Approach for Reliability Evaluation of Cross-Linked Polyethylene Under Combined Thermal and Vibration Stresses

Based on Wiener process model, a new approach for reliability evaluation of cross-linked polyethylene(XLPE) is proposed to improve the lifetime evaluation reliability of XLPE under multi-stressing conditions and study the failure probability distribution. In this paper, two accelerated aging tests are carried out under combined thermal and vibration conditions. The volume resistance degradation data of XLPE samples are tested with a24 h interval under the accelerated stressing conditions at(130℃, 12 m/s~2) and(150℃, 8.5 m/s~2), respectively.Nonlinear degradation data obtained from the experiment are transformed to linear intermediate-variable values using time scaling function, and then linearized degradation data are calculated and evaluated on the basis of linear Wiener process model. Considering traditional Arrhenius equation and inverse power criterion, parameters of the linear Wiener model are estimated according to the maximum likelihood function. The relationship curves on probability density and reliability are given, and the lifetime distribution of XLPE under different stressing conditions is also obtained for evaluating the reliability of XLPE insulation. Finally, the life expectancy of XLPE is 17.9 a under an allowance temperature of 90℃ and an actual vibration acceleration of 0.5 m/s~2. The approach and results in this paper may be used for reliability assessment of high-voltage multiple samples or apparatuses.     

Bayesian reliability assessment and degradation modeling with calibrations and random failure threshold

A degradation model with a random failure threshold is presented for the assessment of reliability by the Bayesian approach. This model is different from others in that the degradation process is proceeding under pre-specified periodical calibrations. And here a random threshold distribution instead of a constant threshold which is difficult to determine in practice is used. The system reliability is defined as the probability that the degradation signals do not exceed the random threshold. Based on the posterior distribution estimates of degradation performance, two models for Bayesian reliability assessments are presented in terms of the degradation performance and the distribution of random failure threshold. The methods proposed in this paper are very useful and practical for multi-stage system with uncertain failure threshold. This study perfects the degradation modeling approaches and plays an important role in the remaining useful life estimation and maintenance decision making.     

Degradation Reliability Analysis Based on TOPSIS Model Selection Method

It is necessary to determine the degradation path model of products at first when using the method based on degradation path model to evaluate the degradation reliability of products.At present,the degradation path model is mainly determined by scatter plots of degradation data.However,this method has strong subjectivity and is liable to cause the evaluation results to be inconsistent with the actual situation.In this paper,a degradation reliability analysis method based on TOPSIS(technique for order preference by similarity to an ideal solution)model selection is proposed,and its implementation process is given.The optimal degradation path model is selected according to the calculated proximity.With the help of TOPSIS method,various degradation path models can be selected and quantified,and the original degradation path method can be improved to avoid the risk of errors in product reliability evaluation caused by inaccurate subjective hypothesis,so as to ensure the objectivity and accuracy in the process of model determination.The validity and practicability of the proposed method are verified by the degradation analysis of the injector of a certain type of diesel engine.     

Optimal Burn-in and Preventive Maintenance Modeling with Competing Failure Processes

In this article, we assume that the product in the burn-in procedure only experiences continuous smooth degradation process, while in the field operation period the product experiences both continuous smooth degradation process and shock process. The shock process can cause the product not only traumatic failure,but also additional abrupt degradation damage. After the system reliability model and maintenance model have been proposed, the optimal burn-in setting and age replacement duration are obtained under the considering of minimizing the long run average cost rate. A numerical example with the real data is analyzed to illustrate the application of the model.     

基于Wiener退化对镁水泥混凝土中钢筋的锈蚀预测

镁水泥混凝土对钢筋的腐蚀限制了其广泛的推广应用,为解决这一难题,提出利用涂层来缓解其对钢筋的腐蚀,确保镁水泥钢筋混凝土建筑满足设计规定的使用年限要求. 根据西部盐渍土地区的自然环境,采用溶液浸泡加速锈蚀的试验方法对氯氧镁涂层钢筋混凝土进行快速腐蚀试验;运用电化学工作站周期性地对氯氧镁涂层钢筋混凝土试块进行电化学试验;以表征涂层钢筋锈蚀的电化学参数（腐蚀电流密度）作为退化指标,在Wiener退化过程的基础上进行可靠度建模并且对涂层钢筋进行锈蚀预测. 研究结果表明:利用涂层钢筋腐蚀电流密度作为耐久性退化指标可以得到镁水泥涂层钢筋混凝土中的涂层钢筋锈蚀的可靠度函数,并确定出涂层钢筋在30 000 d左右达到中等腐蚀.      

基于有限理性的交通网络可靠性均衡模型

为探索交通系统不确定性和出行者心理感知差异对出行路径选择行为的影响,将路网可靠性和有限理性融入出行者的路径选择决策中,提出双目标交通网络均衡模型.为应对模型多解问题,建立出行可靠性和有限理性下的贝叶斯随机用户均衡模型,运用贝叶斯统计和双层规划框架估计权重系数,采用变分不等式刻画交通均衡模型;分别设计迭代算法（iterative algorithm,IA）和相继平均算法（method of successive average,MSA）求解贝叶斯权重系数估计和变分不等式交通网络均衡模型.算例表明：随着观测变量和输入变量扰动变小,估计参数的均方根误差逐步减小;IA在运行15 s后均方根误差达到0.05,MSA在1 s内收敛精度达到10-6;变分不等式均衡模型可以同时反映出行者的风险态度和有限理性决策过程.     

Imprecise Probability Method with the Power-Normal Model for Accelerated Life Testing

We present a new nonparametric predictive inference(NPI) method using a power-normal model for accelerated life testing(ALT). Combined with the accelerating link function and imprecise probability theory,the proposed method is a feasible way to predict the life of the product using ALT failure data. To validate the method, we run a series of simulations and conduct accelerated life tests with real products. The NPI lower and upper survival functions show the robustness of our method for life prediction. This is a continuous research, and some progresses have been made by updating the link function between different stress levels. We also explain how to renew and apply our model. Moreover, discussions have been made about the performance.     

边坡稳定性模糊随机可靠度分析

考虑可靠性分析中结构极限状态变量在零值附近的模糊区间,建立边坡稳定性模糊随机可靠度分析模型。研究了在土性参数变异性、模糊失效概率隶属度函数梯形与岭形分布类型情况下,模糊区间宽率与偏度对模糊可靠指标的影响。分析结果显示:偏度与可靠性指标曲线的斜率随宽率的减小而减小,且其趋势与参数变异性与模糊失效概率隶属度函数类型无关;对于宽率的某一确定值而言,偏度的增大会导致模糊可靠指标的降低;土性参数变异性的增加会导致模糊可靠指标的降低。     

基于ALTA的加速寿命试验数据分析

简单介绍了加速寿命试验,并将计算机辅助工程应用于加速寿命试验数据分析.通过定量加速寿命测试数据分析)软件ALTA对某新产品的三组恒定应力加速寿命试验所获得的数据做了计算机辅助仿真分析.结果表明,通过这个方法可以快速、准确得到可靠性设计中常用的参数,可以大大缩短可靠性设计时间,提高效率,具有较强的实用性.     

服役公路桥梁的时变可靠指标计算

为了对服役结构的可靠性进行正确评估,必须考虑时间变化的影响,将结构服役时间离散为若干个时间点,利用各个时间点上随机的结构抗力和荷载效应,给出服役结构时变可靠指标简化计算公式,分析抗力衰减模式、可变荷载增加大趋势以及服役时间对可靠指标的影响。分析结果表明:在结构抗力和荷载效应保持不变情况下,随着服役时间的增长,结构的可靠指标降低,结构可靠指标的变化规律因抗力衰减模式和荷载增大趋势的不同而有差异。     

Modeling the effect of environmental conditions on reliability of wind turbines

The climate condition of a wind farm has a significant influence on the reliability of wind turbines. The climate condition varies with season in a year and hence the reliability changes in a complex way. The purpose of this paper is to model the effect of climate condition on field reliability of wind turbines. The reliability is measured by monthly-averaged mean time between failures(MTBF), and the climate conditions are described by variables of monthly-averaged temperature, relative humidity, rainfall and wind speed. Referring to the physicsof-failure models in accelerated life testing(ALT), we develop a quantitative relation between the MTBF and the climate variables. For a set of field data, the model parameters are estimated by regression, and the insignificant variables are gradually deleted based on the P-value of the regression coefficients. The resulting model is useful for maintenance workload forecasting and preventive maintenance planning, and has a potential to be used in online failure prediction.     

模拟酸雨侵蚀环境下钢筋混凝土结构长期性能研究综述

为深化对酸雨侵蚀环境下钢筋混凝土结构长期性能演变机制的认识,论述了酸雨侵蚀作用下混凝土材料腐蚀机理、侵蚀模型和物理力学性能时变过程;分析了酸雨锈蚀钢筋的溶液腐蚀机理和大气动态冲刷机制,总结了锈蚀钢筋形貌表征与锈蚀率指标定量化研究成果,归纳了已有锈蚀钢筋力学性能退化模型和本构模型,概述了钢混界面黏结性能演变规律和黏结-滑移本构关系模型;梳理了梁、柱构件及结构静、动力学性能演变规律的室内试验结果、理论计算方法和数值仿真结果的最新研究进展与不足,并展望了未来的研究方向与重点。研究结果表明:酸雨腐蚀混凝土可归因于酸雨离子成分的交互作用,亟需适用性较强的理论模型以揭示腐蚀和扩散机制;室内加速试验揭示了酸雨侵蚀作用下混凝土物理力学性能时变规律,应完善室内加速试验制度,搭建耦合宏细观层次关键指标的混凝土损伤评价体系和预估模型;酸雨加速锈蚀钢筋试验多基于均匀锈蚀,钢筋腐蚀方法和形貌表征逐渐向不均匀锈蚀发展,应进一步发展高精度扫描技术,借助统计分析理论建立钢筋不均匀锈蚀特征参数,优化钢筋力学性能退化模型;通电锈蚀试验和拉拔试验演绎了钢混界面黏结性能演化规律,并建立了黏结-滑移本构关系,但忽略了实际钢筋混凝土结构的受力特点,且锈蚀过程显著区别于自然锈蚀,应考虑酸雨环境与材料特性复杂多变的特点,研究细微观钢混界面损伤行为,揭示酸雨环境、材料特性与黏结性能的内在关系;酸雨侵蚀钢筋混凝土结构时效性能研究多集中在试件层次,且采用腐蚀试验与承载力试验分阶段进行,忽略了荷载-环境的耦合作用,试验所设环境较为单一,试验制度与方法亦未统一,应对标实际工程,考虑实际结构承载和环境工况,搭建长期荷载-酸雨侵蚀耦合作用试验系统,探索荷载-环境-材料多场关联机制,完善理论计算方法与数值仿真手段,揭示结构长期性能演变过程,并推动现场暴露试验发展,量化室内-现场映射关系,指导工程实际。      

道路网短期交通流预测方法比较

介绍了用于短期交通流预测的两大类模型:统计预测算法和人工神经网络模型.对其中各种模型的特征进行了比较,将历史平均模型、求和自回归滑动平均模型(ARIMA)、非参数回归模型、径向基函数(RBF)神经网络模型与贝叶斯组合神经网络模型,应用于一个真实路网的短期流量预测,比较了各模型的预测结果.结果表明,组合神经网络模型预测误差最小,可靠性最高,是一种对短期交通流预测的有效方法.     

Reliability Prediction Method Based on State Space Model for Rolling Element Bearing

Reliability analysis based on equipment’s performance degradation characteristics is one of the significant research areas in reliability research. Nowadays, many researches are carried on multi-sample analysis. But it is limited for a single equipment reliability prediction. Therefore, the method of reliability prediction based on state space model(SSM) is proposed in this research. Feature energy of the monitored signals is extracted with the wavelet packet analysis and the associated frequency band energy with online monitored data. Then,degradation feature is improved by moving average filtering processing taken as input pair model parameter of SSM to be estimated. In the end, state space predicting model of degradation index is established. The probability density distribution of the degradation index is predicted, and the degree of reliability is calculated. A real testing example of bearing is used to demonstrate the rationality and effectiveness of this method. It is a useful method for single sample reliability prediction.     

Reliability Analysis for the Competing Failure with Probabilistic Failure Threshold Value and Its Application to the k-out-of-n Systems

A method for reliability analysis of the competing failure with the probabilistic failure threshold value not the fixed threshold value is presented, which involves the random shocks and the degradation is independent and dependent respectively. Specifically, for the dependent condition, the effect due to the random shocks on the degradation is considered with a damage factor. In addition, the dependent competing failure model is applied to the reliability analysis of the k-out-of-n systems. Finally, two studied cases are presented to illustrate the proposed method, and the results show the proposed method is reasonable.     

Hybrid Reliability Parameter Selection Method Based on Text Mining,Frequent Pattern Growth Algorithm and Fuzzy Bayesian Network

Reliability parameter selection is very important in the period of equipment project design and demonstration. In this paper, the problem in selecting the reliability parameters and their number is proposed. In order to solve this problem, the thought of text mining is used to extract the feature and curtail feature sets from text data firstly, and frequent pattern tree (FPT) of the text data is constructed to reason frequent item-set between the key factors by frequent patter growth (FPG) algorithm. Then on the basis of fuzzy Bayesian network (FBN) and sample distribution, this paper fuzzifies the key attributes, which forms associated relationship in frequent item-sets and their main parameters, eliminates the subjective influence factors and obtains condition mutual information and maximum weight directed tree among all the attribute variables. Furthermore, the hybrid model is established by reason fuzzy prior probability and contingent probability and concluding parameter learning method. Finally, the example indicates the model is believable and effective.     

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.     

Cox比例风险模型在原发性肝癌患者凝血功能分析中的应用

目的应用Cox比例风险模型探讨原发性肝癌的临床分期和患者生存期与凝血功能的相关性,为临床治疗和预后提供可靠的评价指标。方法对228例原发性肝癌患者、52例普通肝病患者和52例健康对照者进行了血浆凝血功能检测,并观察肝癌分期与凝血功能的关系;进行随访并收集相关的预后资料。采用Cox比例风险模型分析凝血指标和原发性肝癌晚期患者生存期及血栓性疾病的关系。结果原发性肝癌患者凝血指标变化不仅与健康对照组的差异显著,而且随着肝癌分期程度的加重,凝血功能障碍加剧(P<0.05);D-聚体(D-dimer)、纤维蛋白原降解产物(FDP)、纤维蛋白原(FIB)和血小板(PLT)水平与晚期肝癌患者的远期生存呈负相关。结论凝血功能指标的检测能从多方面及时、准确地反映肝癌患者肝脏的损害程度及危险程度,动态地观察凝血功能指标有利于对肝癌患者的病情进行更好的监测和治疗。     

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.     

Comparison analysis of efficiency between double-synchronous step-down-stress and step-up-stress accelerated life tests

Double-crossed-step-stress (DCSS) accelerated life test (ALT) method is widely used for estimating the lifetime of products with high reliability and long lifetime. In order to further reduce the test time and test cost, a double-synchronous-step-stress (DSSS) ALT method which combines a double-synchronous-step-down-stress (DSSDS) ALT method and a double-synchronous-step-up-stress (DSSUS) ALT method is proposed. The accelerated stresses decrease and increase in a synchronous way with one step in the DSSDS-ALT and DSSUS-ALT methods, respectively. Monte Carlo method is adopted to simulate the two methods, and the validity and efficiency of them are demonstrated by the simulation results. In addition, a comparison analysis of efficiency between DSSDS-ALT method and DSSUS-ALT method is carried out. The result shows that the DSSDS-ALT method compared with the DSSUS-ALT method can significantly improve the test efficiency under the same test condition.