考虑多部件间随机相关性的多阶段退化系统剩余寿命预测方法

多部件系统中部件之间退化可能存在不同程度的相互影响,使得多部件系统常常具有多阶段的退化特征。针对上述问题,本文考虑多部件系统各部件之间相互作用对退化模式的影响,提出一种基于维纳过程的连续退化双向随机相关影响的多阶段系统退化建模与剩余寿命预测方法。首先利用突变点检测建立考虑双向随机相关影响的多阶段维纳过程退化模型,用来描述部件间随机相互影响对多部件系统退化过程产生的影响。其次为了反映各部件退化异质性,并考虑部件的退化速率是由自身固有的退化速率和与其相关的部件产生的退化率相互作用两部分组成,将系统各阶段的漂移系数和扩散系数定义为随机参数,运用期望最大化算法估计未知参数。最后采用贝叶斯算法更新后验参数分布,预测突变点位置,根据首达时间推导考虑各部件之间退化随机相关性的多阶段退化系统剩余寿命的表达式,并通过数值模拟和商用模块化航空推进系统仿真数据集验证了该方法的有效性。     

线性FBM过程随机退化设备剩余寿命自适应预测

现有文献主要通过马尔科夫过程来描述设备的退化轨迹,鲜有考虑历史状态对未来退化轨迹的影响.鉴于此,为了反映退化轨迹的记忆效应对剩余寿命预测的影响,首先基于分数布朗运动建立一种线性随机退化模型,并通过引入随机效应来反映不同样本间的退化差异性;其次,基于弱收敛性理论与分数布朗运动的特性推导剩余寿命分布的近似解析解;再次,基于...     

融合多源数据的非线性退化建模与剩余寿命预测

针对目前基于单个传感器剩余寿命预测方法存在预测精度不高的问题,该文提出一种融合多源传感器数据的非线性退化建模与剩余寿命预测方法。该方法包括复合健康指标的构建、模型参数的估计和传感器融合系数的确定,在确定融合系数后,结合设备历史寿命数据与实时监测数据,利用Bayesian参数更新公式推导出设备的剩余寿命概率分布,实现设备的剩余寿命在线预测。最后通过由商用模块化航空推进系统仿真生成的发动机退化数据集进行仿真实验,结果表明该文所提方法能够有效提高设备剩余寿命预测的准确性。     

基于Gamma退化过程的直升机主减速器行星架剩余寿命预测模型

鉴于Gamma过程具有平稳、独立增量等退化建模所需的属性,将其用于描述设备退化过程,并针对缺乏故障数据时难以进行剩余寿命预测的问题,利用设备运行中采集的表征其退化状态的大量间接状态参数和少量直接状态参数,建立了基于Gamma退化过程的剩余寿命预测模型;针对经验最大化算法中似然函数难以解析求解的问题,引入粒子滤波算法实现了模型参数估计;最后将模型应用于直升机主减速器行星架的剩余寿命预测,得到了不同时刻的预测结果及95%置信区间,验证了预测模型的有效性和准确性。     

基于二元混合随机过程的轴承剩余寿命预测

针对轴承退化问题,基于两个不同变化特点的性能指标,提出了基于二元混合随机过程的轴承剩余寿命(RUL)预测方法。首先,分析两个特点不同的性能指标,选择合适的随机过程(伽马过程或维纳过程)分别构建基于不同性能指标的退化模型;其次,利用Copula函数分析两个性能指标间的相关特性并构建剩余寿命的联合概率密度函数;然后采用分步极大似然估计法在线更新模型参数,预测未来时刻的剩余寿命;最后,通过仿真和轴承实验数据对所提方法进行验证分析。结果显示所提方法能有效地预测轴承的剩余寿命,通过与基于一元随机过程的剩余寿命预测方法的对比分析,发现所提方法具有更好的预测精度。     

考虑环境改变的部件核密度剩余寿命预测

针对风机关键部件运行过程中剩余寿命预测精度受环境变化影响的问题,提出一种考虑环境冲击影响的核密度估计剩余寿命预测模型。首先采用自适应核密度的非参数估计方法对部件的连续自然退化过程建模;其次假设恶劣环境对部件的影响为部件受到的随机冲击,在考虑改变运行环境条件下建立其部件所受冲击与连续退化随机相关的剩余寿命预测模型,并分析其可靠性,最后通过风电机组退化数据及齿轮箱磨损实测数据进行了试验分析,验证了所提模型的准确性和有效性。     

基于MSCNN-LSTM的滚动轴承剩余寿命预测方法

针对现有卷积神经网络(convolutional neural network,CNN)与长短时记忆网络(long short-term memory,LSTM)堆叠的寿命预测方法忽略低层次信息的问题,引入多尺度技术,提出一种多尺度卷积长短时记忆网络模型(multi-scale CNN-LSTM,MSCNN-LSTM)...     

现有混凝土桥梁结构剩余寿命预测方法研究

在回顾桥梁剩余寿命预测方法的基础上,探讨了利用人工神经网络对现有混凝土桥梁结构剩余寿命进行全桥模糊预测的方法。该方法从全桥的角度综合考虑各种因素影响,利用因果分析图及数学模糊规则,事先归纳出影响混凝土桥梁整体寿命的几种主要因素,并利用自编程序对几种主要因素的相关数据进行神经网络训练。训练结果表明,只要网络结构选择合理,配合正常的检测制度与专门的数据采集系统,其对全桥剩余寿命进行模糊预测的结果是具有实用价值的。     

考虑棘轮效应的疲劳寿命预测方法

多轴棘轮加载时轴向加载的恒定应力、剪切应变幅对轴向棘轮应变和疲劳寿命有很大的影响.考虑棘轮效应影响的Coffin模型将棘轮效应与循环部分相结合来计算疲劳寿命,预测结果较好,绝大部分预测结果分布在2倍分散带内.     

齿轮箱状态识别与剩余寿命预测的MoG-BBN法

基于混合高斯输出贝叶斯信念网络模型的齿轮箱退化状态识别与剩余寿命预测新方法,应用聚类评价指标对全寿命过程退化状态数进行优化,通过计算待识别故障特征向量的概率值来确定齿轮箱退化状态,在退化状态识别的基础上,提出了剩余寿命计算方法。再利用齿轮箱全寿命实验数据对此进行验证。结果表明,该方法可以有效地识别齿轮箱故障状态并实现剩余寿命预测,平均预测正确率为96.47 %,为齿轮箱的健康管理提供参考。     

周期应力下非线性退化建模与剩余寿命估计

针对设备在贮存和工作过程中可能存在受到周期性特征应力作用的问题,基于扩散过程,提出一种周期应力作用下的非线性退化模型,并在首达时间意义下,推导得到解析形式的剩余寿命分布函数,给出参数的极大似然估计方法。仿真实验的统计分析验证所提模型的正确性,并说明所提剩余寿命估计方法优于线性建模方法,具有潜在工程应用价值。     

Remaining useful life prediction for lithium-ion batteries using a quantum particle swarm optimization-based particle filter

ABSTRACT

A novel RUL prediction approach for lithium-ion batteries using quantum particle swarm optimization (QPSO)-based particle filter (PF) is proposed. Compared to particle swarm optimization (PSO)-based PF, QPSO-based PF is proved to have a better performance in global searching and has fewer parameters to control, which makes QPSO-PF easier for applications. Moreover, fewer particles are required by QPSO-PF to accurately track the battery's health status, leading to a reduction of computation complexity. RUL prediction results using real data provided by NASA and compared with benchmark approaches demonstrates the superiority of the proposed approach.     

Analyzing degradation data with a random effects spline regression model

ABSTRACT

This article proposes using a random effects spline regression model to analyze degradation data. Spline regression avoids having to specify a parametric function for the true degradation of an item. A distribution for the spline regression coefficients captures the variation of the true degradation curves from item to item. We illustrate the proposed methodology with a real example using a Bayesian approach. The Bayesian approach allows prediction of degradation of a population over time and estimation of reliability is easy to perform.     

Fatigue life estimation under random loading using the energy criterion

A procedure for estimating the useful life of a component for a given (admissable) probability of fatigue fracture origination under random loading is presented. The method uses material constants obtained from the S/N and cyclic stress/strain curves, standard deviation and probability density distribution of the loading process and a macroblock of harmonic cycles obtained by applying the rainflow cycle counting method to the random loading process. Theoretical and experimental lives are found to exhibit good agreement.     

Particle filtering prognostic estimation of the remaining useful life of nonlinear components

Bayesian estimation techniques are being applied with success in component fault diagnosis and prognosis. Within this framework, this paper proposes a methodology for the estimation of the remaining useful life of components based on particle filtering. The approach employs Monte Carlo simulation of a state dynamic model and a measurement model for estimating the posterior probability density function of the state of a degrading component at future times, in other words for predicting the time evolution of the growing fault or damage state. The approach avoids making the simplifying assumptions of linearity and Gaussian noise typical of Kalman filtering, and provides a robust framework for prognosis by accounting effectively for the uncertainties associated to the estimation. Novel tailored estimators are built for higher accuracy. The proposed approach is applied to a crack fault, with satisfactory results.     

A modified model for the estimation of fatigue life derived from random vibration theory

When a component is subjected to variable-amplitude loading, if the fundamental stress–life cycle relationship and an accumulation rule are given, then the fatigue damage or fatigue life of the component can be calculated and/or estimated. In the present paper, random vibration theory is incorporated into the analysis of the above problem. Several formulas are thus derived. Experimental work is then carried out to verify the derived formulas. Comparison is made among the results calculated based on different formulas, different accumulation rules and different random loading. It is concluded that the derived formulas do provide us with quick prediction of the fatigue damage or fatigue life when a component is subjected to variable-amplitude loading that has a certain random nature.     

Isothermal two-phase flow of a vapor-liquid system with non-negligible inertial effects

In this paper we consider the problem of gas/liquid extraction near the bottom well in the context of geothermal energy exploitation. In particular we develop a mathematical model for the isothermal two-phase flow of a mono-component fluid in an undeformable porous media taking into account inertial effects. We use the so-called Forchheimer’s equation to model the relation between the fluid velocity and the pressure gradient in the region of co-existence of the two phases.We formulate the problem in cylindrical geometry assuming steady state and isothermal conditions. We take into account capillary pressure and we study its influence on the whole system. We derive important formulas that allow to predict the main thermodynamical quantities in the region of co-existence of the liquid and gaseous phase and we determine constraints on the physical parameters in order to predict the behavior of the fluid in the domain of the problem. Finally, we perform some numerical simulations to investigate the dependence on the physical parameters involved in the model.     

Spectral method of fatigue life calculation under random multiaxial loading

We develop a new spectral method for the evaluation of fatigue life under random multiaxial loading. This method is a generalization of the known formulas of Miles, Kowalewski, Raikher, and Bolotin based on the power spectral density function of stresses under uniaxial random loads. The power spectral density function of the equivalent stress determined according to a linear criterion of multiaxial random fatigue is introduced in the indicated formulas. It is shown that, in reducing the multiaxial state of loading to the uniaxial state according to linear criteria, the frequency bands of the components of the stress state are transformed into the frequency band of the equivalent stress without increasing its width. This favorable result cannot be obtained if the equivalent stress is calculated according to nonlinear multiaxial fatigue criteria. Technical University of Opole, Opole, Poland, Published in Fizyko-Khimichna Mekhanika Materialiv, Vol. 32, No. 3, pp. 86–96, May–June, 1996.     

Impact of censoring types on the two-stage method for analyzing reliability experiments with random effects

Many reliability experiments are not completely randomized. Instead they involve subsamples, blocks, split-plot structures, etc. A common analysis often uses random effects to account for the impact of the experimental protocol. The two-stage method is an easy way for practitioners to incorporate random effects in the analysis. This article compares performance of the two-stage method under Type I, Type II censored, and uncensored data from a Weibull distribution. We evaluate the effects of censoring type, censoring rate, sample size, and shape parameter on the two-stage method. Then, we apply the two-stage method to a real experiment. Finally, we give practitioners some recommendations for designing and analyzing reliability experiments.