基于多性能参数的民用航空发动机 实时性能可靠性预测

以民用航空发动机为研究对象,运用性能退化可靠性理论,对发动机的性能可靠性进行了研究.通过分析发动机性能退化过程,利用状态空间方法建立了时变性能退化模型,并通过卡尔曼滤波对性能趋势进行预测;然后考虑各性能参数之间的相关性,运用随机过程理论建立了基于多性能参数的实时性能可靠性预测模型,从而对发动机的退化时间进行实时预测;最后通过实例证明该方法是有效的,并且易于工程实现,同时,也为航空公司进行发动机机队科学管理提供了基础.      

基于加速退化数据的某型电连接器可靠性评估

某型电连接器属于高可靠性、长寿命产品,在短时间内很难获取其失效数据。为了评估其可靠性,在分析其失效机理的基础上设计了步进加速退化试验,通过分析加速退化数据外推出产品在正常工作应力水平下的可靠度函数。试验中以电连接器的接触电阻作为性能参量,选取温度作为加速应力。数据分析时,利用Wiener随机过程对样品退化进行建模。为了提高模型参数的估计精度,采用极大似然法对所有性能退化数据进行整体统计推断。外推其在工作温度下的可靠度时,针对工作温度不恒定的情况利用等效温度表示温度对该产品的综合作用效果。结果表明,提出的基于加速退化数据分析的方法实用、有效,成功实现了某型电连接器的可靠性评估,并可为其他高可靠性产品的可靠性评估工作提供借鉴。     

基于性能退化数据的液体火箭发动机可靠性Bayes评定

性能退化表征的是产品的工作能力随时间逐渐降低的现象。对于液体火箭发动机等试验费用昂贵的高可靠性产品,失效时间数据难以得到,此时性能退化数据是评定其可靠性的重要信息。文章提出用线性随机过程模型来描述产品性能参数逼近临界值的过程,再根据产品的失效机理,推导出产品的失效分布函数形式。相对于传统的寿命分布模型,文中推导的失效分布函数中的参数因物理含义明确而易于通过实时跟踪测量性能参数时间序列数据估计得到。文中还通过一个数值实例说明了该方法在工程上应用的有效性。     

基于Wiener和Copula函数性能退化模型的减推力起飞可靠性收益评估研究

从精细化、规范化管理使用发动机的角度出发,针对航空发动机减推力起飞在可靠性和安全收益指标的贡献度量化评估问题,提出了一种基于性能退化分析的可靠性收益评估方法。建立了单个性能参数Wiener退化量模型,并利用Copula函数进行二元相关性能参数退化量建模,提出了基于Copula函数和Wiener退化过程的二元相关性能可靠性模型。将模型应用于实例分析,通过发动机执行减推力和未执行减推力时的性能退化数据,定量地分析了执行减推力起飞技术对可靠性和在役寿命方面的贡献度,并将文中提出的方法与基于单参数的性能可靠度函数以及二元独立性能参数的性能可靠度函数进行对比分析。结果表明,执行减推力起飞技术的发动机在运行中有更高的安全裕度,在役寿命平均延长了23%左右。     

Gamma过程退化失效可靠性分析

退化型失效产品,可通过退化失效分析对其进行可靠性统计推断。性能退化一般是一个随机过程,并且是单调变化的,为描述产品的退化,给出了一个随机Gamma过程模型,通过求解该过程的首达时分布即可获得产品的失效分布。由于解析方法求解存在很大的难度,给出了一种基于仿真的求解方法。利用所得模型对强激光装置所用的某型金属化膜脉冲电容器进行了可靠性分析,说明了模型的适用性。     

线性独立增量过程分析方法

提出了线性独立增量随机过程的概念和定义,建立了线性独立增量过程回归模型及其分析方法,给出了回归方程和高置信度、高可靠度的置信上、下限曲线.传统回归分析方法只能对数据点进行分析处理,线性独立增量过程分析方法则能够对过程进行回归分析,因此可以对性能退化、裂纹扩展等线性独立增量过程进行整体推断,具有信息量大、精度高的特点.大量Monte Carlo模拟和工程应用表明,在试样数相同的情况下,该方法比传统方法具有更高的精度,而在精度相同的情况下,则可减少试样.      

随机环境应力冲击下基于多参数相关退化的导弹部件寿命预测

为了解决某型导弹部件的贮存寿命预测问题,提出了一种随机环境应力冲击下基于多参数相关退化的寿命预测方法。针对产品存在退化失效与突发失效两种失效模式,利用Wiener、Gamma及Inverse Gaussian等随机过程模型拟合各性能参数的退化数据,并采用Copula函数进行相关性退化失效建模;利用随机环境应力冲击解释突发失效的机理,并采用非均匀泊松过程对突发失效建模;进而建立退化失效与突发失效竞争的贮存寿命预测模型。实例应用说明所提方法能够反映出导弹部件的失效规律,比传统预测方法具有更高的预测准确性,具有较好的工程应用价值。     

性能退化双线性过程方法与成组试验方法的比较

针对性能退化可靠性分析问题,将双线性过程方法与成组试验方法进行了对比分析.首先,从理论层面阐述了双线性过程方法和成组试验方法对性能退化数据的建模过程,可以发现:双线性过程方法通过将性能退化数据作为一个整体进行统计分析,能够避免两步估计造成的信息浪费,提高分析精度.其次,以窗雨刮器开关性能退化试验为例进行了对比分析,结果表明,双线性过程方法共有2.5%的试验数据位于概率为90%的百分位值曲线估计结果上方,符合工程实际需要,而成组试验方法共有15%的试验数据位于百分位值曲线估计结果上方.此外,基于残差分析的模型检验结果表明双线性过程方法更为合理.     

基于退化失效数据的环境因子问题研究

针对具有退化失效特性的高可靠性长寿命产品,在有限试验时间内难以获得大量失效数据进行环境因子研究的问题,通过对产品性能退化特性的监测和分析,研究退化失效环境因子的建模和估计方法.给出了退化失效环境因子的一般定义和数学描述;提出了复合Poisson过程退化轨道模型的退化失效环境因子模型,并给出了环境因子点估计的矩方法和区间估计的二项分布法;通过仿真实例,对方法在工程应用上的有效性进行了说明.      

基于带漂移的布朗运动的民用航空发动机实时性能可靠性预测

以民用航空发动机为研究对象,运用性能退化可靠性理论和随机过程方法,对发动机的可靠性进行了研究.通过分析发动机性能退化过程,建立了基于带漂移的布朗运动的可靠性模型,利用布朗运动特性研究了基于当前状态的退化时间预测方法,实例证明,该方法可操作性强,易于工程实现,为航空公司进行发动机机队科学管理提供了基础.      

Model-driven degradation modeling approaches: Investigation and review

The second law of thermodynamics implies that any animate and inanimate systems degrade and inevitably stops functioning. It is irreversible over time that can be labeled as “the degradation arrow of time”. From perspective of products’ reliability design, it is essential to build appropriate models of describing the degradation arrow of time. The current modeling approaches mainly include the model-driven (having assumed forms based on cognitive experience of mankind) and data-driven (using data learning techniques without form hypothesis) approaches. In this paper, we just investigate and review the model-driven degradation approaches, hoping to provide suggestions of the model construction or selection for scholars or engineers. First, for the single mechanism, degradation law models and stochastic process models are classified as separately depicting the tendency and fluctuation of degradation. For the degradation law model, we propose the concept of meta-models as original types for various personal models. For the stochastic process model, two main types including the non-monotonic and monotonical types are presented. Then, four multi-mechanism degradation types are discussed, that are competitive degradation, multi-stage degradation, coexistence of degradation and impact, and coexistence of degradation and failure. Besides, for the multi-performance degradation, independent and coupling models are introduced. The forms, connotations, applicability and insufficiency of these models are described with a series of examples from the literature and our own experiences. The final explicit suggestions about the potential future work are provided for the development of new degradation models.     

Reliability estimation of mechanical seals based on bivariate dependence analysis and considering model uncertainty

The reliability estimation of mechanical seals is of crucial importance due to their wide applications in pumps in various mechanical systems. Failure of mechanical seals might cause leakage, and might lead to system failure and other relevant consequences. In this study, the reliability estimation for mechanical seals based on bivariate dependence analysis and considering model uncertainty is proposed. The friction torque and leakage rate are two degradation performance indicators of mechanical seals that can be described by the Wiener process, Gamma process, and inverse Gaussian process. The dependence between the two indicators can be described by different copula functions. Then the model uncertainty is considered in the reliability estimation using the Bayesian Model Average (BMA) method, while the unknown parameters in the model are estimated by Bayesian Markov Chain Monte Carlo (MCMC) method. A numerical simulation study and fatigue crack study are conducted to demonstrate the effectiveness of the BMA method to capture model uncertainty. A degradation test of mechanical seals is conducted to verify the proposed model. The optimal stochastic process models for two performance indicators and copula function are determined based on the degradation data. The results show the necessity of using the BMA method in degradation modeling.     

Comparison of two reliability models for performance degradation analysis

In order to investigate the general reliability assessment methods based on performance degradation data, two commonly used stochastic process approaches, bilinear process method and random-effect model were studied. Analyzing procedure and effectiveness of these two methodologies were studied and compared. Meanwhile, the two approaches were illustrated through practical applications. The residual plots and the 10th percentile curves of the two methods were presented to demonstrate the comparative results. The random-effect model yielded more volatile residuals and a lower and unsafe 10th percentile curve. Consequently the bilinear process model can be concluded to derive more reasonable results due to its one-stage estimation property.     

基于退化模型的失效机理一致性检验方法

有效的加速试验必须保证产品的失效机理不变。针对加速退化试验(ADT)可靠性建模的特点,提出了一种基于退化模型的失效机理一致性检验方法。以基于随机过程和基于退化轨迹拟合的退化模型为例,通过加速系数的2种等效定义分别建立了模型参数与失效机理不变的内在联系,进一步推导出其参数在不同应力下须满足的关系。在合理假定检验样本服从正态分布的基础上,利用t统计量对样本的一致性进行检验。通过2个ADT实例验证了所提检验方法的合理性与可行性。