Reliability Evaluation of Compressor Systems Based on Universal Generating Function Method

At present, universal generating function (UGF) is a reliability evaluation technique which holds the bare-looking and easily program-realized merits in multi-state system. Thus, it is meaningful to apply this method to an actual industry system. Compressor systems in natural gas pipelines are series-parallel multi-state systems, where the compressor units in each compressor station work in a parallel way and these pressure-boosting stations in the pipeline are series connected. Considering the characteristic of gas pipelines, this paper develops two different UGFs to evaluate the system reliability. One (Model 1) establishes a system model from every compressor unit while the other (Model 2) considers the whole system as a combination of multi-state components. Besides, all the parameters of “weight” in UGFs are obtained from thermal-hydraulic models based on the actual engineering and “probability” from Monte Carlo simulation. The results show that the system reliabilities calculated by different UGFs are approximately equal. In addition, the demand of gas and the gas pipeline transportation system show a reverse trend. Because the number of parameters needed in Model 2 is far less than that needed in Model 1, Model 2 is simpler programming and faster solved.     

Reliability analysis of multi-state repairable system with dynamic transition probabilities

Inadequate maintenance decisions lead to incremental overall costs. In order to minimize costs in maintenance of the multi-state repairable system, we model a preventive maintenance (PM) scheme of the multistate repairable system using non-Markov process. The periodically decreasing reliability model of the non-Markov dynamic system with dynamic transition probabilities is established to satisfy the probability change. The diesel engine system is taken as an example to illustrate the model. The reliability of the diesel engine is analyzed and its PM scheme is worked out. RENO software is used to simulate the diesel engine system. The maintenance cost of components and the optimal PM interval data of the system are obtained by using the minimal average cost as the objective function. The adaptability of PM is judged, and the optimal PM scheme is presented.     

Reliability Analysis of Retracting Actuator with Multi-State Based on Goal Oriented Methodology

In order to conduct effective reliability analysis of retracting actuator with multi-state(success state,safety failure state and action failure state), we redefine type-3 operator in goal oriented(GO) method to describe three states of main charge of retracting actuator and improve type-15 operator in GO method to describe the logic relations of multi-state output. The quantitative and qualitative reliability analyses of retracting actuator are made based on GO method in this paper. The system state probability of retracting actuator is obtained through quantitative analysis, and its weakness is found through qualitative analysis. The analysis results show that GO method is effective to improve the reliability of retracting actuator, and this method is also feasible for reliability analysis of other complicated initiating explosive systems.     

基于KDE及Markov的高速列车传动系振动评价及可靠性分析

为研究高速列车运行过程中传动系的振动情况及可靠性，对CRH3型高速列车传动系关键部件的振动加速度数据进行实车采集，采用核密度估计（KDE）法对采集数据统计处理，得出各关键部件在各方向上振动响应的概率密度函数近似曲线，据此对传动系的关键部件进行振动评价；通过MATLAB计算各关键部件振动加速度的最优置信区间；对传动系及传动系的关键部件定义“安全”和“故障”两种状态，建立关键部件的威布尔比例失效率模型及传动系的Markov状态转移模型，以传动系当前状态为初始状态，基于实时故障率及维修率分析传动系可靠性的变化. 研究结果表明:传动系中轴箱轴承、齿轮箱以及电机轴承的垂向振动最强，振动加速度集中分布在25倍、20倍、10倍重力加速度范围内，概率99.75%的均方差值分别在20.5026倍、17.6712倍、11.4693倍重力加速度内；计算得到各关键部件振动加速度概率为99.75%的最优置信区间，为系统的振动监测阈值优化及故障评估提供参考；故障率及维修率是影响传动系统状态概率的关键因素，当故障率增加30%时，系统的状态概率约下降10%，当维修率由0.05提升至0.10时，可使系统的可靠性提高20%.      

Lifetime Reliability Analysis of Flexural Cracking for Prestressed Concrete Bridge

Time-dependant reliability is analyzed for the flexural cracking of prestressed concrete bridges under service limit state. The limit state function and random variables are derived from Chinese highway bridge design specifications. For deterioration of structural performances, chloride-induced reinforcement corrosion is emphasized. Through integrating first order reliability method (FORM) and time discretized approach, the time-variant reliability is evaluated. For illustrative propose, the reliability of a typical simply supported prestressed concrete beam is exemplified.     

Binary decision diagram quantitative analysis method based on fuzzy set theory

A binary decision diagram(BDD) is a data structure that is used to represent a Boolean function.Converting fault tree into BDD can effectively simplify counting processes and improve the accuracy and effectiveness of the results. However, due to various types of uncertainties in reliability data, we cannot obtain precise failure probabilities. In order to accurately quantify the certainties and obtain much more reliable results, we use BDD method based on fuzzy set theory for reliability quantitative analysis. In this regard, we take W-axis feeding system of heavy-duty computer numerical control(CNC) machine as a project example and adopt fuzzy BDD quantitative analysis method to analyze its reliability. The analysis results(aided by computer calculation)illustrate the effectiveness of the method proposed in this paper.     

Numerical simulation to reliability analysis of fault-tolerant repairable system

In the traditional method for the reliability analysis of fault-tolerant system, the system structure is described by means of binary decision diagram (BDD) and Markov process, and then the reliability indexes are calculated. However, as the size of system augments, the size of state space will increase exponentially. Additionally, Markov approach requires that the failure and repair time of the components obey an exponential distribution. In this study, by combining dynamic fault tree (DFT) and numerical simulation based on the minimal sequence cut set (MSCS), a new method to evaluate reliability of fault-tolerant system with repairable components is proposed. The method presented does not depend on Markov model, so that it can effectively solve the problem of the state-space combination explosion. Moreover, it is suitable for systems whose failure and repair time obey an arbitrary distribution. Therefore, our method is more flexible than the traditional method. At last, an example is given to verify the method.     

Minimum resistance ship hull uncertainty optimization design based on simulation-based design method

In the ship hull optimization design based on simulation-based design (SBD) technology, low precision of the approximate model leads to an uncertainty form of optimization model. In order to enable the approximate model with finite precision to maximize the effectiveness, uncertainty optimization method is introduced here. Wave resistance coefficient approximation model, built by back propagation (BP) neural network, is represented as a form of interval. Afterwards, a minimum resistance optimization model is established with the design space constituted by principal dimensions and ship form coefficients. Double-level nested optimization architecture is proposed: for outer layer, improved particle swarm optimization (IPSO) algorithm with learning factor improvement strategy is used to generate design variables, and for inner layer, modified very fast simulated annealing (MVFSA) algorithm is used to solve the objective function interval with uncertainty region. Cases calculation proves the effectiveness and superiority of uncertainty optimization method for ship hull SBD optimization design, thus providing a good way for finding optimal designs.     

基于正态云模型和模糊层次分析法的列车通信网络性能评估方法

为保证高速列车安全、可靠运行,研究了列车通信网络性能评估方法;综合考虑列车通信网络的实时性、可靠性和服务质量,建立了合理的列车通信网络性能评价指标体系,采用模糊层次分析法确定列车通信网络性能评估指标的权重;考虑列车通信网络评估过程中具有不确定性,构建了基于正态云模型和模糊熵的二维评估模型;建立了基于交换式以太网的大容量和高可靠性列车通信网络仿真平台,获取各指标样本数据,运用二维评估模型计算各指标的隶属度,依据模糊理论最大隶属度法则确定列车通信网络性能等级。研究结果表明:在列车通信网络状态良好时,60%评估样本的网络性能等级为Ⅰ、Ⅱ级,在网络丢包率和误码率较大时,40%评估样本的评估等级为Ⅲ、Ⅳ级,表明二维评估模型能够有效地反映列车通信网络状态;与仅运用模糊综合评价法相比较,两者的评估结果基本一致,反映了二维评估模型的准确性;模糊综合评价法不能消除评估过程中不确定性因素的影响,从而导致评估结果缺乏精确度,因此,提出的方法更适合于列车通信网络性能评估。      

Reliability analysis of electrical system of computer numerical control machine tool based on bayesian networks

The core of computer numerical control (CNC) machine tool is the electrical system which controls and coordinates every part of CNC machine tool to complete processing tasks, so it is of great significance to strengthen the reliability of the electrical system. However, the electrical system is very complex due to many uncertain factors and dynamic stochastic characteristics when failure occurs. Therefore, the traditional fault tree analysis (FTA) method is not applicable. Bayesian network (BN) not only has a unique advantage to analyze nodes with multiply states in reliability analysis for complex systems, but also can solve the state explosion problem properly caused by Markov model when dealing with dynamic fault tree (DFT). In addition, the forward causal reasoning of BN can get the conditional probability distribution of the system under considering the uncertainty; the backward diagnosis reasoning of BN can recognize the weak links in system, so it is valuable for improving the system reliability.     

自锚式悬索-斜拉组合体系桥梁施工期结构安全评价

针对自锚式悬索-斜拉组合体系桥梁施工期存在的诸多影响结构安全的问题,以实桥工程为依托,采用层次分析法,进行施工期结构风险识别,根据风险识别结果,基于BP网络的失效概率法,根据主要风险模式和风险因素,建立主要风险模式下的结构极限状态方程,得到各个施工阶段的失效概率,确定结构的目标可靠度。     

基于失效概率法的桥梁地震风险评估

为了研究地震破坏下高速铁路连续梁桥发生破坏的可能性,根据地震风险性（risk）为地震危险性（hazard）与易损性（fragility）乘积的定义,基于失效概率法,对高速铁路连续梁桥地震风险评估方法进行了分析.通过条带法建立桥梁地震需求模型,基于可靠度函数获得桥梁地震易损性曲线,拟合得到桥梁易损性概率密度函数;根据桥址处地震危险性资料,推导桥址处地震加速度概率密度函数;通过地震加速度概率密度函数与桥梁结构易损性概率密度函数的数值积分,实现桥梁地震风险概率评估.以一座（32+48+32）m高速铁路连续梁桥为例系统演绎了失效概率法桥梁风险评估的实现过程.研究结果表明:当地震危险性资料缺乏或不足时可以通过地震烈度分布函数及其与地震峰值加速度之间的换算关系,推导和完善地震危险性分析资料;对于高速铁路（32+48+32）m连续梁桥100年设计期间内发生轻微损伤的概率为5.16%,发生中等损伤的概率为4.46%,桥梁受到轻微损伤和中等损伤风险概率接近,几乎不可能发生严重损伤和完全破坏.      

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停车换乘可靠性是决定停车换乘设施能否成功吸引用户的重要因素之一.为了度量基于地铁的停车换乘可靠性,考虑了道路网上旅行时间不确定性、停车设施内搜索泊位时间不确定性和地铁车站等车不确定性,定义了“换乘可靠度”和“方式可靠度”.利用随机网络均衡分析方法模拟小汽车出行者以个人旅行时间最小为原则的旅行选择行为,包括方式选择、路径选择和停车设施选择.通过蒙特卡洛模拟和相继平均法求解均衡模型,并设计算例验证了不确定性对停车换乘分担率的显著影响.算例还分析了地铁发车频率、停车设施容量和总需求强度等因素对停车换乘可靠性的影响.     

Research on Nonlinear Dynamic Simulation and Fatigue Reliability Life Prediction for Synthesis Transmission System of Self-Propelled Gun

Aiming to the puzzle that the inner load of nonlinear synthesis transmission system is difficult to obtain, a new kind of virtual prototype establishment and simulation method is put forward. The influence on nonlinear vibration with flexible rotor, bearing backlash is analyzed based on a virtual prototype. To validate the virtual prototype of nonlinear gear transmission system, the corresponding test platform is established. The consistency between simulation results and test results proves that the simulation results of the virtual prototype can be used to calculate the fatigue reliability life of key components. A new kind of fatigue reliability life prediction method of gear system considering multi-random parameter distribution is put forward based on the fatiguestatistic theory. Considering the periodicity of gear meshing, linear interpolation method is adopted to obtain the stress-time course of random load spectrum based on the gear’s complicated torque provided by virtual prototype. The gear’s P-S_a-S_m-N curved cluster can be simulated based on material’s P-S-N curve. The simulation process considers the parameter distributions of stress concentration coefficients, dimension coefficients and surface quality treatment coefficients, and settles the puzzle that traditional test methods cannot acquire the gear’s fatigue life of all reliability levels. This method can provide the distribution function and the interval of fatigue reliability life of gear’s danger region, and has a guide meaning for the gear maintenance periods determination and reliability evaluation.     

Imprecise reliability assessment for heavy numerical control machine tools against small sample size problem

Small sample size problem is one of the main problems that heavy numerical control (NC) machine tools encounter in their reliability assessment. In order to deal with the small sample size problem, many indirect reliability data such as reliability data of similar products, expert opinion, and engineers’ experience are used in reliability assessment. However, the existing mathematical theories cannot simultaneously process the above reliability data of multiple types, and thus imprecise probability theory is introduced. Imprecise probability theory can simultaneously process multiple reliability data by quantifying multiple uncertainties (stochastic uncertainty, fuzzy uncertainty, epistemic uncertainty, etc.) together. Although imprecise probability theory has so many advantages, the existing natural extension models are complex and the computation result is imprecise. Therefore, they need some improvement for the better application of reliability engineering. This paper proposes an improved imprecise reliability assessment method by introducing empirical probability distributions to natural extension model, and the improved natural extension model is applied to the reliability assessment of heavy NC machine tool spindle to illustrate its effectiveness.     

基于多尺度排列熵和长短时记忆神经网络的航空发动机剩余寿命预测

针对航空发动机性能退化失效的变点和多状态参数的时间序列预测, 构建了基于多尺度排列熵算法和长短时记忆神经网络的剩余寿命预测模型; 使用多尺度排列熵算法对时间序列进行变点分析, 求解出性能退化过程中的突变点, 得到了有故障征兆的性能退化起始点; 构建了包含多变量的长短时记忆神经网络模型, 将多个状态参数代入到模型中得到对应的剩余寿命; 将变点后的航空发动机多状态参数和剩余寿命作为样本, 代入到长短时记忆神经网络模型中进行多步和多变量的时间序列预测; 通过综合航空发动机状态参数变点分析方法和时间序列预测模型, 得到最终的剩余寿命预测结果。研究结果表明: 多尺度排列熵算法能够及时监控各个状态参数的变化, 当发现状态参数异常时, 排列熵的值会发生跳变, 从而有助于及时发现故障征兆; 长短时记忆神经网络模型通过门控单元对长时间序列数据进行信息筛选, 充分保留了有效信息用于时间序列预测; 多变量长短时记忆神经网络能够对多状态参数进行同步分析, 并且将状态参数直接与剩余寿命相对应, 提高了模型效率; 通过多尺度排列熵算法和长短时记忆神经网络模型的结合, 能够考虑到航空发动机的多退化模式, 得到更符合实际退化过程的剩余寿命预测结果; 经过算例分析, 提出方法的剩余寿命预测的均方根误差为5.3, 与长短时记忆神经网络、反向传播神经网络和支持向量机相比, 误差分别降低了63%、72%和78%。      

Method of a new iteration scheme combined with Kriging model for structural reliability evaluation

The first order reliability method (FORM) is widely adopted for structural reliability evaluation due to its numerical efficiency. Concerning the issue of FORM often failing to converge when the limit state function (LSF) behaves high nonlinearity, a new iteration scheme called ??rotated gradient algorithm (RGA)?? is proposed and combined with Kriging model to evaluate the reliability of implicit performance function. In this paper, the Kriging model is applied to approximate the real LSF first. Then the scheme of RGA, constructed in terms of gradient information of two adjacent design points obtained during the process of calculation, is used to calculate the reliability index. Numerical examples show the validity in convergence and accuracy of the proposed method for arbitrary nonlinear performance function.     

考虑非线性累积损伤的大跨多荷载桥梁的疲劳可靠度评估

针对大跨多荷载桥梁疲劳损伤累积非线性过程中的大量不确定性,对火车、汽车与风荷载作用下的大跨悬索桥,利用连续损伤模型提出了一个疲劳可靠度评估方法.首先,在连续损伤模型基础上,对模型参数进行分析;然后,根据工程应用的需要,适当简化疲劳模型,在连续损伤模型中引入合适的随机变量,定义疲劳可靠度分析的极限状态函数,假定多种未来可能的交通荷载和荷载增长模式,利用蒙特卡洛方法产生随机变量并计算失效概率;最后以香港青马大桥为例,讨论了该桥在不同荷载状况下使用120年后的疲劳失效概率.研究发现:若保持当前的交通状态,桥梁可保持良好状况,但未来交通荷载的快速增长会导致结构提前失效.      

考虑油石比波动的沥青混合料可靠度设计

引入可靠度理论至沥青混合料配合比设计,减少施工油石比(Pb)变异对混合料性能的不利影响。将混合料失效定义为体积指标超出限值,由此提出可靠区间概念。用Pb概率分布函数在可靠区间内积分得到可靠度。以可靠度为评价指标对SMA-13进行级配优化,使SMA-13可靠度提高42.9%的同时不降低其路用性能。绘制可靠区间、Pb标准差与可靠度的诺模图,结合调研推荐:高速公路混合料可靠区间应≥0.6%,其它道路≥0.5%;高速公路混合料可靠度应≥95%,其它道路≥80%。     

基于统计与假设检验的高速公路交通事故数据分布特性

为了研究高速公路基本路段上交通事故数据的分布特征, 将事故数、伤亡事故数、事故死亡人数与事故受伤人数归类为离散型事故数据, 将事故间隔时间与平均每年每公里事故数归类为连续型事故数据; 对于离散型事故数据, 采用均匀划分法、动态聚类法与滑动窗法划分高速公路统计区段, 运用泊松分布、负二项分布、零堆积泊松分布与零堆积负二项分布对事故数据进行拟合; 对于连续型事故数据, 以收费区间为路段划分标准, 用正态分布、负指数分布进行事故数据拟合; 运用皮尔逊卡方值对各种拟合结果进行拟合优度检验。研究结果表明: 在各种区段上, 事故数均服从负二项分布, 有些情况下会同时服从负二项分布与泊松分布, 伤亡事故数与事故死亡人数主要服从零堆积泊松分布或零堆积负二项分布, 拟合优度检验中的概率均大于0.05;平均每年每公里的事故数比较符合正态分布, 而事故间隔时间则主要服从负指数分布, 拟合优度检验中的概率也均大于0.05;交通事故数据的统计分布特征是建立事故预测模型与事故多发点鉴别的前提条件之一, 而事故间隔时间可作为安全可靠度的度量指标。