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1.
When applying a diagnostic technique to complex systems, whose dynamics, constraints, and environment evolve over time, being able to re-evaluate the residuals that are capable of detecting defaults and proposing the most appropriate ones can quickly prove to make sense. For this purpose, the concept of adaptive diagnosis is introduced. In this work, the contributions of information theory are investigated in order to propose a Fault-Tolerant multi-sensor data fusion framework. This work is part of studies proposing an architecture combining a stochastic filter for state estimation with a diagnostic layer with the aim of proposing a safe and accurate state estimation from potentially inconsistent or erroneous sensors measurements. From the design of the residuals, using α-Rényi Divergence (α-RD), to the optimization of the decision threshold, through the establishment of a function that is dedicated to the choice of α at each moment, we detail each step of the proposed automated decision-support framework. We also dwell on: (1) the consequences of the degree of freedom provided by this α parameter and on (2) the application-dictated policy to design the α tuning function playing on the overall performance of the system (detection rate, false alarms, and missed detection rates). Finally, we present a real application case on which this framework has been tested. The problem of multi-sensor localization, integrating sensors whose operating range is variable according to the environment crossed, is a case study to illustrate the contributions of such an approach and show the performance.  相似文献   
2.
We generalize the Jensen-Shannon divergence and the Jensen-Shannon diversity index by considering a variational definition with respect to a generic mean, thereby extending the notion of Sibson’s information radius. The variational definition applies to any arbitrary distance and yields a new way to define a Jensen-Shannon symmetrization of distances. When the variational optimization is further constrained to belong to prescribed families of probability measures, we get relative Jensen-Shannon divergences and their equivalent Jensen-Shannon symmetrizations of distances that generalize the concept of information projections. Finally, we touch upon applications of these variational Jensen-Shannon divergences and diversity indices to clustering and quantization tasks of probability measures, including statistical mixtures.  相似文献   
3.
In this article, a way to employ the diffusion approximation to model interplay between TCP and UDP flows is presented. In order to control traffic congestion, an environment of IP routers applying AQM (Active Queue Management) algorithms has been introduced. Furthermore, the impact of the fractional controller PIγ and its parameters on the transport protocols is investigated. The controller has been elaborated in accordance with the control theory. The TCP and UDP flows are transmitted simultaneously and are mutually independent. Only the TCP is controlled by the AQM algorithm. Our diffusion model allows a single TCP or UDP flow to start or end at any time, which distinguishes it from those previously described in the literature.  相似文献   
4.
We address the problem of telegraphic transport in several dimensions. We review the derivation of two and three dimensional telegrapher’s equations—as well as their fractional generalizations—from microscopic random walk models for transport (normal and anomalous). We also present new results on solutions of the higher dimensional fractional equations.  相似文献   
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6.
高速列车轴承可靠性评估关键力学参量研究进展   总被引:3,自引:2,他引:1  
轴承是高速列车牵引传动和轮轴系统的关键零部件. 受列车运行过程中电机转矩、齿轮啮合以及轮轨随机激励的影响,轴承可能发生疲劳破坏, 严重影响高速列车的行车安全.我国特有的复杂运用条件对轴承部件的疲劳性能提出了更高的要求,而轴承疲劳可靠性的基础理论和关键技术是我国轴承正向设计研发中的薄弱环节.可靠性评估方面的相关研究在解决轴承可靠性研究的瓶颈问题中起到了承上启下的关键作用.高速列车轴承可靠性评估手段与技术旨在获得使用环境中轴承可靠性评估的关键力学参量,并以此推动复杂激励下轴承疲劳可靠性理论研究. 因此,需要哪些关键力学参量并且在复杂的实际使用环境下如何去获取这些力学参量是进行高速列车轴承可靠性评估的关键所在.本文首先概述了高速列车轴承所处的复杂使用环境及运用中的主要失效模式,并据此分析了高速列车轴承可靠性评估所需的关键力学参量,强调了轴承内部滚滑行为和载荷分布在可靠性评估和轴承状态监测中的重要作用,之后从计算模型和测试技术等方面系统阐述了针对这两个关键力学参量的研究进展.最后提出了在高速列车轴承可靠性评估关键力学参量特征及测试技术研究中值得关注的若干问题.   相似文献   
7.
为提高生鲜羊肉储存期内(4,8和20 ℃环境)挥发性盐基氮(TVB-N)的近红外光谱(NIR)检测的稳定性和准确性,选取特征光谱和预测模型是关键步骤。以121个羊肉样品为实验对象,采集生鲜羊肉680~2 600 nm波段的近红外光谱。以多元散射校正(MSC)、标准正态变换(SNV)等散射校正方法,Savitzky-Golay卷积平滑(SGS)、移动平均平滑(MAS)等平滑处理方法,以及归一化(Normalization)、中心化(Centering)、标准化(Autoscaling)等尺度缩放方法分别预处理光谱数据后建立偏最小二乘法(PLS)预测模型。比较发现SGS处理的光谱建模效果最好。利用蒙特卡洛采样(MCS)法及马氏距离法(MD)消除了羊肉光谱的5个异常数据。运用光谱-理化值共生距离(SPXY)算法划分总样本的75%(87个)为校正集样本,剩余29个为验证集样本,利用竞争性自适应重加权法(CARS)、无信息变量消除法(UVE)、改进的无信息变量消除法(IUVE)和连续投影算法(SPA)提取特征光谱得到的波长个数分别为14,713,144和15。将全光谱和4种方法提取的特征波长作为输入变量建立预测模型,CARS提取的波长所建立模型的性能优于UVE、IUVE和SPA提取的波长所建立模型的性能,表明CARS方法可以有效简化输入变量并提高预测模型的性能。改进后得到的IUVE法相比于UVE法,筛选出的波长数更少且模型性能有所提升。以提取的特征波长建立PLS,支持向量机(SVM)和最小二乘支持向量机(LS-SVM)预测模型,SVM模型得到最优的校正集预测结果,其中CARS-SVM预测模型的校正决定系数(R2C)和校正均方根误差(RMSEC)分别为0.939 1和1.426 7,最优的验证集预测效果为LS-SVM预测模型得到,其中IUVE-LS-SVM预测模型的验证决定系数(R2V)和验证均方根误差(RMSEV)分别为0.856 8和1.886 2。基于近红外特征光谱建立简化、优化的生鲜羊肉储存期TVB-N预测模型,为实现快速无损检测生鲜羊肉中的TVB-N浓度提供技术支持。  相似文献   
8.
By using the perpetual cutoff method, we prove two discrete versions of gradient estimates for bounded Laplacian on locally finite graphs with exception sets under the condition of CDE(K,N). This generalizes a main result of F. Münch who considers the case of CD(K, ) curvature. Hence, we answer a question raised by Münch. For that purpose, we characterize some basic properties of radical form of the perpetual cutoff semigroup and give a weak commutation relation between bounded Laplacian Δ and perpetual cutoff semigroup PtW in our setting.  相似文献   
9.
发展了一套固态亚毫米波外差干涉系统和一种基于全相位快速傅里叶变换(apFFT)的相位处理方法用 于测量 HL-2M 初始等离子体电子密度。该系统采用平面型二极管倍频技术对低频的锁相微波源进行高次倍频以 产生功率大于 0.1MW、频率 306.9GHz 的探测波。基于 apFFT 的相位处理数值算法可以从原始信号中提取相位信 息,缓解由可能的高水平密度扰动导致的相位跳变。系统的固有时间分辨率为 5μs,电子密度测量范围在 1016~1020m−3。在 HL-2M 装置首次实验期间,该系统被安装在中平面上,利用装置内壁反射实现干涉测量,成功 测量了线平均电子密度。   相似文献   
10.
Low-pressure gas discharge plasmas are known to be strongly affected by the presence of small dust particles. This issue plays a role in the investigations of dust particle-forming plasmas, where the dust-induced instabilities may affect the properties of synthesized dust particles. Also, gas discharges with large amounts of microparticles are used in microgravity experiments, where strongly coupled subsystems of charged microparticles represent particle-resolved models of liquids and solids. In this field, deep understanding of dust–plasma interactions is required to construct the discharge configurations which would be able to model the desired generic condensed matter physics as well as, in the interpretation of experiments, to distinguish the plasma phenomena from the generic condensed matter physics phenomena. In this review, we address only physical aspects of dust–plasma interactions, that is, we always imply constant chemical composition of the plasma as well as constant size of the dust particles. We also restrict the review to two discharge types: dc discharge and capacitively coupled rf discharge. We describe the experimental methods used in the investigations of dust–plasma interactions and show the approaches to numerical modelling of the gas discharge plasmas with large amounts of dust. Starting from the basic physical principles governing the dust–plasma interactions, we discuss the state-of-the-art understanding of such complicated, discharge-type-specific phenomena as dust-induced stratification and transverse instability in a dc discharge or void formation and heartbeat instability in an rf discharge.  相似文献   
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