Model parameter estimation and residual life prediction for a partially observable failing system

We consider a partially observable degrading system subject to condition monitoring and random failure. The system's condition is categorized into one of three states: a healthy state, a warning state, and a failure state. Only the failure state is observable. While the system is operational, vector data that is stochastically related to the system state is obtained through condition monitoring at regular sampling epochs. The state process evolution follows a hidden semi‐Markov model (HSMM) and Erlang distribution is used for modeling the system's sojourn time in each of its operational states. The Expectation‐maximization (EM) algorithm is applied to estimate the state and observation parameters of the HSMM. Explicit formulas for several important quantities for the system residual life estimation such as the conditional reliability function and the mean residual life are derived in terms of the posterior probability that the system is in the warning state. Numerical examples are presented to demonstrate the applicability of the estimation procedure and failure prediction method. A comparison results with hidden Markov modeling are provided to illustrate the effectiveness of the proposed model. © 2015 Wiley Periodicals, Inc. Naval Research Logistics 62: 190–205, 2015     

基于油液分析的装备状态多阶段组合预测模型

状态预测是状态维修的关键步骤之一。针对装备状态变化规律复杂、特点难易准确掌握的关键问题,以延时时间概念和两阶段预知模型为基础,提出了根据不同阶段特点采用不同预测方法的多阶段组合预测模型。通过油液分析及其相关规定,对装备运行阶段进行了具体划分,给出了适应各阶段特点的预测方法。最后,通过实例验证了该模型的有效性。     

高超音速化学平衡流粘性激波层数值计算

本文给出了层流化学平衡粘性激波层方程对于细长解析体的数值解。这些求解结果是通过空间步进方法得到的,并且与参考文献里的计算结果作了比较,以估价该方法的精确度。结果表明,这种控制方程完全耦合求解的方法能够给出相当精确和稳定的结果,这些结果与参考文献的计算结果相当吻合。     

环肋圆柱壳模型在水下爆炸响应试验中的边界条件

为验证试验研究中环肋圆柱壳模型的边界条件,运用大型商业有限元程序MSC.DYTRAN分别设置3种边界条件,对试验过程进行了数值仿真研究。壳体塑性变形的仿真过程显示,迎爆面中部首先变形,随后侧爆面和背爆面相继变形,壳体最终形成数个凸凹相间的轴向凹凸带,最大塑性变形发生在迎爆面中心肋位。壳体塑性变形的仿真计算结果与试验结果的对比结果表明:固支边界条件符合试验实际情况。该结论适用于试验研究中模型边界条件的确立。     

基于灰色系统理论的设备状态监测系统设计

介绍了设备状态集中监测系统的构建和灰色系统理论在设备状态预测中的应用原理及方法．利用Matlab提供的基于最小二乘法的非线性曲线拟合函数能方便地求解一阶灰微分方程,从而得到原始数列的预测值表达式．应用实例表明,基于灰色系统理论的预测模型适用于小样本不确定问题的研究,预测精度高、实现容易．基于灰色系统理论的设备状态监测系统的研制对于科学制定维修计划,改进设备的管理维护手段,确保试验任务的质量和进度具有重要作用．     

基于AdaBoost-SVM算法的某火炮炮闩技术状态评估

针对现役装备技术状态评估多依赖于手工拆卸的现状,提出一种基于AdaBoost-SVM模式识别算法的在线技术状态评估方法。利用人工后坐在线检测设备对炮闩装置技术状态参数进行检测,在对检测数据进行相关性分析特征提取的基础上,引入支持向量机模式识别方法,建立炮闩装置技术状态评估模型。通过将评估模型与Ada-Boost算法相结合,每次迭代都根据测试精度对分类错误的样本点和各分量分类器的权重重新赋值,在下一次迭代中形成新的分量分类器以优化分类结果,最终将各分量分类器依其权重综合完成评估。实例分析结果验证了评估模型的正确性和有效性。     

带混合误差的Ishikawa迭代格式

将Ishikawa型迭代格式的收敛性问题推广到带混合误差的Ishikawa型迭代格式的情形 ,同时所用的证明方法和技巧有所改进     

非线性边值问题的一种高精度计算模型

讨论非线性边值问题的一种高精度计算模型 .利用积分值将边值问题转化为形式初值问题 ,构造了一类四阶精度的计算格式 ,证明了收敛性 .通过算例表明该方法收敛速度高 ,计算量小 .     

发动机冷却燃料做功潜力?分析

在高马赫数飞行下,用燃料冷却超燃冲压发动机壁面的冷却需求量大于发动机燃烧量。为了降低燃料的冷却量以及实现燃料冷却量和燃烧量的匹配,采用?分析法对超燃冲压发动机壁面燃料冷却工质进行做功潜力分析。发动机壁面冷却燃料的特性决定其热量?大小。根据发动机壁面温度分布、热流密度分布计算热量?,建立稳定流动燃料工质的?平衡方程。结果表明：在壁面最高温度为1200K时,传入壁面的热量为562.4kW,其中理论热量?为541.3kW;冷却燃料工质流量的增加,最大输出功减小;燃料工质出口温度增加,输出功减小,燃料工质出口压力增加,输出功基本不变。     

A model to predict the residual life of aircraft engines based upon oil analysis data

This paper reports on a study using the available oil monitoring information, such as the data obtained using the Spectrometric Oil Analysis Programme (SOAP), to predict the residual life of a set of aircraft engines. The relationship between oil monitoring information and the residual life is established using the concept of the proportional residual, which states that the predicted residual life may be proportional to the wear increment measured by the oil analysis programmes. Assuming such a relationship between wear and the residual life exists, we formulated a recursive prediction model for the item's residual life given measured oil monitoring information to date. A set of censored life data of 30 aircraft engines (right censored due to preventive overhaul) along with the history of their monitored metal concentration information are available to us. The metal concentration information includes many variables, such as Fe, Cu, Al, etc.; not all of them are useful, and some of them may be correlated. The principal component analysis (PCA) has been adopted to reduce the dimension of the original data set and to produce a new set of uncorrelated variables, which we shall use in the prediction model. The procedure associated with estimating model parameters is discussed. The model is fitted to the actual SOAP data from the aircraft engines, and the goodness‐of‐fit test has been carried out. © 2005 Wiley Periodicals, Inc. Naval Research Logistics, 2005.