道路行车系统中人的可靠性研究

随着人-车-路-环境系统复杂性的增加和交通事故数量的上升,新型交通设备对其使用者的素质与适应性提出了全面的要求,要提高道路行车系统的整体可靠性,必须对人的可靠性进行分析研究.从人的生理、心理、教育训练、驾车技能等因素对驾驶员可靠性的相关影响进行了探讨.分析了影响驾驶员的可靠性因素,研究了驾驶员的可靠性模型,提出建立有助于驾驶员可靠性分析研究的综合数据库,最后从理论上分析总结了提高驾驶员可靠性的措施从而得出提高道路行车安全的有效途径.     

驾驶员可靠性筛选数学模型分析

利用随机分组测试理论和算法,建立了汽车驾驶员安全可靠性筛选的定量分析数学模型,在统计分析观察时间段的基础上,可以筛选出安全可靠的驾驶员,驾驶员年龄段,为选拔汽车驾驶员,提高驾驶员素质,防止人为差错导致交通事故,提供理论依据.     

政府监管下的企业安全生产行为研究——基于前景理论的演化博弈分析

针对我国频发的企业安全生产事故问题,从监管部门的角度出发将前景理论引入到企业安全生产的监管研究中,并运用演化博弈理论,构建企业与监管部门的博弈支付矩阵来分析二者的博弈过程,从而得到影响企业安全生产行为的影响因素及约束条件.结果表明:企业安全生产行为主要受安全生产成本、监管部门的惩罚力度、安全事故发生概率、安全事故给企业带来的损失、监管成本等因素的影响;由于不同企业风险规避系数不同,政府补贴可能会产生负面效应,在政府补贴失效的情况下可采取加大监管力度与处罚强度的办法.     

认知性VDT持续监控作业人因可靠性动态预测方法

结合N-back任务范式和持续操作测试(CPT)任务范式,设计出模拟认知性VDT持续监控作业的实验.根据实验数据:分别对脑力负荷评估指标体系中的6个评估指标在20个作业时间段的均值进行方差分析,差异显著;训练非线性自回归神经网络模型(NAR),对不同作业时间段脑力负荷在评估指标上发生的变化进行动态预测;再结合认知性VDT持续监控作业人因可靠性评估模型对人因可靠性概率进行预测.研究结果表明:该方法可动态预测不同时间段作业者的人因可靠性,实现认知性VDT持续监控作业任务的动态分配,提高系统可靠性.     

基于无线网络的塔吊群防碰撞系统的研究

根据无线网络的特点与塔吊群协同作业的安全要求,研究了工业环境下无线网络的实时性和可靠性,成功研制了塔吊群防碰撞系统,预防塔吊间的碰撞问题.     

Boeing737-300/400机队可靠性等级预测研究

为了研究航空公司机队可靠性等级预测问题,提出一种基于灰色关联与支持向量机(SVM)的航空公司机队可靠性等级预测模型.从某航空公司B737-300/400机队的可靠性月报中,得到影响机队可靠性等级的9个指标;应用灰色关联法对机队可靠性等级和指标进行相关性分析,就各个指标与机队可靠性等级之间的关联度进行了排序;采用基于径向基核函数(RBF)的支持向量机(SVM)建立了航空公司机队可靠性等级预测模型.以某航空公司B737-300/400机队为例进行了可靠性等级预测分析,验证了所提方法的有效性.     

基于改进灰色GM(1,1)马尔柯夫模型的煤矿事故百万吨死亡率预测

煤矿安全事故预防和控制是煤矿安全评价和决策的基础.灰色预测适合于时间短、数据量少和波动不大的系统对象,而马尔可夫链理论适用于预测随机波动大的动态过程.结合灰色预测GM(1,1)模型和马尔可夫链理论的优点,提出了一种改进的灰色马尔可夫GM(1,1)模型.利用改进的GM(1,1)模型进一步拟合煤矿人因失误事故的发展变化趋势,并以此为基础进行马尔柯夫预测,提高预测效果.以2000-2010年全国煤矿事故百万吨死亡率为例进行了预测分析,结果表明模型既能揭示煤矿人因失误事故百万吨死亡率变化的总体趋势,又能克服随机波动性数据对预测精度的影响,具有较强的工程实用性,并对煤矿人因失误安全事故的预测和控制有一定的实际意义.     

基于逐步回归分析和BP_Adaboost算法的危险驾驶行为辨识

为准确辨识车辆在行驶过程中可能出现的异常加减速,压线行驶,右侧超车驾驶行为,以便于及时给予驾驶员信息反馈和安全预警,使车辆保持安全的运行状态.首先通过虚拟驾驶仿真实验平台,采集驾驶行为的48种车辆运行数据对实验数据进行预处理,获得实验样本1492组;其次利用逐步回归分析对原始数据进行降维处理,并选取其中的最优回归模型获得特征参数;将提取的特征参数数据输入到BP_Adaboost多分类网络中,训练BP_Adaboost多分类网络,对上述驾驶行为进行识别;最后该模型与BP神经网络进行识别结果对比分析.结果表明模型识别率相较于BP神经网络提高了8.81%,达到92.93%,能进行更加有效的安全预警.     

可靠性分析中的最小二乘支持向量机分类方法

为了提高支持向量分类机在处理大样本可靠性问题时的计算效率,将最小二乘支持向量分类机引入到可靠性分析中,使得支持向量机中的二次规划问题转化为求解线性方程组问题,减少了计算量.数值算例表明:基于最小二乘支持向量分类机的可靠性方法与基于支持向量分类机的可靠性方法具有一样的计算精度,而且前者的计算效率明显优于后者.     

基于改进SFLA对立体仓库系统堆垛机作业路径的优化

给出了求解自动化立体仓库堆垛机作业路径优化问题的一种新算法,改进的蛙跳算法.堆垛机作业路径优化是自动化立体仓库问题中重要一个环节,本身又是一个NP难题,所以对它的研究有着重要的意义.蛙跳算法,作为新的群智能优化算法,有较多优点,但目前对它的应用研究范围较窄,所以做这方面尝试性的研究.最后通过实例仿真,验证了算法的有效性.故不仅拓宽了蛙跳算法的应用范围,而且也给本身求解方法不多的堆垛机作业路径优化问题提供了一种新的解决方法.     

基于粒子群优化Kriging模型的边坡可靠度分析

采用传统极限平衡法进行边坡可靠度分析时,不可避免会遇到一个问题,即边坡功能函数形式的高度非线性以及隐含性.对于隐式功能函数,传统的求解方法是通过对功能函数进行多次迭代,从而得到安全系数值.但是由于功能函数的形式较为复杂,导致迭代计算的过程变得尤为繁琐且效率低下.鉴于传统边坡可靠度分析中存在的安全系数计算繁琐耗时的问题,提出一种基于粒子群优化(PSO)算法的自动采样Kriging代理模型方法,该方法可以代替功能函数的作用进行安全系数的求解.首先用拉丁超立方抽样方法(LHS)选取少量土体参数组,并通过极限平衡法求出对应的安全系数,将土体参数组和安全系数作为初始样本建立Kriging模型;其次由粒子群优化算法将最有期望改善模型拟合精度的样本点添加到样本集合中,以逐步迭代提升Kriging模型的计算精度;最后集合经典蒙特卡洛模拟(MCS)获得边坡的破坏概率.通过一个双层的土质边坡算例分析,证明了该方法可以实现准确高效的安全系数计算,尤其是在安全系数计算量十分庞大的情况下可以大大节省计算时间,是一种有效的边坡工程稳定可靠度分析方法.     

3D mathematical model and numerical simulation for laying marine cable along prescribed trajectory on seabed

In this paper, we establish a mathematical model, that is, an initial-boundary value problem of partial differential equations (PDE), to describe the three dimensional (3D) motion of a marine cable being laid onto the seabed of varying depth. Based on this PDE model, a numerical method for simulating dynamically the moving process of marine cable is developed, which can be used to determine the cable laying operations in practice such that the marine cable can be laid on the prescribed position on seabed.     

Some Reliability Models of Production Lines,with Special Reference to Computer Operation and Scheduling

A situation is considered where a machine or a production line, for example an electronic computer or a data-processing system, has alternate "good" and "bad" periods of operation. Two types of model are described which can be used to tackle this kind of situation and these form an approach to the practical problem of scheduling work through such a system. The two aspects considered are the probability of a preassigned schedule of operation being completed within some critical time, and the optimum assignment of the length of the scheduled operations.     

A TSP (1,2) application arising in cable assembly shops

One of the main operations in producing cable systems in the automotive industry is that of cutting/stripping/crimping. The most time-consuming activity in this operation is changing the heads whenever a different connector is to be crimped at either one of the ends. This set-up time is practically doubled when the heads at both ends are to be changed. Thus, one is faced with the problem of minimizing the total machine set-up time; which turns out to be a TSP where the distances between the nodes are either one or two. A simple and effective heuristic algorithm is developed that yields solutions, which are only a few percent above the optimum in the worst case.     

New maximum entropy-based algorithm for structural design optimization

A new algorithm based on nonlinear transformation is proposed to improve the classical maximum entropy method and solve practical problems of reliability analysis. There are three steps in the new algorithm. Firstly, the performance function of reliability analysis is normalized, dividing by its value when each input is the mean value of the corresponding random variable. Then the nonlinear transformation of such normalized performance function is completed by using a monotonic nonlinear function with an adjustable parameter. Finally, the predictions of probability density function and/or the failure probability in reliability analysis are achieved by looking the result of transformation as a new form of performance function in the classical procedure of maximum entropy method in which the statistic moments are given through the univariate dimension reduction method. In the proposed method, the uncontrollable error of integration on the infinite interval is removed by transforming it into a bounded one. Three typical nonlinear transformation functions are studied and compared in the numerical examples. Comparing with results from Monte Carlo simulation, it is found that a proper choice of the adjustable parameter can lead to a better result of the prediction of failure probability. It is confirmed in the examples that result from the proposed method with the arctangent transformation function is better than the other transformation functions. The error of prediction of failure probability is controllable if the adjustable parameter is chosen in a given interval, but the suggested value of the adjustable parameter can only be given empirically.     

结构的失效可能度及模糊概率计算方法

依据模糊可能性理论,系统地建立含模糊变量时结构的可靠性计算模型。旨在解决模糊结构、模糊-随机结构和模糊状态假设下结构的可靠性计算问题。所建模型可给出模糊结构失效的可能度和模糊-随机结构失效概率的可能性分布。研究表明:对同时含模糊变量和随机变量的混合可靠性计算问题,把失效概率(或可靠度)作为模糊变量,能更客观地反映系统的安全状况。算例分析说明了文中方法的合理性和有效性。     

Range reliability in random walks

This paper introduces a definition of reliability based on a process range. Thus, process failure is defined when the range of a process first reaches a given and unacceptable level. The Mean Time To Failure (MTTF) which is denned as the mean of the first time for a range to attain a given amplitude is then calculated for an asymmetric random walk process. The probability distribution of the range is then given and the process reliability over long periods of system operations are then calculated. Applications such as the control of wings movements, stock price and exchange rates volatility (defined in terms of reliability) are also used to motivate the usefulness of range processes in reliability studies. Finally, we point out that there is necessarily a relationship between the range reliability and the propensity of a series to become chaotic.