考虑非线性退化与随机失效阈值的剩余寿命预测

针对广泛存在的非线性退化设备,现有方法尚未考虑随机失效阈值对剩余寿命预测结果的影响。因此,通过对设备性能退化过程进行分析,提出了一种综合考虑非线性退化与随机失效阈值的剩余寿命预测方法。基于Wiener过程构建了考虑个体差异与测量误差的非线性退化模型;基于卡尔曼滤波算法建立状态空间模型以实现对退化状态的在线更新;基于极大似然法估计失效阈值分布系数估计方法,得到随机失效阈值的概率分布;基于随机失效阈值推导出剩余寿命的概率分布,实现对剩余寿命的在线预测。算例研究表明,所提方法可以有效地提升剩余寿命预测的准确性,具备一定工程应用价值。     

基于竞争失效建模的导弹贮存寿命评估方法

为了提高导弹贮存寿命估计的准确性,提出了一种基于退化失效与突发失效竞争的导弹贮存寿命估计方法。基于建模假设,建立导弹竞争失效模型;采用赤池信息准则(AIC)来确定导弹退化过程的最优随机过程模型,进而建立其退化失效模型;采用威布尔分布和比例危险模型,建立基于退化量影响的突发失效模型;采用极大似然估计算法,求解模型未知参数。结合实例分析,验证了所建模型的正确性和优势。     

考虑有损伤测量条件下的设备剩余寿命的建模分析

在有损测量的情况下,仅从退化数据本身出发所建的模型不能反映设备的真实退化过程.尤其在测量导致的设备性能退化量不可忽略时,不考虑测量耗损量将不能有效进行预测和评估.为解决这个问题,首先基于维纳过程建立有损测量的设备退化过程,进一步给出了相应模型的参数估计方法和基于贝叶斯理论的设备剩余寿命的实时更新方法,最后通过一个仿真示...     

基于SF-REM的齿轮箱剩余寿命预测方法研究

剩余寿命预测是视情维修决策的重点和难点.针对工程实践中历史数据少、模型参数估计精度低的问题,建立一种基于随机滤波(SF)的齿轮箱剩余寿命预测模型.该方法采用递归期望最大化(REM)算法对模型参数进行递归更新,推导极大似然估计方法的参数递归更新过程,最后经实例验证模型的有效性和实用性.     

装备剩余寿命预测平行仿真中模型动态演化方法

装备平行仿真中的一个重要概念是实时数据驱动的模型动态演化,但是至今仍缺乏具体应用领域的实现方法。以带未知离散冲击的混合退化装备剩余寿命预测为背景,以多态Wiener状态空间模型为演化对象,提出一种装备平行仿真中模型动态演化方法,包括基于交互多模型强跟踪滤波的模型软切换和基于期望最大化算法的模型参数在线估计,并实现了基于平行仿真的装备剩余寿命实时预测。利用某轴承退化数据进行实例研究,结果表明该方法能有效提高仿真逼真度,剩余寿命预测的准确度较高、不确定性较小,具有较高工程应用价值。     

SVM异常数据识别的比例风险预测模型

剩余寿命预测在设备维修管理中扮演着重要的角色,准确的剩余寿命预测对制定维修策略起着至关重要的作用,从而可以有效避免设备故障的发生.提出一种基于支持向量机(SVM)异常数据识别的比例风险模型(PHM)用于剩余寿命的预测,该模式利用支持向量机和比例风险模型分别实现异常状态数据的识别和剩余寿命的预测.案例研究表明,SVM -PHM模型较PHM模型具有更好的预测精度.     

基于退化速率跟踪粒子滤波的剩余使用寿命预测框架

毋庸置疑,剩余使用寿命预测对于设备的健康管理越来越重要。近年来粒子滤波方法被越来越多地应用到设备寿命预测技术当中,这是因为粒子滤波方法能更好的解决非线性非高斯系统滤波问题,而且能够获得不确定度信息。但该方法的预测性能却过度依赖于预测模型,并且对于模型参数的初始分布也比较敏感,这在一定程度上限制了粒子滤波预测方法的进一步发展。本文针对基本粒子滤波预测方法的不足,提出了一种基于退化速率跟踪粒子滤波的通用预测框架,以历史观测数据的退化速率统计规律作为指导来跟踪目标数据的退化速率,实现对粒子滤波预测方法的简化。并将该方法用于轴承和锂离子电池的剩余使用寿命预测,验证了方法的有效性。     

退化速率跟踪粒子滤波在剩余使用寿命预测中的应用

毋庸置疑,剩余使用寿命预测对于设备的健康管理越来越重要。近年来粒子滤波方法被越来越多地应用到设备寿命预测技术当中,这是因为粒子滤波方法能更好地解决非线性非高斯系统滤波问题,而且能够获得不确定度信息。但该方法的预测性能却过度依赖于预测模型,并且对于模型参数的初始分布也比较敏感,这在一定程度上限制了粒子滤波预测方法的进一步发展。针对基本粒子滤波预测方法的不足,提出了一种基于退化速率跟踪粒子滤波的通用预测框架,以历史观测数据的退化速率统计规律作为指导来跟踪目标数据的退化速率,实现对粒子滤波预测方法的简化,并将该方法用于轴承和锂离子电池的剩余使用寿命预测,验证了方法的有效性。     

油库设备更新决策年平均成本方法及应用

基于年平均成本方法，结合军队油库实际，提出了油库设备经济寿命和大修更新决策模型。该模型描述了年均总成本与油库设备原值、残值、折旧方式、利率、经济寿命、运行成本等因素的关系，并运用该模型和成本最小化原理判断油库更新决策的合理时机。计算结果表明：油库设备更新决策模型是合理可靠的。最后，指出了油库设备更新决策应考虑的几个因素，这为油库设备实现价值化管理提供了依据。     

基于相似性的装备剩余寿命预测研究

为了更有效估计装备的剩余寿命,对基于相似性的寿命预测方法进行研究。首先介绍基于相似性的寿命预测方法的基本概念和流程,然后研究基于高斯核回归的退化轨迹提取方法,在传统欧氏距离的基础上,考虑时间范围的影响,改进相似度计算方式,最后用高斯核密度估计得到剩余寿命的区间估计值.一个数值仿真试验表明,基于相似性的方法能够利用失效历史样本对装备的剩余寿命进行有效预测.     

基于年龄更换策略的威布尔分布备件需求计算方法

备件需求量预测在装备保障工作中发挥着重要作用。预防性维修可以消除装备潜在的故障或避免装备发生故障后所导致的严重后果,从而使装备始终处于期望状态。预防性维修策略下备件需求量建模能够以可预见的可靠性数据为基础进行,其关键问题是最佳更换间隔时间的确定。针对威布尔分布装备备件,采用年龄更换策略,确定最佳更换间隔时间,并在此基础上导出威布尔型备件需求计算模型,为备件需求量的预测提供了一种简单有效的方法。     

Optimal renewal policies for complex systems

Most maintenance and replacement models for industrial equipment have been developed for independent single-component machines. Most equipment, however, consists of multiple components. Also, when the maintenance crew services several machines, the maintenance policy for each machine is not independent of the states of the other machines. In this paper, two dynamic programming replacement models are presented. The first is used to determine the optimal replacement policy for multi-component equipment. The second is used to determine the optimal replacement policy for a multi-machine system which uses one replacement crew to service several machines. In addition, an approach is suggested for developing an efficient replacement policy for a multi-component, multi-machine system.     

Determination of burn‐in parameters and residual life for highly reliable products

Today, many products are designed and manufactured to function for a long period of time before they fail. Determining product reliability is a great challenge to manufacturers of highly reliable products with only a relatively short period of time available for internal life testing. In particular, it may be difficult to determine optimal burn‐in parameters and characterize the residual life distribution. A promising alternative is to use data on a quality characteristic (QC) whose degradation over time can be related to product failure. Typically, product failure corresponds to the first passage time of the degradation path beyond a critical value. If degradation paths can be modeled properly, one can predict failure time and determine the life distribution without actually observing failures. In this paper, we first use a Wiener process to describe the continuous degradation path of the quality characteristic of the product. A Wiener process allows nonconstant variance and nonzero correlation among data collected at different time points. We propose a decision rule for classifying a unit as normal or weak, and give an economic model for determining the optimal termination time and other parameters of a burn‐in test. Next, we propose a method for assessing the product's lifetime distribution of the passed units. The proposed methodologies are all based only on the product's initial observed degradation data. Finally, an example of an electronic product, namely contact image scanner (CIS), is used to illustrate the proposed procedure. © 2002 Wiley Periodicals, Inc. Naval Research Logistics, 2003     

系统可靠寿命的不确定性分析及其高效方法

为了分析元器件失效率的不确定性对系统可靠性的影响,借鉴Borgonovo的矩独立灵敏度分析思想,在充分考虑了系统可靠寿命完整不确定性信息的情况下,提出了基于系统可靠寿命的矩独立重要性测度,用来分析不确定性条件下系统元器件失效率对其可靠寿命的平均影响。但由于系统可靠寿命函数是系统可靠度函数的反函数,一般无法解析表达而以隐函数的形式存在,致使该矩独立重要性测度难以高效准确求解。为了解决这一问题,文章提出了一种新的Kriging自适应代理模型的高效算法,该算法以Kriging代理模型预测值的变异系数作为自适应学习函数,通过自主增加新的试验样本,增强代理模型的预测准确性。阀门控制系统和民用飞机电液舵机系统两个算例分析表明,在保证计算精度的情况下,通过变异系数自适应学习函数,仅需添加少量系统可靠寿命试验样本,就能够构建用来充分近似系统可靠寿命函数的Kriging代理模型,解决了重要性测度的高效求解问题,从而验证了所提方法的合理性和算法的高效性。     

Optimal design of accelerated life testing plans for periodical replacement with penalty

Accelerated life testing (ALT), enhanced by optimal test plans, has been widely accepted in practice as a quick approach for estimating the reliability of a product. From the estimation result, preventive maintenance schedules can be determined to ensure the performance of the product under its normal operating conditions. By default, maintenance decision‐making is regarded as the last and least rewarding step. However, sometimes the maintenance schedules, such as preventive maintenance intervals, are predetermined due to customer concerns and/or by various mandatory regulations and rules. Under such circumstances, how to accurately estimate the expenditure (e.g., on maintenance or spare parts management) associated with these maintenance requirements becomes an important issue. A viable solution is to incorporate the maintenance requirements into ALT plans. This paper provides an approach for the optimal design of ALT plans oriented by a mandatory periodical replacement schedule subject to a discounted penalty. The objective is to improve the estimation accuracy of the economic impact of this maintenance requirement. A numerical experiment is provided to demonstrate the approach in practical use. © 2008 Wiley Periodicals, Inc. Naval Research Logistics 2009     

Machine maintenance with workload considerations

Machine maintenance is modeled in the setting of a single‐server queue. Machine deterioration corresponds to slower service rates and failure. This leads to higher congestion and an increase in customer holding costs. The decision‐maker decides when to perform maintenance, which may be done pre‐emptively; before catastrophic failures. Similar to classic maintenance control models, the information available to the decision‐maker includes the state of the server. Unlike classic models, the information also includes the number of customers in queue. Considered are both a repair model and a replacement model. In the repair model, with random replacement times, fixed costs are assumed to be constant in the server state. In the replacement model, both constant and variable fixed costs are considered. It is shown in general that the optimal maintenance policies have switching curve structure that is monotone in the server state. However, the switching curve policies for the repair model are not always monotone in the number of customers in the queue. Numerical examples and two heuristics are also presented. © 2007 Wiley Periodicals, Inc. Naval Research Logistics, 2007     

基于二维量度的复杂设备预防性维修决策优化

针对使用与维修具有两个测量维度的复杂设备,开展了其预防性维修决策的优化研究。基于二维量度的故障模式,给出了二维故障率的定量描述方法;分析了其预防性更换过程的基本过程,探讨了二维量度下更换周期对维修效果的影响,并从经济性角度建立了二维工龄更换费用模型;最后,采用算例的形式,对某设备维修决策同时考虑日历使用时间和行驶里程的情况,进行了二维更换间隔期的优化求解,从而验证了所建立方法与模型的实用性。