Flat convergence for integral currents in metric spaces

In compact local Lipschitz neighborhood retracts in weak convergence for integral currents is equivalent to convergence with respect to the flat distance. This comes as a consequence of the deformation theorem for currents in Euclidean space. Working in the setting of metric integral currents (the theory of which was developed by Ambrosio and Kirchheim) we prove that the equivalence of weak and flat convergence remains true in the more general context of metric spaces admitting local cone type inequalities. These include in particular all Banach spaces and all CAT(κ)-spaces. As an application we obtain the existence of a minimal element in a fixed homology class and show that the weak limit of a sequence of minimizers is itself a minimizer.     

On the existence of integral currents with prescribed mean curvature vector

Given an integralm-currentT ₀ in ℝ ^m+k and a tensorH of typ (m, 1) on ℝ ^m+k with values orthogonal to each of its arguments we prove the existence of an integralm-currentT with boundary ∂T=∂T ₀ having prescribed mean curvature vectorH, i. e. is a solution of      

电力变压器绕组振动声纹特性分析*

为更加准确分析变压器绕组的状态特征,本文提出一种基于多物理场耦合仿真的变压器绕组振动声纹特性分析方法。根据实验条件,建立变压器绕组振动噪声模型,考虑变压器绝缘油在噪声传播过程中的作用,对S13-M-200/10型号的油浸式变压器进行短路实验,测量油箱表面的振动加速度以及周围空间的声音信号。仿真结果与实测数据对比分析,油箱表面的振动加速度集中频率为100Hz,空间声音信号集中频率为100Hz和200Hz,验证仿真模型的有效性。最后,建立变压器机械故障的仿真模型,分析得到变压器发生机械故障时,声音信号中100Hz频率分量减少,200Hz频率分量增加,为变压器绕组故障诊断提供依据。     

QoS-aware resource allocation and fault tolerant operation in hybrid SDN using stochastic network calculus

Mobile edge computing (MEC) is a key feature of next-generation mobile networks aimed at providing a variety of services for different applications by performing related processing tasks closer to the users. With the advent of the next-generation mobile networks, researchers have turned their attention to various aspects of edge computing in an effort to leverage the new capabilities offered by 5G. So, the integration of software defined networking (SDN) and MEC techniques was seriously considered to facilitate the orchestration and management of Mobile Edge Hosts (MEH). Edge clouds can be installed as an interface between the local servers and the core to provide the required services based on the known concept of the SDN networks. Nonetheless, the problem of reliability and fault tolerance will be of great importance in such networks. The paper introduced a dynamic architecture that focuses on the end-to-end mobility support required to maintain service continuity and quality of service. This paper also presents an SDN control plane with stochastic network calculus (SNC) framework to control MEC data flows. In accordance with the entrance processes of different QoS-class data flows, closed-form problems were formulated to determine the correlation between resource utilization and the violation probability of each data flow. Compared to other solutions investigated in the literature, the proposed approach exhibits a significant increase in the throughput distributed over the active links of mobile edge hosts. It also proved that the outage index and the system’s aggregate data rate can be effectively improved by up to 32%.     

基于互信息熵-近红外光谱的过程模式故障检测

近红外光谱分析在工业过程故障检测方面具有独特的优势,是一种准确且高效的方法。结合互信息熵和传统的主成分分析,对近红外光谱特征信息进行提取,通过构建过程的模式来刻画工业过程的运行状态。利用近红外光谱数据,从有机分子含氢基团振动信息中获取工业系统的过程模式,从微观分子层面探索提高工业过程故障检测准确率的有效方法,结合贝叶斯统计学习技术,提出了基于近红外光谱数据的工业过程故障检测技术。针对近红外光谱信息量丰富,谱带较宽,特征性不强的特点,首先对工业过程不同运行状态下的近红外光谱吸光度数据进行一阶导数预处理,采用主成分分析法（principal component analysis,PCA）压缩光谱数据量,扩大不同运行状态下光谱特征信息的差异性,提取光谱的内部特征信息。然后采用互信息熵（mutual information entropy,MIE）作为光谱特征信息相关性度量函数,基于最小冗余最大相关算法进一步减少光谱特征信息间的冗余并最大化光谱特征信息与类别的相关性,弥补了PCA无监督特征波长选择的不足,提出一种基于PCA-MIE的过程模式构建方法,获得的过程模式子集更紧凑更具类别表现力。再利用贝叶斯统计学习算法,根据后验概率对构建的模式子集进行决策,判别生产过程的正常状态和故障状态。由于过程模式子集结合了PCA浓聚方差的优势和互信息熵相关性测度的特征信息选择方法,蕴含了更多的近红外光谱的本质信息与内在规律,从而更能刻画工业过程的运行状态。接着,设置测试准确率TA作为评估标准,用以评价故障检测方法的性能效果。最后利用某化工厂提供的原油脱盐脱水过程近红外光谱数据对所提方法进行验证,并与传统近红外光谱特征信息提取方法PCA和MIE方法性能进行对比分析,结果表明基于PCA-MIE的过程模式故障检测方法几乎在所有维数子集上性能都优于其他两种方法,在特征维数为18维时获得最高的准确率94. 6%,证明了方法的优越性。     

Persistent current in metals with a large dephasing rate

In a weakly disordered metal electron interactions are responsible for both decoherence of the quasi-particles as well as for quantum corrections to thermodynamic properties. We consider electrons which are interacting with two-level-systems. We show that the two-level-systems enhance the average equilibrium (“persistent”) current in an ensemble of mesoscopic rings. The result supports the recent suggestion that two puzzles in mesoscopic physics may be related: The low temperature saturation of the dephasing time and the high persistent current in rings. Received 26 May 2000     

Detection,isolation and identification of multiple actuator and sensor faults in nonlinear dynamic systems: Application to a waste water treatment process

The goal in many fault detection and isolation schemes is to increase the isolation and identification speed. This paper, presents a new approach of a nonlinear model based adaptive observer method, for detection, isolation and identification of actuator and sensor faults. Firstly, we will design a new method for the actuator fault problem where, after the fault detection and before the fault isolation, we will try to estimate the output of the instrument. The method is based on the formation of nonlinear observer banks where each bank isolates each actuator fault. Secondly, for the sensor problem we will reformulate the system by introducing a new state variable, so that an augmented system can be constructed to treat sensor faults as actuator faults. A method based on the design of an adaptive observers’ bank will be used for the fault treatment. These approaches use the system model and the outputs of the adaptive observers to generate residues. Residuals are defined in such way to isolate the faulty instrument after detecting the fault occurrence. The advantages of these methods are that we can treat not only single actuator and sensor faults but also multiple faults, more over the isolation time has been decreased. In this study, we consider that only abrupt faults in the system can occur. The validity of the methods will be tested firstly in simulation by using a nonlinear model of waste water treatment process with and without measurement noise and secondly with the same nonlinear model but by using this time real data.     

模糊重要度分析方法的研究

阐述故障树分析中从精确到模糊的重要分析法,提出了模糊重要度分析的新方法－中值法,它是用模糊故障树分析技术对结构复杂的新型系统进行可靠性、贮存可靠性研究的重要组成部分。同时,本文用两种模糊重度分析方法对一故障树作了重要度分析。     

产品质量危机事件原因挖掘模型研究

为有效解决因产品质量危机事件发生原因揭示不准确而导致应对措施选择与实施不当问题,根据产品质量危机影响因素发掘结果,提取出了产品质量危机事件可能原因,采用故障树法构建了质量危机事件潜在原因关系模型;将故障树法和贝叶斯网络相结合,基于专家调查与模糊集理论,推理出底层原因先验概率算法,并将其先验概率输入贝叶斯网络模型,获得底层原因后验概率及关键重要度,将后验概率及关键重要度共同作为质量危机事件关键原因诊断依据,构建了质量危机事件原因挖掘模型;通过实际案例验证了关键原因挖掘结果的准确性,为企业挖掘质量危机事件发生原因提供了理论依据。     

Fault identification in nonlinear hybrid systems

The problem of fault identification in hybrid systems is investigated. It is assumed that the hybrid systems under consideration consist of a finite automaton, the set of nonlinear differential equations, and so-called mode activator that coordinates the action of these two parts. To solve the fault identification problem, sliding mode observers are used. The suggested approach for constructing sliding mode observers is based on the reduced order model of the original system. This allows to reduce complexity of sliding mode observers and relax the limitations imposed on the original system. Examples illustrate details of the solution.