随机钢结构的相关性与敏感性研究

参数敏感性和失效相关性对于钢结构可靠度设计、优化和评定等具有重要的价值。本文以一简单函数为例来验证相关性和敏感性计算的正确性与高效性,紧接着以1个11-弦杆的桁架结构为例,重点研究了此种结构的参数敏感性和失效相关性,分析了变形能力极限状态下可靠度的重要性量度,将α、γ、δ和η作为4种重要性量度,分别研究了各随机变量对极限状态方程的敏感性和失效概率对随机变量均值和标准差的敏感性,并研究了基于变形能力的失效模式之间的相关性;将Polak-He和SQP算法引入到了桁架结构的可靠度与敏感性计算当中。主要得出如下结论:在此类桁架结构的可靠度计算中,节点坐标的变异性的影响不容忽略,有时甚至影响很大;4种重要性量度的变化趋势大体一致;SQP法和经过合适选取缩放系数的Polak-He法具有很高的验算点搜索效率。     

对小型电子熔断器检测平台建设需求的探讨

现代高科技电子产品中小型熔断器作为过流保护元件已相当普遍。本文通过对小型熔断器行业现状及发展趋势分析,针对小型熔断器市场需求逐步增大的要求,面对现有的检测能力的不足,提出了规划建设一个以资源共享、服务行业的开放式小型熔断器公共检测平台的探讨。     

层次重要度因果分析法在建筑基础工程中的应用

基础工程质量的好坏对建筑整体至关重要.论文将层次重要度因果分析法应用到建筑基础工程中,不仅定性分析了影响建筑基础工程质量的因素,还定量分析给出了各因素的权重,在工程实践中对加强基础工程质量具有示范作用.     

基于梯形模糊数的电力变压器故障模式重要度评定方法研究

电力变压器各部件故障模式之间具有高度的复杂性和关联性,且设备价值昂贵,实施可靠性试验困难,所以难以利用传统重要度定义的方法进行重要度分析。鉴于上述问题,笔者提出了基于梯形模糊数的重要度评定方法。通过分析影响故障模式重要度的因素,建立了重要度评价指标体系,并借助德尔菲法制定了指标的评价等级及相应评分准则,引入了协调程度的概念对专家评分进行修正,并利用梯形模糊数确定指标权重,最终通过线性加权将指标与指标权重结合,得到了各故障模式的重要度。计算实例表明,该方法简便、有效,可用于电力变压器的可靠性评估及维修决策。     

WAMS通信业务的系统有效性建模与仿真

广域测量系统(wide area measurement system,WAMS)作为现代电力系统及未来智能电网的重要组成部分,其自身的可靠性至关重要,而WAMS通信业务的有效性直接影响着系统功能的实现。参照现有WAMS通信网的结构,建立了以子站相量测量单元(phasor measurement unit,PMU)通信模块、区域通信网、区域相量数据集中器(phasor data center,PDC)、骨干通信网为组件的WAMS通信网物理模型;借鉴基于全网业务性能平均值的通信网可靠性测度的研究理论,提出了融合网络通道、传输时延和数据可靠性3个特性指标的单一业务有效性的逻辑模型;根据WAMS数据业务的应用需求和汇集型通信的特点,基于可靠性串联模型给出了同一时标下所有通信业务同时有效的系统有效性指标及其计算公式;探讨了基于系统有效性的元件重要度的分析方法。对IEEE 14节点WAMS系统进行蒙特卡罗仿真,得出了该系统通信业务的系统有效性和系统元件重要度排序。     

电力系统可靠性评估中的分层均匀抽样法

为避免传统蒙特卡洛抽样方法在系统可靠性评估中抽样效率低下的问题,文中结合重要抽样法与分层抽样法的思想,提出了分层均匀抽样法,以实现对系统故障状态的高效评估。该方法综合考虑了系统故障概率与故障影响,直接对系统故障的后果进行抽样,避免了常规方法中构造M维空间抽样函数的困难。文中对系统各重故障状态进行了分层均匀抽样,并通过自寻优的方式优化分配各层的抽样次数,有效地降低了抽样方差。该方法完全避免了对系统零故障状态的抽样,使其抽样效率不受系统可靠性改变的影响,可用于高可靠性电力系统的评估。文中从理论上推导了该方法的合理性,并通过对IEEE-RTS 79系统以及修改后的高可靠性系统算例评估,证实了算法的适用性。     

事故树分析与贝叶斯网络重要度在溃坝风险分析中的应用

为降低大坝溃坝发生的概率,采用基本事件的概率重要度、临近重要度和相对重要度影响因子分析了引起溃坝的各基本事件,利用事故树分析法和贝叶斯网络引出三种重要度的定义和公式,并用重要度对各基本事件进行评估。以某大坝溃坝模型为例,将三种重要度进行了对比,结果表明贝叶斯网络和相对重要度影响因子在溃坝风险分析中具有相对较大的优势     

Truncation Error Evaluation Method for Minimal Cut Set-Based Fault Tree Analysis

The minimal cut set approach is extensively used in probabilistic safety assessments. Truncation neglecting low-probability cut sets is usually applied to determine the minimal cut sets of a manageable size. The errors in the calculated top event probability due to the truncation are not usually known. A truncation error evaluation method, which is based on the Monte Carlo simulation technique and the characteristics of coherent reliability systems, is proposed in this paper. This method can be easily applied to the most problems in probabilistic safety assessments and does not require much computation time. The applicability and accuracy of the proposed method are also described.     

A novel RBF neural network for radar emitter recognition based on Rough Sets

With the spreading of radar emitter technology, it is more difficult for traditional methods to recognize radar emitter signals. In this article, a new method is proposed to establish a novel radial basis function (RBF) neural network for radar emitter recognition based on Rough Sets theory. First of all, radar emitter signals describing words are processed by Rough Sets, and the importance weight of each attribute is obtained and the classification rules are extracted. The classification rules are the basis of initial centers of Rough k-means. These initial centers can reduce the computational complexity of Rough k-means efficiently because of a priori knowledge from Rough Sets. In addition, basis functions of neural units of an RBF neural network are improved with attribute importance weights based on Rough Sets theory. The novel network structure makes the RBF neural network more effective. The simulation results show that novel RBF neural network radar emitter recognition can recognize radar emitter signals more effectively than a traditional RBF neural network, because of the improved Rough k-means and the network structure with attribute importance weights.     

The error performance simulation for DEQPSK systems employing nonlinear phase synchronizers

Abstract

In this paper, we use the importance sampling (IS) method to evaluate the bit error rate (BER) for systems employing nonlinear synchronizers. It is shown by simulation results that the sample sizes required by the IS method for evaluating the BER of systems with nonlinear synchronizers are almost constant for various values of signal‐to‐noise ratio (SNR). This implies that the efficiency of IS to MC method approaches infinity as the SNR becomes very high. It is also shown in this paper that for differential decoding of QPSK signals, the error performance of a system with nonlinear synchronizer of size 15 is close to that of a coherent system.