Discrete time transfer matrix method for dynamics of multibody system with flexible beams moving in space

In this paper, by defining new state vectors and developing new transfer matrices of various elements mov- ing in space, the discrete time transfer matrix method of multi-rigid-flexible-body system is expanded to study the dynamics of multibody system with flexible beams moving in space. Formulations and numerical example of a rigid- flexible-body three pendulums system moving in space are given to validate the method. Using the new method to study the dynamics of multi-rigid-flexible-body system mov- ing in space, the global dynamics equations of system are not needed, the orders of involved matrices of the system are very low and the computational speed is high, irrespec- tive of the size of the system. The new method is simple, straightforward, practical, and provides a powerful tool for multi-rigid-flexible-body system dynamics.

Feature Extraction and Recognition for Rolling Element Bearing Fault Utilizing Short-Time Fourier Transform and Non-negative Matrix Factorization

Due to the non-stationary characteristics of vibration signals acquired from rolling element bearing fault, thc time-frequency analysis is often applied to describe the local information of these unstable signals smartly. However, it is difficult to classitythe high dimensional feature matrix directly because of too large dimensions for many classifiers. This paper combines the concepts of time-frequency distribution（TFD） with non-negative matrix factorization（NMF）, and proposes a novel TFD matrix factorization method to enhance representation and identification of bearing fault. Throughout this method, the TFD of a vibration signal is firstly accomplished to describe the localized faults with short-time Fourier transform（STFT）. Then, the supervised NMF mapping is adopted to extract the fault features from TFD. Meanwhile, the fault samples can be clustered and recognized automatically by using the clustering property of NMF. The proposed method takes advantages of the NMF in the parts-based representation and the adaptive clustering. The localized fault features of interest can be extracted as well. To evaluate the performance of the proposed method, the 9 kinds of the bearing fault on a test bench is performed. The proposed method can effectively identify the fault severity and different fault types. Moreover, in comparison with the artificial neural network（ANN）, NMF yields 99.3% mean accuracy which is much superior to ANN. This research presents a simple and practical resolution for the fault diagnosis problem of rolling element bearing in high dimensional feature space.

Solving Diffusion Time in Heterogeneous Microscale Rock Matrix by 3D Computations: Non-Fickian Dispersion Observed in Porous Media

Understanding and simulating the underlying microscopic physics of the rock matrix is very useful for determining macroscopic physical properties such as permeability. Matrix diffusion is an important transport parameter controlling the late-time behaviour of breakthrough curves (BTCs). We compute the memory function, implemented in the sink/source term of Mobile-immobile mass transfer by solving the matrix diffusion using a time diffusion random-walk approach. The diffusion is controlled by different parameters like the porosity, tortuosity, mobile-immobile interface and immobile domain cluster shapes. All these properties are investigated by X-ray microtomography that captures the main characteristics of matrix diffusion at three dimensions. We compare the memory function deduced from the field-scale tracer tests well with the computed memory function. Simulation results of the memory function appeared to be coherent with that measured from the tracer test for a large tortuosity value. Probably, the diffusion paths are longer, and they are controlled by the properties mentioned above. From a representative elementary volume of natural reservoirs studied here, we conclude that, microscale diffusion process in the immobile domain play a crucial role to better understand the non-Fickian dispersion measured from the tracer test.

Electricity Price Influence Factors Analysis Using Stochastic Matrix for Real-Time Electricity Price Forecasting

Real-time electricity price( RTEP) influence factor extraction is essential to forecasting accurate power system electricity prices. At present,new electricity price forecasting models have been studied to improve predictive accuracy,ignoring the extraction and analysis of RTEP influence factors. In this study,a correlation analysis method is proposed based on stochastic matrix theory.Firstly, an augmented matrix is formulated, including RTEP influence factor data and RTEP state data. Secondly, data correlation analysis results are obtained given the statistical characteristics of source data based on stochastic matrix theory.Mean spectral radius( MSR) is used as the measure of correlativity.Finally,the proposed method is evaluated in New England electricity markets and compared with the BP neural network forecasting method. Experimental results show that the extracted index system comprehensively generalizes RTEP influence factors,which play a significant role in improving RTEP forecasting accuracy.

On stabilization for a class of nonlinear stochastic time-delay systems:a matrix inequality approach

This paper treats the feedback stabilization of nonlinear stochastic time-delay systems with state and control-dependent noise. Some locally （globally） robustly stabilizable conditions are given in terms of matrix inequalities that are independent of the delay size. When it is applied to linear stochastic time-delay systems, sufficient conditions for the state-feedback stabilization are presented via linear matrix inequalities. Several previous results are extended to more general systems with both state and control-dependent noise, and easy computation algorithms are also given.

How Kieffer Density Matrix Formalism Aids Different Initial Time Steps, Leading to Lorentz Violations, and Breakup of Primordial Black Holes for GW Generation

A result from Kieffer, as outlined at the beginning of the article identifies two different candidates for initial time steps, delta t. We assert that this difference in time steps may be related to a specific early universe Lorentz Violation. The author asserts that the existence of early universe Lorentz violation in turn is assisting in a breakup of primordial black holes. And that also has a tie into Kieffer different time steps as outlined. And the wrap up is given in the final part of this document.

Event-Triggered Finite-Time H∞ Filtering for Discrete-Time Nonlinear Stochastic Systems

This paper addresses the problem of event-triggered finite-time H∞ filter design for a class of discrete-time nonlinear stochastic systems with exogenous disturbances. The stochastic Lyapunov-Krasoviskii functional method is adopted to design a filter such that the filtering error system is stochastic finite-time stable (SFTS) and preserves a prescribed performance level according to the pre-defined event-triggered criteria. Based on stochastic differential equations theory, some sufficient conditions for the existence of H∞ filter are obtained for the suggested system by employing linear matrix inequality technique. Finally, the desired H∞ filter gain matrices can be expressed in an explicit form.

精细积分方法的发展与扩展应用

钟万勰院士于1991年首先提出计算矩阵指数的精细积分方法,其要点是2N类算法和增量存储。精细积分方法可给出矩阵指数在计算机意义上的精确解,为常微分方程的数值计算提供了高精度、高稳定性的算法,现已成功应用于结构动力响应、随机振动、热传导以及最优控制等众多领域。本文首先介绍矩阵指数精细积分方法的提出、基本思想和发展;然后依次介绍在时不变/时变线性微分方程、非线性微分方程以及大规模问题求解中发展起来的各种精细积分方法,分析了其优缺点和适用范围;最后介绍了精细积分方法的基本思想在两点边值问题、椭圆函数和病态代数方程等问题的扩展应用,进一步展示了该思想的特色。

MicrobMatcher: a microbial comparison software based on matrix-assisted laser desorption/ionization with time-of-flight mass spectrometry

Matrix-assisted Laser Desorption/Ionization with Time-of-flight Mass Spectrometry (MALDI-TOFMS) was investigated as a method for the rapid identifica-tion of species. Current demand in microbial identi-fication is how to compare unknown strains to the known one quickly, semi-automatically and accurately. In this paper, we present a software tool that allows flexibly microbial matching in a user-friendly way, by letting the users to customize comparison parameters including: in vitro transcription enzyme, mass tolerance,minimum fragment length, intensity threshold and corresponding weights. We provide three spectral scoring functions to compute the affin-ity between the species. Therefore, the precision of microbial comparison increases. To test and verify this tool, we employed experimental spectral data based on MALDI-TOFMS and the gene sequences of E.coli and Salmonella. This software is written in Java for cross-platform intention.

结构动力问题的高阶精确时步群积分方法

高阶精确时间积分方法可为与时间相关的高频复杂动力行为提供高精度的预测结果,但既有高阶精确时间积分方法普遍存在计算工作量偏大的问题,难以满足实际结构线性和非线性动力分析日益增长的计算需求。该文提出了一种基于时步群的高阶精确时间积分方法,将p(p≥2)个相邻的未知时步组成待求解的时步群,以结构动力方程积分解为基础构建逐时步群求解结构动态响应的时间积分方案。在对每个时步群进行积分的过程中,无需联立求解方程,仅通过矩阵乘法运算即可一次性地计算得到时步群内全部p个时步的动态响应。数值特性分析以及线性与非线性算例试验均表明,该文算法精度高、稳定性好、数值耗散可控,在选择较大的时间步距情形下依然能够稳定地获得高精度的计算结果。相较传统二阶精度时间积分方法,该文算法的计算效率亦有较大幅度地提高。

面向不同训练内容的训练环境快速切换方法

训练环境中,传统的人工部署和配置切换方式效率低且易出错,不利于用户在不同训练对象和训练模式下对训练的灵活组织与应用。为满足当前训练需求,提出了一种面向不同训练内容的训练环境快速切换方法。首先,阐述了该方法的主要原理;然后,描述了训练科目编排优化、基于应用集群和容器调度的系统快速构建以及轻量级客户端集成3种关键技术;最后,给出了应用实例。应用实例表明,该方法实现了训练内容快速切换和训练资源动态重组,提升了训练效能。

全方位机器人的重心位置预测与轨迹跟踪控制

针对全方向移动机器人存在非线性动态强耦合、实时重心偏移及难以实现高精度跟踪控制的问题,本文提出一种基于长短期记忆(LSTM)神经网络的重心位置在线预测的轨迹跟踪控制法.首先,建立考虑重心偏移的动力学模型并基于LSTM神经网络训练构建其对比模型;其次,基于模型对比法实时估计重心偏移参数,再基于张神经网络(ZNN)对估计的重心偏移参数进行预测以减小估计过程引起的滞后;最后,基于非线性动态反馈解耦法设计数值加速度控制算法,且基于离散系统极点配置法分析了系统的稳定性.仿真结果验证了所提方法相对于数值加速度控制器与自适应控制器因能在线预测重心偏移参数完成高精度动态解耦实现控制精度的提高.实际实验中,所提控制算法相比数值加速度控制及模型预测控制,其跟踪精度明显提高,这表明所提控制算法可显著减小重心偏移对跟踪控制精度的影响.

铝酸盐体系中氧化时间对碳化硅颗粒增强铝基复合材料微弧氧化膜层的影响

[目的]探究氧化时间对碳化硅颗粒增强铝基(SiC_(p)/Al)复合材料微弧氧化膜层的影响。[方法]选用铝酸盐体系作为电解液,对SiC_(p)/Al复合材料进行微弧氧化处理,分析氧化时间对膜层组织结构、物相、厚度、粗糙度、结合力、电绝缘性及耐蚀性的影响。[结果]随着氧化时间延长,膜层逐渐变得连续均匀,厚度增加。若氧化时间过长,膜层会出现层叠现象,形成大尺寸微孔及裂纹,且生长速率越来越低。膜层结合力随氧化时间延长先增大后减小,在60 min时最大,达到39.85 N。氧化时间为10 min时,膜层的电绝缘性及耐蚀性最优,100 V和500 V电压下的绝缘电阻分别达到3.11×10^(12)Ω和1.41×10^(12)Ω,腐蚀电位为-0.6298 V,腐蚀电流密度为1.332×10^(-7)A/cm^(2)。[结论]SiC_(p)/Al复合材料表面微弧氧化膜层的连续性、均匀性及生长速率均与氧化时间有关。需选择合适的氧化时间,才能制备出连续、均匀且综合性能优异的膜层。

基于多目标函数的避洪转移安置方案优化

针对目前避洪转移方案仅考虑时间或距离成本最优导致部分安置点人数分配不合理的问题,从“安全第一、就近就便、平灾结合、利于管理”的避洪转移安置方案基本要求出发,首先对安置点的适用性、分布合理性及容量大小3个方面进行分析,依据“时间、距离、适宜度和安置容量”四因素初步筛选合适的安置点。然后通过路权函数建立避洪转移时间成本矩阵,以转移时间成本和安置点的优化分配为多目标函数确定避洪转移安置点的最优分配方案。最后以TOPSIS评价方法对避洪转移安置点分配的单目标方案与多目标方案进行对比分析。结果表明:多目标方案的相对接近度大于单目标方案,基于多目标函数确定的避洪转移安置分配方案更加合理。

板翅式换热器传递函数动态模型及参数确定方法

飞机综合环控/热管理系统迫切需要建立快捷高效的换热器动态仿真模型,以满足先进控制系统设计需求。基于此,针对板翅式换热器动态模型,提出一种包含2个延迟环节和4个一阶惯性环节的传递函数矩阵形式,并从换热器机理模型出发,利用拉普拉斯变换推导模型中4个时间常数的计算公式,提出基于换热器效率的传热热阻计算关系式的辨识方法,解决了主要模型参数设置难题。以板翅式换热器为研究对象,在Simulink仿真平台搭建其传递函数动态模型,并与AMESim仿真平台搭建的机理模型进行对比分析,结果显示:2种模型所得空气和冷却水出口温度分别随入口温度和质量流量阶跃变化的动态响应曲线吻合很好,其中,4种工况空气和冷却水出口温度最大稳态偏差分别为0.034℃和0.029℃,当冷却水入口质量流量阶跃变化时,空气出口温度动态响应相对偏差最大,为9.27%,当空气入口质量流量阶跃变化时,冷却水出口温度动态响应相对偏差最大,为7.03%。

磁性氮化碳复合材料的制备及其对磷酸化肽的富集

蛋白质的磷酸化在细胞信号传导和疾病发生发展中起着重要作用,但磷酸化的动态变化和低丰度的特点使得对其直接分析有着较大的困难。为了解决磷酸化肽难离子化、检测丰度低的瓶颈问题,本研究制备了一种磁性氮化碳复合材料,结合基质辅助激光解吸电离飞行时间质谱(MALDI-TOF-MS),建立了一种对复杂样品中低丰度磷酸化肽富集与分析的方法。采用电子显微镜、红外光谱分析及X射线衍射分析等手段对合成的磁性氮化碳材料进行表征。以酪蛋白酶解产物为实验模型,发现磁性氮化碳材料能够实现对磷酸化肽的高选择性富集和高灵敏度检测,检出限为0.1 fmol。选择脱脂牛奶、人唾液和人血清为实际分析样品,发现磁性氮化碳材料对微量蛋白生物样品中磷酸化肽的分析具有较高的应用潜力。

基于Matrix Pencil的OFDM信号的TOA/AOA定位

为提高估计精度,提出一种基于低复杂度的矩阵束方法(MPM)的OFDM信号超分辨率TOA/AOA二维定位方法。首先,对信道频率响应(CFR)采用MPM方法进行时延估计,得出首径(FAP)时延,即OFDM信号的TOA估计;然后,对天线接收信号的频域阵列信号使用同样的算法进行AOA/DOA估计;最后,联合TOA、AOA估计结果在二维平面内确定目标的位置。由于载波间的相关性和相干多径的影响,使AOA估计的RMSE偏差比TOA估计大,所以对TOA估计过程中的各径幅值,设置权值对非首径的幅值进行抑制,减少对后续首径AOA估计的影响。利用OFDM信号进行仿真,其结果表明,非首径幅值抑制方法能明显提高AOA估计精度和无偏性,使整体定位误差明显改善,满足单基站或接入点室内定位的需要。

非线性广义时滞Markov跳变系统的H_(∞)滑模控制

研究了一类转移速率部分未知的广义时滞Markov跳变系统的H_(∞)滑模控制问题.首先,对广义时滞Markov跳变系统设计了积分型滑模面,并求出对应的等效控制器.之后,构建Lyapunov泛函,通过线性矩阵不等式方法得到闭环系统随机容许且满足H_(∞)性能γ的充分条件,运用加减项方法以及引入自由权矩阵,使得到的结果降低了保守性;对滑模力学分析,设计了滑模控制器,使得系统能在有限时间内到达滑模面上.最后,通过数值算例与仿真验证了理论的可行性.

结合空时上下文信息的视频SAR图像相干斑滤波

作为合成孔径雷达(synthetic aperture radar,SAR)的一种新体制,视频SAR能够对场景连续成像,在目标检测、跟踪等应用情景有独特优势。然而,相干斑的存在影响了视频SAR图像质量及后续目标检测应用。针对这一问题,提出了一种结合空时上下文信息的视频SAR图像相干斑滤波方法。该方法主要由3步构成:首先构建能表征视频SAR图像距离-方位-时间三维动态散射信息的空时上下文协方差矩阵;其次根据协方差矩阵的相似检验选取一定邻域内目标像素的相似样本;最后根据相似样本进行平均实现相干斑滤波。基于两组实测视频SAR数据开展相干斑滤波对比实验,实验结果表明所提方法能在有效抑制相干斑的同时较好地保留目标细节信息,验证了所提方法的有效性和优势。