基于及时修正策略可靠性增长的动态Bayes评估方法

针对指数寿命型设备在及时修正策略下的可靠性增长过程,提出了一种动态Bayes评估方法。该方法建立了及时修正策略下的AMSAA模型,并依据已有研制试验数据,对下一次试验的设备失效率进行预测,并将预测结果作为对新技术状态下设备失效率的验前认识,然后利用最大熵方法给出设备失效率的验前分布,进而实现对产品可靠性增长的Bayes统计分析。最后给出了该方法的具体算例,通过对比分析证明了该方法的有效性。     

液体火箭发动机环境因子的Bayes估计

基于液体火箭发动机的寿命服从威布尔分布的条件,假定天地试验环境下威布尔分布的形状参数不变,运用Bayes方法对weibull分布天地实验条件下的环境因子进行分析,给出了环境因子在平方损失下的Bayes估计,并与极大似然估计法进行比较,通过仿真实例验证了该方法的有效性。     

贝叶斯回归支持向量机的软测量建模方法

提出了一种基于贝叶斯证据框架的回归型支持向量机的参数选择和软测量建模方法。证据框架的第1层推理用来解释支持向量机的训练。证据框架的第2和第3层推理用于自动调整正则化参数和核参数并使其接近最优值。然后,将这种基于贝叶斯证据框架的回归型支持向量机用于估计聚丙烯腈生产过程的质量指标。仿真结果表明了该方法的有效性。     

基于粒子滤波的结构疲劳裂纹扩展动态贝叶斯推断方法

准确预测结构的疲劳裂纹扩展过程是开展飞机单机寿命监控与剩余寿命估算的基础。提出一种基于动态贝叶斯网络的结构疲劳裂纹扩展预测方法,结合疲劳裂纹扩展的先验知识与后验知识来准确地推断裂纹长度;研究粒子滤波算法中不同粒子数对动态贝叶斯网络推断精度的影响规律;通过对单孔板结构与耳片连接结构件在随机载荷谱下进行裂纹扩展研究。结果表明：动态贝叶斯网络方法可以对复杂结构的疲劳裂纹扩展进行准确预测,预测精度相对于传统方法提高50% 以上。     

Variational Bayesian Kalman filter using natural gradient

We propose a technique based on the natural gradient method for variational lower bound maximization for a variational Bayesian Kalman filter. The natural gradient approach is applied to the Kullback-Leibler divergence between the parameterized variational distribution and the posterior density of interest. Using a Gaussian assumption for the parametrized variational distribution, we obtain a closed-form iterative procedure for the Kullback-Leibler divergence minimization, producing estimates of...     

Bayesian approach to retrieval of vertical ozone profile from radiometry data

A technique for retrieving vertical distributions (profiles) of atmospheric gas constituents from data of passive remote sensing of the atmosphere is proposed. The goal of the technique based on the statistical (Bayesian) approach to solution of inverse problems is construction of probability distribution for a sought quantity throughout the interval of the studied heights. It is assumed that initial data contain measurement noise, and a priori information about properties of the profile is used. It is proposed to approximate the sought profile by a function in the form of an artificial neural network. This approximation allows optimal inclusion of a priori information into retrieval procedure, thus ensuring the most effective regularization of the problem. Efficiency of the proposed technique is demonstrated on an example of retrieval of vertical ozone profile from data of ground-based sounding of the atmosphere in the millimeter wavelength range. Results of profile retrieval from model data and from spectra of radiation temperature of the atmosphere measured in the Apatity (67° N, 33° E) in the winter of 2002–2003 are presented.     

Provocative radio transients and base rate bias: A Bayesian argument for conservatism

Most searches for alien radio transmissions have focused on finding omni-directional or purposefully earth-directed beams of enduring duration. However, most of the interesting signals so far detected have been transient and non-repeatable in nature. These signals could very well be the first data points in an ever-growing data base of such signals used to construct a probabilistic argument for the existence of extraterrestrial intelligence. This paper looks at the effect base rate bias could have on deciding which signals to include in such an archive based upon the likely assumption that our ability to discern natural from artificial signals will be less than perfect.     

Aircraft air conditioning system health state estimation and prediction for predictive maintenance

The vast potential of system health monitoring and condition based maintenance on modern commercial aircraft is being realized through the innovative use of Airplane Condition Monitoring System (ACMS) data. However there are few methods addressing the issues of failure prognostics and predictive maintenance for commercial aircraft Air Conditioning System (ACS). This study developed a Bayesian failure prognostics approach using ACMS data for predictive maintenance of ACS. First, a health index characterizing the ACS health state is inferred from a multiple sensor signals using a data driven method. Then a dynamic linear model is proposed to describe the degradation process for failure prognostics. Bayesian inference formulas are carried out for degradation estimation and prediction. The developed approach is applied on a passenger aircraft fleet with ACMS data recorded for one year. The analysis of the case study shows that the developed method can produce satisfactory prognostics results, where all the ACS failure precursors are identified in advance, and the relative errors for the failure time prediction made when just entering the degradation warning stage are less than 8%. This would allow operators to proactively plan future maintenance.     

基于贝叶斯网络的飞机变流器故障诊断 决策系统的设计与实现

文章在介绍飞机变流器维修决策特点的基础上,给出了一种基于贝叶斯网络的变流器故障诊断决策系统的软件结构,并分析了模型建造、知识库管理、模型推理、诊断决策、实例收集、模型学习等模块的功能和算法,以实现面向不确定性信息时的诊断决策功能。     

某飞行器数据记录设备的可靠性综合评估

针对飞行器数据记录设备的的小子样可靠性评估问题,从贝叶斯定理出发,进行了理论推导,建立了由分系统的可靠性参数综合评估系统可靠性参数的理论模型,并对某飞行器数据记录设备进行了可靠性综合评估