪器的切削力监控技术研究

研制了一种基于虚拟仪器界面、供现场使用的高精度、高效率的金属切削过程监控系统。研究中采用回归分析、叠加原理及抛物线插值的方法建立切削力模型 ,并基于该模型进行参数估计来提取切削状态特征 ,进而监控整个切削过程     

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。     

Vibration signal-based chatter identification for milling of thin-walled structure

In high speed milling aeronautical part, tool condition monitoring(TCM) is very important, because it is prone to get a chatter owing to the low stiffness of thin-walled structures. And the TCM is key technology for automated machining. In this paper, aiming to chatter monitoring in thin-walled structure milling, a variational mode decomposition – energy distribution(VMD-ED)method is proposed to improve the identification accuracy. And a moving average root mean square – mean value(MARMS-MV) ide...     

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。     

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.     

Real-time clock comparison and monitoring with multi-GNSS precise point positioning: GPS,GLONASS and Galileo

The precise point positioning (PPP) technique is widely used in time and frequency applications. Because of the real-time service (RTS) project of the International GNSS Service, we can use the PPP technique for real-time clock comparison and monitoring. As a participant in the RTS, the Centre National d’Etudes Spatiales (CNES) implements the PPPWIZARD (Precise Point Positioning with Integer and Zero-difference Ambiguity Resolution Demonstrator) project to validate carrier phase ambiguity resolution. Unlike the Integer-PPP (IPPP) of the CNES, fixing ambiguities in the post-processing mode, the PPPWIZARD operates in the real-time mode, which is also called real-time IPPP (RT-IPPP). This paper focuses on applying the RT-IPPP for real-time clock comparison and monitoring. We review the principle of real-time clock comparison and monitoring, and introduce the methodology of the RT-IPPP technique. The observations of GPS, GLONASS and Galileo were processed for the experiments. Five processing modes were provided in the experiment to analyze the benefits of ambiguity resolution and multi-GNSS. In the clock comparison experiment, the average reduction ratios of standard deviations with respect to the G PPP mode range from 9.7% to 35.0%. In the clock monitoring experiment, G PPP mode can detect clock jumps whose magnitudes are larger than 0.9 ns. The RT-IPPP technique with GRE PPP AR (G) mode allows for the detection of any clock jumps larger than 0.6 ns. For frequency monitoring, G PPP mode allows detection of frequency changes larger than 1.1 × 10⁻¹⁴. When the RT-IPPP technique is applied, monitoring with GRE PPP AR (G) mode can detect frequency changes larger than 6.1 × 10⁻¹⁵.     

分布式容错配电系统设计与仿真

阐述了分布式容错配电系统的功能需求及构型设计,完成了分布式容错配电仿真验证系统的研制,并进行了试验验证。结果表明:系统运行可靠,控制逻辑正确,系统设计满足功能要求。     

Characterization of ionospheric amplitude scintillations using wavelet entropy detrended GNSS data

The extensive monitoring networks of Global Navigation Satellite System (GNSS) ionospheric scintillation have been established to continuously log observation data. Further, the amplitude scintillation index and the phase scintillation index, which are derived from scintillation observations, are anticipated to accommodate the accuracy requirement of both the user level and the monitoring station level. However, raw scintillation observations essentially measure superposed waveform impairments of GNSS signals propagating through ionosphere and troposphere. It implies that fluctuations of raw scintillation observations are caused by multiple factors from the entire radio propagation environment. Hence, it is crucial to characterize ionospheric scintillations from GNSS observation data. And the characterization is implemented through extracting fluctuations of raw observations merely induced by ionospheric scintillations. Designed to address this problem by means of Fourier filtering detrending, the present work investigates the influence of varying detrending cutoff frequencies on wavelet statistical energy and wavelet entropy distributions of scintillation data. It consequently derives criteria on the optimum detrending cutoff frequency for three types of raw amplitude scintillation data, which are classified by their wavelet energy distributions. Results of the present work verify that detrending with specific optimum cutoff frequencies rather than the fixed and universally applicable one renders the validity and credibility of characterizing ionospheric scintillations as the part of GNSS observation fluctuations purely induced by ionosphere electron density irregularities whose scale sizes are comparable with or smaller than the Fresnel scale.