Reduced State Enumeration?Another Algorithm for Reliability Evaluation

This new algorithm for reliability evaluation is a refinement of the state enumeration method. The set of enumerated states is different for different parts of the fault tree, in particular the number of enumerated states does not necessarily increase towards the top event. This method makes it feasible to treat some large fault trees analytically rather than by Monte Carlo simulation. A lot of research remains to be done, like programming and evaluating the algorithm, and finding intrinsic measures of difficulty for fault trees.     

A New Real-Time Reliability Prediction Method for Dynamic Systems Based on On-Line Fault Prediction

While a specific system is in use, its reliability will decrease gradually after the infant mortality period because of the components' degradation, or external attacks. Thus, reliability is a natural characteristic of a system's health, and can be used for condition monitoring & predictive maintenance. This paper introduces a new real-time reliability prediction method for dynamic systems which incorporates an on-line fault prediction algorithm. The factors that may reduce a system's reliability are modeled as an additive fault input to the system, and the fault is assumed to be varying linearly with time, approximately. The time-varying fault is roughly estimated based on a modified particle filtering algorithm at first. Then, as a time series, the fault estimate sequence is smoothed, and predicted by an exponential smoothing method. Mathematical analysis shows that the effects of the system, and measurement noises on the fault estimates are greatly reduced by exponential smoothing, which indicates that the comparatively high accuracy of the fault estimates & predictions is guaranteed. Based on the particle filtering & fault prediction results, the whole system's predictive reliability is computed through a Monte Carlo simulation strategy. The effectiveness of the proposed real-time reliability prediction method is validated by a computer simulation of a three-vessel water tank system.     

Efficient Evaluation of System Reliability by Monte Carlo Method

This paper presents a new Monte Carlo method to estimate the reliability of a large complex system represented by a reliability block diagram or by a fault tree. Two binary functions are introduced; one dominates the system structure function and the other is dominated by the structure function. These functions can be constructed easily by using part of path sets and cut sets of the system. Through the use of these binary functions, two variance-reducing techniques (control variate and importance sampling) are applied to the Monte Carlo evaluation of the system reliability. We prove that the new Monte Carlo method gives a reliability estimate with a smaller variance than that of the crude Monte Carlo method.     

Interval methods for fault-tree analysis in robotics

This paper describes a novel technique, based on interval methods, for estimating reliability using fault trees. The approach encodes inherent uncertainty in the input data by modeling these data in terms of intervals. Appropriate interval arithmetic is then used to propagate the data through standard fault trees to generate output distributions which reflect the uncertainty in the input data. Through a canonical example of reliability estimation for a robot manipulator system, we show how the use of this novel interval method appreciably improves the accuracy of reliability estimates over existing approaches to the problem of uncertain input data. This method avoids the key problem of loss of uncertainty inherent in some approaches when applied to noncoherent systems. It is further shown that the method has advantages over approaches based on partial simulation of the input-data space because it can provide guaranteed bounds for the estimates in reasonable times     

基于现场数据的地铁车辆牵引系统可靠性分析

牵引系统的可靠性对于地铁车辆的安全运行极为重要.文章结合某地铁线路的现场车辆检修记录,采用故障树法和蒙特卡洛法分析牵引系统的可靠性.首先,根据现场检修数据建立地铁牵引系统的故障树模型,并对所建立的故障树模型进行定性、定量分析.其次,运用蒙特卡洛法对地铁牵引系统进行可靠性仿真.最后,确定了牵引系统的薄弱环节和各部件的重要...     

基于蒙特卡罗的故障树模型的仿真研究

定量计算顶事件发生的概率是进行故障树分析的重要环节,通常采用公式计算时,不仅计算量大,而且计算过程复杂、繁琐,很容易出错。本文利用蒙特卡罗模拟法对故障树模型进行仿真,从而精确计算出顶事件发生概率以及其他一些可靠性指标,通过实例证明,此方法简单易行,计算结果精度高,对复杂系统的可靠性分析具有十分重要意义。     

Determination of Reliability Using Event-Based Monte Carlo Simulation Part II

Analytic determination of reliability of general systems becomes increasingly difficult as the system complexity increases. Inclusion of s-dependent components and/or allowing repair of failed components makes such analysis virtually impossible. This paper extends the Monte Carlo simulation procedure of Kamat and Riley to estimate the reliability of such systems. A computer program finds all minimal tie-sets from a coded reliability flow graph and performs the simulation. In each replication, the s-dependency of failures and/or repair of failed components is incorporated in the generation of pseudorandom time-to-failure through modification of the failure rate for each affected component. A search through the minimal tie-sets identifies the success or failure of the system at each value of required time of operation. The computer program estimates the system reliability as a function of time with approximate individual (for each time point) 95 percent symmetric s-confidence limits.     

考虑时间因素的不同基本门故障概率计算

在门级电路的可靠性概率评估方法中,基本门的故障概率p一般人为设定或以常数形式出现.考虑到不同基本门的故障概率具有随时间变化的特性并结合其输入导线,本文构建了考虑输入负载的随时间变化的不同基本门的故障概率模型.理论分析与实验结果表明,基于弱链接模型的双峰对数正态分布更适合用来表示输入导线故障概率的时间分布.用本文方法、美国军用标准MIK-HDBK-217及Monte Carlo方法计算了ISCAS85基准电路的可靠度并进行了比较,还通过了行业标准的检验,结果验证了本文所构建模型的合理性.     

A Second-Order Moments Method for Uncertainty Analysis

The system moments approach is extended to combine random variables for large systems. A computer code, COSMOS, has been developed to propagate uncertainties for systems which contain up to 100 components. Extension of the method to very large systems is possible by modular evaluation. An example illustrates the method for evaluating the distribution of the top event unavailability for a fault tree. Advantages of the method include small required execution times and the avoidance of random number generation. Application of the method to Boolean sum-of-products representations of fault trees provides results which are consistent with the Monte Carlo method since, for this special case, higher order derivatives are zero. Serious limitations to the method include: unquantifiable accuracy for functions whose higher derivatives are non-zero (as is often the case), inability to model s-dependent failures as the moments equations assume s-independence, and difficulty in improving the accuracy of the method (compared with Monte Carlo evaluation which may be arbitrarily improved).     

Constructing fault trees for advanced process control systems $application to cascade control loops

A systematic approach to construct fault trees for advanced process control systems is presented in this paper. For illustration purpose, the proposed method is explained with a specific feedback scheme, i.e., the cascade control strategy. The digraph configuration of a standard system is first described and analyzed in detail. On the basis of a series of qualitative simulation studies, all failure mechanisms can be identified and summarized with a set of generalized fault-tree structures. The fault trees produced with the conventional digraph-based techniques are shown to be not as comprehensive as the ones constructed with the proposed approach. To demonstrate the correctness of our analysis, the successful application of the proposed structures to a heat exchange process is presented. In addition, the resulting fault tree is compared with one obtained from a single-loop feedback control system and the trade-off between the two in system reliability and control performance is assessed accordingly.     

脉冲响应函数在Monte Carlo模拟中的应用研究

MonteCarlo方法是研究复杂面光源入射条件下光在生物组织分布规律的唯一有效手段,但直接的MonteCarlo模拟存在计算量大、收敛速度慢的问题。通过引入生物组织脉冲响应函数的概念,利用卷积方法计算光在穿过组织一定深度后的分布规律,编制了相应的程序并进行了大量计算机模拟,在此基础上,提出了一种对模拟结果进行评价的方法,利用该方法分析了光源离散量与脉冲响应函数模拟量对光场分布计算结果的影响,证明基于脉冲响应函数的MonteCarlo模拟可以极大地提高计算效率和收敛速度。     

Fast and accurate FPGA-based framework for processor architecture vulnerability analysis

This paper presents a fast, accurate, and flexible FPGA-based fault emulation platform, namely FARAVAM that can be exploited for AVF analysis in modern microprocessors. The proposed approach provides fault injection capabilities supporting automatic modification of post-synthesis net-lists and introduces a highly controllable and observable transient fault analysis environment. The presented vulnerability analysis platform using both exhaustive and random fault emulation approaches, provides useful information for identifying areas threatening reliability to make processors more fault tolerant. We applied our platform for extracting the best trade-offs between precision and speed up in vulnerability analysis of MIPS processor. The experimental results indicate that in addition to having high precision we obtain about seven orders of magnitude speed up in comparison with simulation based vulnerability analysis techniques.     

Survey of reliability and availability evaluation of complex networks using Monte Carlo techniques

Generally there are four main difficulties in evaluating complex large-scale system reliability, availability and MTBF: the system structure may be very complex; subsystems may follow various failure distributions; subsystems may conform to arbitrary failure and repair distributions for maintained systems; the failure data of subsystems are sometimes not sufficient, reliability test sample sizes tend to be small. It is difficult and often impossible to obtain s-confidence limits of them by classical statistics. Monte Carlo technique combined with Bayes method is a powerful tool to solve this kind of problems. In this survey, the typical existing Monte Carlo reliability, availability and MTBF simulation procedures, variance reduction methods, and random variate generation algorithms are analyzed and summarized. The advantages, drawbacks, accuracy and computer time of Monte Carlo simulation in evaluating reliability, availability and MTBF of a complex network are discussed. Finally, some conclusions are drawn and a general Monte Carlo reliability and MTTF assessment procedure is recommended.     

Ensuring the reliability of electron beam crosslinked electric cables by the optimization of the dose depth distribution with Monte Carlo simulation

The reliability of electric cables and wires using electron beam crosslinked polymers as isolator materials strongly depends on the accuracy in predicting the dose deposited during irradiation. This paper presents the main reliability issues that can be encountered in field operation, experimental data showing the criticality of the dose parameter, and proposes the use of a built-in reliability approach based on Monte Carlo simulation to design optimum processing conditions. The main requirements and advantages of the Monte Carlo based methodology are discussed in conjunction with the limitations of the traditional heuristic calculation procedure. Finally, Monte Carlo simulation is used for the first time to point out some relevant effects that occur during processing and that can lead to severe dose estimation errors.     

Reliability Assessment of Microgrid Using Sequential Monte Carlo Simulation

Sequential Monte Carlo simulation method is introduced to the reliability assessment of microgrid,and a Weibuil distribution wind speed model is built to simulate the hourly wind speed of a specific site.Wind turbine generator model combined with a two-state reliability model is applied to Monte Carlo simulation method,and results show that the wind turbine reliability model works well with sequential Monte Carlo simulation.A two-state reliability model of micro gas turbine and a load model from IEEE reliability test system(IEEE RTS)are also introduced to the reliability evaluation of microgrid.Case studies show that Monte Carlo simulation method is flexible and efficient dealing with microgrid consisting of renewable resources with fluctuation characteristics.     

FTA在波峰焊接缺陷分析中的应用

故障树分析法(FTA)是系统可靠性、安全性分析的重要方法之一。本文将FTA应用于波峰焊接缺陷分析,建立焊接缺陷的故障树图,并分析提出提高焊点品质的改进措施。     

一种FPGA抗辐射工艺映射方法研究

 提出一种基于部分TMR和逻辑门掩盖的FPGA抗辐射工艺映射算法FDRMap,以及一个基于蒙特卡洛仿真的并行错误注入和仿真平台.该平台和算法已经应用到复旦大学自主研发的FPGA芯片FDP4软件流程的工艺映射模块.实验结果表明,FDRMap能够在增加14.06%LUT数目的前提下,降低电路的抗辐射关键度32.62%;与单纯采用部分TMR的方法相比,在节省12.23%的LUT数目同时,还能额外降低电路关键度12.44%.     

A New Monte Carlo Method for Evaluating System-Failure Probability

This paper proposes, under a rare-event assumption, a new ``Coverage Monte Carlo' method for evaluating the top-event probability of a coherent fault tree. All the min cuts are assumed to be known. A Karp-Luby Monte Carlo (KLM) estimator with minimum variance is derived in a different manner. The KLM evaluates an inclusion-exclusion formula excluding the first sum of products. A new coverage Monte Carlo (NCM) estimator evaluates the formula excluding the first and the second sums of products. The NCM yields an estimator with a smaller variance than the KLM which becomes a linear time procedure in the number of min cuts. Upper bounds on the numbers of trials necessary to attain a given coefficient of variation are derived for KLM and NCM. The bounds can be calculated before any Monte Carlo trials. The KLM requires at least 8 times more trials than the NCM. Given sufficient computer memory to implement an alias sampling method, the NCM requires less computation time than the KLM when an accurate estimate is required. The NCM is more favorable when the deterministic bounding practice based on the first and second sums of products yields a smaller relative error. The NCM is consistent with the fact that deterministic bounds have been computed.     

故障树分析法在控制器中的应用

叙述了故障树分析法在控制电路中的应用。根据分析结果,识别故障危险源,评价系统危险、风险,并采取改进措施以提高产品的可靠性和安全性。     

Polarimetric channel characterization of foliage for performanceassessment of GPS receivers under tree canopies

The attenuation, depolarization, and fluctuation of a microwave signal going through a tree canopy are investigated by developing a Monte Carlo based coherent scattering model. In particular, the model is used to analyze the performance of Global Positioning System (GPS) receivers under tree canopies. Also the frequency and time-domain channel characteristics of a forest are investigated when a transmitter is outside and a receiver is inside a forest. A fractal algorithm (Lindenmayer system) is used to generate the structure of coniferous or deciduous trees whose basic building blocks are arbitrarily oriented finite cylinders, thin dielectric needles, and thin dielectric disks. Attenuation and phase change of the mean field through foliage is accounted for using Foldy's approximation. Scattering of the mean field from individual tree components and their images in the underlying ground plane are computed analytically and added coherently. Since tree trunks and some branches are large compared to the wavelength and may be in the close proximity of the receiver, a closed-form and uniform expression for the scattered near-field from dielectric cylinders is also developed. Monte Carlo simulation of field calculation is applied to a cluster of trees in order to estimate the statistics of the channel parameters, such as the probability density function (pdf) of the polarization state of the transmitted field, path loss, and the incoherent scattered power (the second moment of the scattered field), as a function of the observation point above the ground