快中子零功率反应堆(DF-VI)的临界事故概率分析

本文应用故障树分析方法,对快中子零功率堆(DF-Ⅵ)在启动过程中发生临界事故的可能性做了初步的定量估计。结果表明,该堆每次启动发生临界事故的概率约为10~(-6)量级,得出确保装置启动安全的首要因素是选配合格的操作人员的结论,并对设备的改进提出了一些建议.     

应用浅层测温法寻找油气藏

地温法是非地震物化探手段中的一种常用方法，在油气普查和勘探方面已得到广泛应用，并取得了显著效果。简要介绍了地温法寻找油气藏的仪器设备、基本原理、适用范围及特点，并举例说明了其应用效果。应用高精度测温仪，通过开展浅层地温测量和研究，可以达到寻找油气的目的。     

The column protocol: A high availability and low message cost solution for managing replicated data

This paper presents a quorum-based replica control protocol which is resilient to network partitioning. In the best case, the protocol generates quorums of a constant size. When some replicas are inaccessible, the quorum size increases gradually and may be as large as O(n), where n is the number of replicas. However, the expected quorum size is shown to remain constant as n grows. This is a desirable property since the message cost for accessing replicated data is directly proportional to the quorum size. Moreover, the availability of the protocol is shown to be comparably high. With the two properties—constant expected quorum size and comparably high availability—the protocol is thus practical for managing replicated data.     

完备ARRs集的生成方法及传感器优化配置应用

广泛应用于故障诊断和传感器优化、分析、证实的解析冗余关系(Analytical redundancy relations,ARRs)缺乏系统、有效的方法来产生完备ARRs集,为此,提出了一种逐次消元法。该方法以系统元关系(Primary relations,PRs)为基础,通过若干次循环消元过程,生成了完备ARRs集,同时生成了对应的假定特征矩阵(Hypothetical signature matrix,HSM);基于HSM,把传感器优化配置问题映射为一个特殊的0-1整数规划模型,并用分支定界法求解该模型。应用表明,该方法能在不降低故障检测率、隔离率的前提下减少传感器数目,降低了测试代价,对故障诊断中的传感器配置问题有借鉴意义。     

医院局域网丢包实例解析

医院局域网的日常运维管理,经常会遇到的一种故障现象就是丢包,当网络出现传输延迟、无法连接服务器数据库等异常现象以后,如何能快速找到故障原因并排除故障．这是对网络管理人员的一大挑战,网管人员应当具备处理这种网络丢包故障的能力。列举工作中遇到的几种丢包案例,总结出故障解决的经验与心得,希望能够提高大家的分析能力和解决此类网络故障的能力。     

惯性导航装置虚拟检测仪设计

惯性导航装置是一种很重要且精密的设备,故障检测和诊断是设备维修的前提,综合采用现在的虚拟检测技术,对惯性导航装置的故障检测方法进行了研究,设计了虚拟检测仪的硬件设备,开发了虚拟检测仪的软件,完成了整个虚拟检测仪的设计。     

基于改进LMD方法的风电机组齿轮箱故障诊断研究

局部均值函数的求取是局部均值分解(LMD)的关键环节。针对局部均值函数求取存在偏差进而造成模态混叠的问题,提出了一种基于局部积分均值的LMD风电机组齿轮箱故障诊断方法。该方法改变了对相邻两极值点求平均值的思路,采用求取相邻两极值点的局部积分均值,再通过滑动平均法进行平滑处理,最终得到局部均值函数。为实现风电机组齿轮箱故障诊断,首先采用改进LMD方法对信号进行降噪处理,然后采用多尺度熵提取降噪处理后信号的特征向量,最后采用极限学习机进行故障诊断。通过仿真分析,证明了该方法能有效解决模态混叠现象,提高了LMD的分解精度。试验验证分析表明,该方法的故障诊断准确率为100%,通过对比分析表明,该方法优于其他故障诊断方法,具有工程应用价值。     

Soft computing approach to fault diagnosis of centrifugal pump

Fault detection and isolation in rotating machinery is very important from an industrial viewpoint as it can help in maintenance activities and significantly reduce the down-time of the machine, resulting in major cost savings. Traditional methods have been found to be not very accurate. Soft computing based methods are now being increasingly employed for the purpose. The proposed method is based on a genetic programming technique which is known as gene expression programming (GEP). GEP is somewhat a new member of the genetic programming family. The main objective of this paper is to compare the classification accuracy of the proposed evolutionary computing based method with other pattern classification approaches such as support vector machine (SVM), Wavelet-GEP, and proximal support vector machine (PSVM). For this purpose, six states viz., normal, bearing fault, impeller fault, seal fault, impeller and bearing fault together, cavitation are simulated on centrifugal pump. Decision tree algorithm is used to select the features. The results obtained using GEP is compared with the performance of Wavelet-GEP, support vector machine (SVM) and proximal support vector machine (PSVM) based classifiers. It is observed that both GEP and SVM equally outperform the other two classifiers (PSVM and Wavelet-GEP) considered in the present study.     

A self-adjusting algorithm for byzantine agreement

Summary Byzantine Agreement is important both in the theory and practice of distributed computing. However, protocols to reach Byzantine Agreement are usually expensive both in the time required as well as in the number of messages exchanged. In this paper, we present a self-adjusting approach to the problem. The Mostly Byzantine Agreement is proposed as a more restrictive agreement problem that requires that in the consecutive attempts to reach agreement, the number of disagreements (i.e., failures to reach Byzantine Agreement) is finite. Fort faulty processes, we give an algorithm that has at mostt disagreements for 4t or more processes. Another algorithm is given forn3t+1 processes with the number of disagreements belowt ²/2. Both algorithms useO(n ³) message bits for binary value agreement. Yi Zhao is currently working on his Ph.D. degree in Computer Science at University of Houston. His research interests include fault tolerance, distributed computing, parallel computation and neural networks. He obtained his M.S. from University of Houston in 1988 and B.S. from Beijing University of Aeronautics and Astronautics in 1984, both in computer science. Farokh B. Bastani received the B. Tech. degree in electrical engineering from the Indian Institute of Technology, Bombay, India, and the M.S. and Ph.D. degrees in electrical engineering and computer science from the University of California, Berkeley. He joined the University of Houston in 1980, where he is currently an Associate Professor of Computer Science. His research interests include software design and validation techniques, distributed systems, and fault-tolerant systems. He is a member of the ACM and the IEEE and is on the editorial board of theIEEE Transactions on Software Engineering.     

航空发动机传感器故障鲁棒检测方法

研究发动机传感器故障准确检测问题,现代航空发动机数字电子控制系统对传感器的可靠性要求日益提高。针对航空发动机结构复杂,又工作在高温和高压下,常规采用的传感器故障检测方法的准确性易受到建模误差与外界扰动的影响,造成漏报或误报。为了提高检测精度,提出建立航空发动机数控系统传感器未知输入故障模型,采用特征结构配置的方法,通过配置闭环系统左特征向量实现故障检测残差对不确定性因素的干扰解耦,降低扰动对故障诊断结果的影响。用某型涡扇发动机数控系统传感器故障数字仿真试验表明,所设计的方法对范数有界的不确定量可以实现干扰解耦,抑制干扰对故障检测的影响,改善检测算法的鲁棒性,提高检测结果的准确性,同时满足在线运算的实时性要求。提高了航空发动机的可靠性,保证了安全飞行。