Reliability-based Robust Optimization Design of Automobile Components with Non-normal Distribution Parameters

In the reliability designing procedure of the vehicle components, when the distribution styles of the random variables are unknown or non-normal distribution, the result evaluated contains great error or even is wrong if the reliability value R is larger than 1 by using the existent method, in which case the formula is necessary to be revised. This is obviously inconvenient for programming. Combining reliability-based optimization theory, robust designing method and reliability based sensitivity analysis, a new method for reliability robust designing is proposed. Therefore the influence level of the designing parameters’ changing to the reliability of vehicle components can be obtained. The reliability sensitivity with respect to design parameters is viewed as a sub-objective function in the multi-objective optimization problem satisfying reliability constraints. Given the first four moments of basic random variables, a fourth-moment technique and the proposed optimization procedure can obtain reliability-based robust design of automobile components with non-normal distribution parameters accurately and quickly. By using the proposed method, the distribution style of the random parameters is relaxed. Therefore it is much closer to the actual reliability problems. The numerical examples indicate the following: (1) The reliability value obtained by the robust method proposed increases (】0.04%) comparing to the value obtained by the ordinary optimization algorithm; (2) The absolute value of reliability-based sensitivity decreases (】0.01%), and the robustness of the products’ quality is improved accordingly. Utilizing the reliability-based optimization and robust design method in the reliability designing procedure reduces the manufacture cost and provides the theoretical basis for the reliability and robust design of the vehicle components.

Parameter Estimation of Mixed Weibull Distributions Using Cuckoo Search

The lifetime data of products with multiple failure modes which are collected from life testing are often fitted by the mixed Weibull distributions. Since the mixed Weibull distributions contain no less than five parameters,the parameter estimation is difficult and inaccurate. In order to enhance the accuracy,a new method of parameter estimation based on Cuckoo search( CS) is proposed. An optimization model for the mixed Weibull distribution is formulated by minimizing the residual sum of squares. The optimal parameters are searched via CS algorithm. In the case study,the lifetime data come from the life testing of diesel injectors and are fitted by the twocomponent Weibull mixture. Regarding the maximum absolute error and the accumulative absolute error between estimated and observed values as the accuracy index of parameter estimation,the results of four parameter estimation methods that the graphic estimation method,the nonlinear least square method,the optimization method based on particle swarm optimization( PSO) and the proposed method are compared. The result shows that the proposed method is more efficient and more accurate than the other three methods.

Interval Estimation in a Two Parameter Weibull Distribution Based on Type-2 Censored Data

In this paper, we consider the construction of the approximate profile- likelihood confidence intervals for parameters of the 2-parameter Weibull distribution based on small type-2 censored samples. In previous research works, the traditional Wald method has been used to construct approximate confidence intervals for the 2-parameter Weibull distribution under type-2 censoring scheme. However, the Wald technique is based on normality assumption and thus may not produce accurate interval estimates for small samples. The profile-likelihood and Wald confidence intervals are constructed for the shape and scale parameters of the 2-parameter Weibull distribution based on simulated and real type-2 censored data, and are hence compared using confidence length and coverage probability.

Progress in Theoretical Research on Reliability for China's Space Engineering

With the support of the Fundamental Reliability Theoretical Research (FRTR) Foundation of the Quality Control Bureau of Ministry of Astronautics (MOA), PRC, 9 Chinese institutes and universities have worked for years on reliability statistics problems pending to be solved in space research and development. This paper gives a brief review of our main research results, including (1) Results on Normal Distributions; (2) Results on Weibull Distributions; (3) Results on the Synthesisof System Reliability-Theoretical Method; (4) Results on the Synthesis of System Reliability-Approximation Method: Binomial Distribution, Exponential Distribution, Weibull Distribution, Parallel System, General Cases; (5) Structual Reliability; (6) Zero-Failure Reliability Estimation; (7) Storage Life and Others. All these results can be acquired from the Quality Control Bureau of the Ministry of Aero-Space Industry (MAS).

Research on Preventive Maintenance Strategy of Simulator Based on Reliability Theory

Based on the theory of reliability, this paper studies the preventive maintenance strategy of the simulator with incomplete maintenance, and establishes the preventive maintenance model with the aim of simulating the maintenance cost and simulating machine availability. The main contents of this paper are as follows： Firstly, this paper introduces the background and significance of this paper, expatiates the relevant concepts and mathematical foundation of simulator maintenance related theory and reliability maintenance thought, simulator performance degradation law, Weibull parameter estimation method, As the center of the maintenance （RCM） theory of system maintenance decision analysis.

Modelling Complete Power Outage Data Using Reliability

Data on time between complete power outages, Time between Failure (TBF) in Uyo were considered. Trend test and serial correlation test were conducted graphically for the data. The tests proved that the data were identically and independently distributed (iid). Summary statistics of the data showed that complete power outage occurred 416 times between the year 2014 and 2018. The maximum likelihood estimation method was used to estimate the parameters of Weibull 2-parameter, Normal, Lognormal 2-parameter and exponential distributions. The values of Kolmogorov-Smirnov, Anderson Darling and Chi-Square statistics were used to determine the best fit distributions. A model for the computation of reliability of electric power was then proposed.

Detail fatigue rating method based on bimodal Weibull distribution for DED Ti-6.5Al-2Zr-1Mo-1V titanium alloy

Previous studies have shown that the fatigue life distribution of metal materials fabricated with Additive Manufacturing(AM) methods, such as Direct Energy Deposited(DED) Ti-6.5Al-2Zr-1Mo-1V alloys, exhibits two peaks. To promote the application of AM in aerospace and other engineering fields, developing a fatigue strength evaluation method suitable for AM materials based on their unique fatigue behaviours and fatigue life distributions is necessary. In this paper, a novel Detail Fatigue Rating(DFR) method was developed to evaluate the fatigue strength of DED Ti-6.5Al-2Zr-1Mo-1V based on a bimodal Weibull distribution and the excessive restriction on the allowable stress of potential was improved. Meanwhile, a Bimodal Weibull distribution model for fatigue life and its parameter estimation method were established based on a twoparameter Weibull distribution. The fatigue life at a specific reliability level and confidence level was calculated by using the bootstrap method. The calculation results showed that fatigue life estimated by using the bimodal Weibull distribution at the high reliability level and high confidence level is higher than that estimated by using the two-parameter Weibull distribution. Furthermore,The S-N curve at the specified confidence level and reliability level was fitted.

Study on segmented distribution for reliability evaluation

In practice, the failure rate of most equipment exhibits different tendencies at different stages and even its failure rate curve behaves a multimodal trace during its life cycle. As a result,traditionally evaluating the reliability of equipment with a single model may lead to severer errors.However, if lifetime is divided into several different intervals according to the characteristics of its failure rate, piecewise fitting can more accurately approximate the failure rate of equipment. Therefore, in this paper, failure rate is regarded as a piecewise function, and two kinds of segmented distribution are put forward to evaluate reliability. In order to estimate parameters in the segmented reliability function, Bayesian estimation and maximum likelihood estimation（MLE） of the segmented distribution are discussed in this paper. Since traditional information criterion is not suitable for the segmented distribution, an improved information criterion is proposed to test and evaluate the segmented reliability model in this paper. After a great deal of testing and verification,the segmented reliability model and its estimation methods presented in this paper are proven more efficient and accurate than the traditional non-segmented single model, especially when the change of the failure rate is time-phased or multimodal. The significant performance of the segmented reliability model in evaluating reliability of proximity sensors of leading-edge flap in civil aircraft indicates that the segmented distribution and its estimation method in this paper could be useful and accurate.

The Exponential Flexible Weibull Extension Distribution

This paper is devoted to study a new generalization of the flexible Weibull with three parameters. This model is referred to as the exponential flexible Weibull extension (EFWE) distribution which exhibits bathtub-shaped hazard rate function. Some statistical properties such as the mode, median, the moment, quantile function, the moment generating function and order statistics are discussed. Moreover, the maximum likelihood method for estimating the model parameters and the Fisher’s information matrix is given. Finally, the advantage of the EFWE distribution is concluded by an application using real data.

Empirical Bayes Test for Two-parameter Exponential Distribution under Type-Ⅱ Censored Samples

The empirical Bayes test problem is considered for scale parameter of twoparameter exponential distribution under type-II censored data.By using wavelets estimation method,the EB test function is constructed,of which the asymptotic optimality and convergence rates are obtained.Finally,an example concerning the main result is given.

排序集抽样下Weibull分布的产品可靠度估计

排序集抽样方法用于样本单元排序容易但测量困难的情形。产品可靠度是描述产品可靠性的重要度量指标,Weibull分布在可靠性试验中占有非常重要的地位。为了提高Weibull分布产品可靠度的估计效率,本文采用排序集抽样方法,研究了产品可靠度的极大似然估计,计算了Weibull分布形状参数和尺度参数的Fisher信息阵,证明了极大似然估计量的渐近正态性,并给出了新估计量的渐近方差。渐近相对效率和模拟相对效率的计算结果表明:排序集抽样下极大似然估计量的估计效率一致高于简单随机抽样下极大似然估计量。最后,单碳纤维强度数据的实际分析结果验证了排序集抽样方法的高效率性。

试验数据服从Weibull分布时可靠性试验最少试件数的确定

试验试件数的确定是产品疲劳寿命试验过程中的一个重要问题,为节省时间和费用,要求在满足一定精度前提下使得试件数最少。研究在试验数据服从双参数Weibull分布的情况下,如何确定可靠性试验中最少试件数(最小子样容量)的问题。提出以估计量的相对偏差作为精度指标,并推导出确定最少试件数的公式。通过实例计算,给出在一定精度指标和置信水平下,估计特征寿命和安全寿命时所需的最少试件数。

随机变量多重Weibull统计模型及参数最优估计

利用Weibull分布函数兼容性好的特点,采用混合Weibull分布模型来描述复杂随机变量分布,并按照最小二乘法原则,对统计模型参数进行最优化估计,建立复杂随机变量分布的统计模型。对某汽车发动机工作转矩统计模型的建立示例表明,多重Weibull分布适合用来表达一些复杂随机变量的统计特性,参数估计的最优化模型适用,参数优化估计过程能可靠收敛。

随机删失数据下基于EM算法的Weibull分布参数估计

生存分析中的观测数据具有样本小、数据随机删失的特点.而目前处理这类问题所使用的参数估计方法并不理想.作者基于EM算法给出随机删失数据下Weibull分布的参数估计方法,证明了估计量满足一个非线性方程组,并用实例表明了此方法的有效性.

三参数Weibull分布参数的极大似然估计数值解法

利用降阶思想,给出了一种新的求解三参数Weibull分布参数的极大似然估计数值方法。该方法首先假定形状参数已知,将三元方程组转化为二元方程组,并用二分法求解该二元方程组的数值解,然后将尺度参数和位置参数表示成形状参数的函数,此时极大似然函数仅是关于形状参数的单变量函数,再次应用二分法即可得出形状参数的最优估计结果。该算法稳定,不需要赋予初始值,对样本数量没有限制。与其他方法相比,具有计算精度高、运算速度快的优点,便于工程应用。

基于Weibull函数分布的电力通信网光缆失效率模型

为了解决电力通信网可靠性评估过程中光缆可靠性的量化和计算问题,在现有的三参数Weibull分布函数的基础上,结合光缆现行的国家与电力行业标准和主流生产厂家的光缆特性指标,提出了光缆失效的3个影响参数——形变参数、结构参数以及时间参数,并建立了适用于分析电力通信光缆失效率的概率分布模型。针对现有数据的局限性,采用将传统的黄金分割迭代算法与一种能够近似拟合的最大似然估计法相结合的方法对参数的取值进行计算和估计。该模型较好地反映了不同的因素对光缆可靠性的影响程度,实例分析验证了该模型具有一定的实用性。

Weibull分布产品小样本定时截尾试验方案下的可靠性评估

针对Weibull分布产品小样本定时截尾试验方案下的可靠性评估问题,假设样本结构在截尾时间为使该样本结构出现概率最大的截尾时间区间内的任意一点时产生,应用Monte Carlo模拟方法,发现形状参数矩估计量中值与其真值之比值仅取决于样本结构,而不受分布母体影响,据此提出了中值无偏矩估计法,并给出了2～12样本量的中值无偏系数取值。以偏差和均方根误差为评价指标,通过数值模拟方法,对该方法和矩估计法进行比较后发现,在两项指标上,前者较后者均具有明显优势。通过试验验证了所提出方法的实用性、有效性和优越性。

三参数 Weibull 分布的秩拟合最优化法

对于给定的一组疲劳寿命试验数据，首先求得该样本顺序统计量的平均秩（或中位秩），然后由三参数Ｗｅｉｂｕｌ分布对此平均秩进行拟合．通过对线性拟合相关系数的最优化求解来确定Ｗｅｉｂｕｌ分布的位置参数，再由最小二乘拟合便可估计出Ｗｅｉｂｕｌ分布的形状参数和尺度参数．该方法具有迭代收敛快且拟合精度高的特点．

三参数Weibull分布竞争失效场合变应力加速寿命试验统计分析

三参数Weibull分布(Three-parameter Weibull distribution,TPWD)作为一种应用广泛的分布形式,具有很强的数据拟合能力且对于描述具有渐变性失效特征的失效模式如磨损、疲劳、腐蚀、老化等的的寿命分布具有更加明确的物理意义。针对产品失效模式为TPWD的竞争失效场合加速寿命试验统计分析的需求,根据TPWD的特点,在竞争失效加速寿命试验统计分析基本模型的基础上系统研究TPWD竞争失效变应力加速寿命试验统计分析方法,建立参数估计的极大似然模型并进行实例验证。实例结果表明,建立的TPWD竞争失效变应力加速寿命试验统计分析方法和模型是正确可行的,具有很好的估计效果。