基于虚拟试验的冲击磨损可靠性强化试验研究

为缩短可靠性试验周期、降低试验成本,结合虚拟试验技术对系统进行可靠性强化试验研究。以机械系统磨损失效为研究对象,通过磨损试验理论分析确定了磨损强化试验机理,提出了虚拟强化试验技术确定原则,推导了接触磨损强化系数,并利用MATLAB软件编制了相应的计算程序。基于炮闩系统虚拟样机,对平面接触的冲击磨损零部件进行了具体的强化试验,制定了强化试验技术方案,试验结果表明所采用的强化试验技术可行,研究成果有助于促进虚拟试验在可靠性强化试验领域的应用。     

Miner线性累计损伤理论在汽车试验场可靠性试验强化系数研究中的应用

 可靠性试验强化系数是汽车试验场制定规范的基础,运用科学的计算理论和方法可以得到准确的强化系数．根据Miner线性累积损伤理论,按照零件产生疲劳的因素对其进行修正,推导了计算汽车可靠性试验强化系数的数学模型,并在模型中引入损伤因子统计量和频率因子统计量的概念,使影响强化系数的多因素的物理意义更为准确．结合长安大学汽车试验场可靠性强化道路的实际,对某载货车在试验场上的载荷谱测试数据进行处理,计算得到试验场多种路面的综合强化系数．提供的理论和计算方法对其他试验场具有普遍的参考价值．     

多轴平稳非高斯随机振动试验控制方法

多轴向平稳非高斯随机振动控制试验能够对指定响应信号的时、频域特征进行同时控制。提出了一种快速生成具有指定功率谱密度、斜度和峭度的平稳非高斯随机振动信号的方法。通过频率采样方法将目标功率谱密度设计成滤波器,利用非线性变换方法获取非高斯随机信号,再将此信号经过设计的滤波器以获得满足要求的非高斯随机信号。该方法简单、快速并克服了传统非线性变换方法的缺点。进一步将此方法应用于三轴向平稳非高斯随机振动试验中,给出了三轴向非高斯随机振动控制的闭环均衡步骤,此方法能够同时对信号的功率谱自谱、相干系数、相位差以及斜度和峭度进行解耦控制。进行了三轴向平稳非高斯随机振动控制试验,三个方向上加速度信号的功率谱密度、斜度和峭度控制效果均令人满意,满足工程应用要求。     

宽量程真空传感器可靠性强化试验及故障分析

面向宽量程真空传感器研发阶段的可靠性优化,设计低温步进、高温步进、快速温变、振动步进和综合环境5项可靠性强化试验,并搭建真空对比测试系统。在经历每项可靠性强化试验后,对比试验获得被测传感器和标准传感器测试不同真空度的示值。真空测试和可靠性分析结果表明,被测传感器的全温区温度可靠性较好,但振动步进试验使1只传感器发生故障,电离灯丝断裂、引线针与陶瓷基座间的钎焊裂纹、可伐环与陶瓷基座间的钎焊孔洞是被测传感器试验和使用故障的主要原因。从优化管芯结构设计、自动化灯丝焊接工艺、优化钎焊工艺等方面提出传感器可靠性优化建议。此外,虽然被测传感器相对标准传感器的测量误差较大,但被测传感器之间的输出一致性较好,可从后端补偿上提高传感器测量精度。     

运输包装加速随机振动试验研究综述

加速随机振动试验是目前物流过程中运输包装损伤和安全性评价的重要技术手段,通过提高振动等级压缩测试时间,省时高效,减少运输包装系统优化设计周期,包括四部分：实际物流车辆振动信号的采集与分析、实验室信号模拟与再现、运输包装振动疲劳损伤与寿命评估、加速随机振动试验理论与方法。从以上四方面进行综述,总结了实际车辆振动信号统计特征和影响因素、信号模拟方法及特点,阐述了振动疲劳理论与运输包装损伤研究进展,分析了目前加速随机振动试验研究现状和不足,讨论了目前该研究领域尚未解决的问题,指出了进一步的研究方向。     

On the time compression (test acceleration) of broadband random vibration tests

Many broadband random vibration tests are time compressed. This is done by increasing test intensity according to the Basquin model of cyclic fatigue. Conventionally, the test level is accelerated from the root mean acceleration and an assumed power constant (k = 2) is applied. Using conventional analysis the potential error in test severity can be very large if k is incorrect. The Miner–Palmgren hypothesis of accumulated fatigue is used to re‐assess the potential error in test severity accounting for the non‐stationarity found in road distribution. This shows a substantially reduced sensitivity to the value of k depending on the distribution of actual vibration intensities around the time‐compressed test intensity. Using an example of a leaf‐sprung vehicle, the conventional level of time compression is shown to have low sensitivity to errors in k, whereas for an example of an air‐ride vehicle a lower level of time compression is needed to reduce error sensitivity. Copyright © 2010 John Wiley & Sons, Ltd.     

Integration of computation and testing for reliability estimation

This paper develops a methodology to integrate reliability testing and computational reliability analysis for product development. The presence of information uncertainty such as statistical uncertainty and modeling error is incorporated. The integration of testing and computation leads to a more cost-efficient estimation of failure probability and life distribution than the tests-only approach currently followed by the industry. A Bayesian procedure is proposed to quantify the modeling uncertainty using random parameters, including the uncertainty in mechanical and statistical model selection and the uncertainty in distribution parameters. An adaptive method is developed to determine the number of tests needed to achieve a desired confidence level in the reliability estimates, by combining prior computational prediction and test data. Two kinds of tests — failure probability estimation and life estimation — are considered. The prior distribution and confidence interval of failure probability in both cases are estimated using computational reliability methods, and are updated using the results of tests performed during the product development phase.     

Integration method for reliability assessment with multi-source incomplete accelerated degradation testing data

ABSTRACT

During the product life cycle, the lifetime information will be collected at each stage, mainly from different tests at the R&D phase, field usage, and maintenance. To comprehensively conduct reliability assessments, it generally requires the integration of multi-source datasets, even that from similar products. In this article, we considered the scenario that products have been arranged with several accelerated degradation tests (ADT) under different types of accelerated stresses with dependency. The obtained data is called incomplete ADT dataset with incomplete stress conditions which fails the traditional integration method for reliability assessments. A novel method is proposed to accomplish this task through mutually exclusive set (MES) theory. The probability assignments for each dataset are given through the union set of several MESs. Then, the multi-source ADT datasets are integrated with the assigned weights of probabilities. Finally, a simulation study and a real application are given to illustrate the effectiveness of the proposed methodology.     

A Bayesian framework for accelerated reliability growth testing with multiple sources of uncertainty

Reliability growth tests are often used for achieving a target reliability for complex systems via multiple test‐fix stages with limited testing resources. Such tests can be sped up via accelerated life testing (ALT) where test units are exposed to harsher‐than‐normal conditions. In this paper, a Bayesian framework is proposed to analyze ALT data in reliability growth. In particular, a complex system with components that have multiple competing failure modes is considered, and the time to failure of each failure mode is assumed to follow a Weibull distribution. We also assume that the accelerated condition has a fixed time scaling effect on each of the failure modes. In addition, a corrective action with fixed ineffectiveness can be performed at the end of each stage to reduce the occurrence of each failure mode. Under the Bayesian framework, a general model is developed to handle uncertainty on all model parameters, and several special cases with some parameters being known are also studied. A simulation study is conducted to assess the performance of the proposed models in estimating the final reliability of the system and to study the effects of unbiased and biased prior knowledge on the system‐level reliability estimates.     

非高斯随机振动下包装件时变振动可靠性分析

包装件在流通过程中经常受到非高斯随机振动激励的作用,提出了一种包装件在非高斯随机振动激励条件下的时变可靠性的分析方法。结合多项式混沌扩展和Karhunen-Loeve扩展,提出了基于功率谱(或自相关函数)、均值、方差、偏斜度和峭度信息的非高斯随机振动激励的模拟方法;为减小数值分析量,应用拟蒙特卡洛法,在随机变量空间中合理控制变量的分布模拟非高斯随机振动激励,通过四阶龙格库塔法分析,用较少的随机振动模拟样本准确得到了包装件加速度响应的前四阶矩和自相关函数。基于响应的统计信息,应用该研究提出的多项式混沌扩展、Karhunen-Loeve扩展和拟蒙特卡洛分析,获得包装件加速度响应样本,计算包装件的时变可靠性,用原始蒙特卡洛法验证了计算的准确性;该方法在包装件的可靠性分析、包装系统优化等方面具有重要意义。     

An orthogonal normal transformation of correlated non-normal random variables for structural reliability

In this paper, an efficient and explicit technique is proposed for transforming correlated non-normal random variables into independent standard normal variables based on the three-parameter (3P) lognormal distribution. In contrast with the classic Nataf transformation, the derived equivalent correlation coefficient in non-orthogonal standard normal space of the proposed transformation is expressed as an explicit formula, thereby avoiding tedious iteration algorithm or multifarious empirical formulas. Meanwhile, the applicable range of the original correlation coefficient is determined based on fundamental properties of the proposed expression of correlation distortion and the definition of correlation coefficient. The proposed transformation requires only the first three moments (i.e., mean, standard deviation, and skewness) of basic random variables, as well as their correlation matrix. Therefore, the proposed transformation can also be applied even when the joint distribution or marginal distributions of the basic random variables are unknown. Several numerical examples are presented to demonstrate the user-friendliness, efficiency, and accuracy of the proposed transformation applied in structural reliability analysis involving correlated non-normal random variables.     

The role of the British Society for Strain Measurement and in particular the Product Quality and Reliability Testing Group in enhancement of the Nation's quality and reliability initiative*

This paper reviews the very important role of the BSSM in contributing to the wide understanding and application of experimental stress analysis in product design evaluation and testing. The paper presents the benefits of strain measurement techniques and a number of initiatives which have been taken by the BSSM in relation to quality and reliability which have included meetings held in conjunction with other organisations, the BSSM Certificate Scheme and involvement in standards for strain gauge measurements. The paper concludes with some facts and figures related to Quality Assurance, and costs of failure and fracture, from authoritative published sources in the UK and USA.     

A literature review on planning and analysis of accelerated testing for reliability assessment

Accelerated testing has been widely used for several decades. Started with accelerated life tests with constant‐stress loadings, more interest has been focused prominently on accelerated degradation tests and time‐varying stress loadings. Because accelerated testing is crucial to the assessment of product reliability and the design of warranty policy, it is important to develop an efficacious test plan that encompasses and addresses important issues, such as design of stress profiles, sample allocation, test duration, measurement frequency, and budget constraint. In recent years, extensive research has been conducted on the optimal design of accelerated testing plans, and the consideration of multiple stresses with interactions has become a big challenge in such experimental designs. The purpose of this study is to provide a comprehensive review of important methods for statistical inference and optimal design of accelerated testing plans by compiling the existing body of knowledge in the area of accelerated testing. In this work, different types of test planning strategies are categorized, and their drawbacks and the research trends are provided to assist researchers and practitioners in conducting new research in this area.     

On the estimation of failure probability having prescribed statistical moments of first passage time

A method of estimating the probability density function and cumulative distribution function when only the ordinary or central moments of the distribution are known is examined. The technique is used in conjunction with previous work which yields the ordinary moments of time to first passage failure to obtain accurate estimates of the failure probability for two representative oscillators. The results are then compared to those obtained by a nearly exact numerical scheme.