大电流矩形镉镍蓄电池组的FMEA分析

对大电流矩形镉镍电池进行了详细的失效模式与影响分析（ＦＭＥＡ），提出了相应的预防措施，对一南类电池的可靠性和维修性设计具有一定的帮助。     

基于神经网络模型的学习诊断

基于故障树模型的诊断把故障树的底事件分成三部分：必然的故障源集（ＣＦＳ）、正常底事件集（ＮＥＳ）和可能的故障源集（ＰＦＳ），及如何进一步确定ＰＦＳ中各元素的状态（正常或异常）。在存在大量训练样本的情况下，可采用基于神经网络模型的学习诊断方法来确定ＰＦＳ中各元素的状态，并通过对某卫星能源系统故障模拟原理性试验台的故障诊断验证了该方法的有效性。     

航天电连接器及其组件失效分析

介绍了航天电连接器及其组件失效分析中初步分析、详细分析、故障假设和最终鉴定四个阶段的内容及方法。阐述了断路、接触不良、瞬断、绝缘不良、短路、误配线、固定不良和密封不良等常见失效模式和失效机理。给出了失效分析的程序和若干检验方法。     

Numerical analysis for impacts of nozzle end-clearances on aerodynamic performance and forced response in a VNT turbine

It has been well known that nozzle end-clearances in a Variable Nozzle Turbine (VNT) are unfavorable for aerodynamic performance, especially at small openings, and efforts to further decrease size of the clearances are very hard due to thermal expansion. In this paper, both the different sizes of nozzle end-clearances and the various ratios of their distribution at the hub and shroud sides were modelled and investigated by performing 3D Computational Fluid Dynamics (CFD) and Finite Element Analysis (FEA) simulations with a code of transferring the aerodynamic pressure from the CFD results to the FEA calculations. It was found that increasing the size of the nozzle end-clearances divided equally at the hub and shroud sides deteriorates turbine efficiency and turbine wheel reliability, yet increases turbine flow capacity. And, when the total nozzle end-clearances remain the same, varying nozzle end-clearances’ distribution at the hub and shroud sides not only shifts operation point of a VNT turbine, but also affects the turbine wheel vibration stress. Compared with nozzle hub clearance, the shroud clearance is more sensitive to both aerodynamic performance and reliability of a VNT turbine. Consequently, a possibility is put forward to improve VNT turbine efficiency meanwhile decrease vibration stress by optimizing nozzle end-clearances’ distribution.     

飞控系统故障检测的参数模糊自适应调节

提出通过模型参数的模糊比例积分自适应调节，以校正基于模型的飞控系统故障检测中的系统数学模型偏差。针对模型中误差差较大的迎角导数值，将俯仰角加速度的测量值与教学模型估计值之差作为比例积分调节的反馈量，动态实时校正数学模型参数。     

基于故障树的直升机维修差错分析方法的研究

根据维修差错一人的失误机理、差错的墨菲定律，以及事故链模型和JamesReason模型，提出了基于故障树的主动预先的维修差错分析方法，试图在直升机设计之中和直升机交付使用前，通过这种基于故障树的维修差错分析方法，找出设计中、使用维修及使用管理中出现的问题或维修差错，提出改进措施，防止在使用维修中出现维修差错。通过这种主动事前的预防维修差错分析方法，可以消除或减少维修差错，提高直升机的安全性。     

A simulation study on the mode conversion process from slow Z-mode to LO mode by the tunneling effect and variations of beaming angle

For a particular angle of incidence wave, it is possible for a slow Z-mode wave incident on an inhomogeneous plasma slab to be converted into an LO mode wave. But for another wave normal angle of the incident wave, it has been considered impossible, since an evanescence region exists between two mode branches. In this case we expect that the mode conversion takes place through the tunneling effect. We investigate the effect of the spatial scale of the density gradient on the mode conversion efficiency in an inhomogeneous plasma where the mode conversion can occur only by the tunneling effect. We use the computer simulation solving Maxwell’s equations and the motion of a cold electron fluid. By considering the steepness of the density gradient, the simulation results show the efficient mode conversion could be expected even in the case that the mismatch of the refractive indexes prevents the close coupling of plasma waves. Also, we show for these cases the beaming angle does not correspond to Jones’ formula. This effect leads to the angles larger and smaller than the angle estimated by the formula. This type of mode conversion process becomes important in a case where the different plasmas form a discontinuity at their contact boundary.     

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.     

基于三维有限元的火箭模态振型斜率预示方法研究

振型斜率火箭是姿控系统设计的重要参数,对飞行任务的可靠性与安全性有着至关重要的作用。依据全箭动特性的测量原理及参数定义,结合三维有限元建模方法和模型修正技术,全面考虑了速率陀螺、惯组安装位置处的局部刚度对振型和振型斜率的影响,建立了基于局部细节精细化建模的全箭模态振型斜率预示方法,并总结了3种不同的振型斜率提取方法,提高了振型斜率的预示精度。同时提供了三维模型振型一维化的方法,解决了使用三维有限元模型计算弹性运动方程式系数的难题。     

Applying fuzzy bi-dimensional scenario-based model to the assessment of Mars mission architecture scenarios

Sending man to Mars has been a long-held dream of humankind. NASA plans human planetary explorations using approaches that are technically feasible, have reasonable risks and have relatively low costs. This study presents a novel Multi-Attribute Decision Making (MADM) model for evaluating a range of potential mission scenarios for the human exploration of Mars. The three alternatives identified by the Mission Operations Directorate (MOD) at the Johnson Space Center (JSC) include split mission, combo lander and dual scenarios. The proposed framework subsumes the following key methods: first, the conjunction method is used to minimize the number of alternative mission scenarios; second, the Fuzzy Risk Failure Mode and Effects Analysis (RFMEA) is used to analyze the potential failure of the alternative scenarios; third, the fuzzy group Real Option Analysis (ROA) is used to estimate the expected costs and benefits of the alternative scenarios; and fourth, the fuzzy group permutation approach is used to select the optimal mission scenario. We present the results of a case study at NASA’s Johnson Space center to demonstrate: (1) the complexity of mission scenario selection involving subjective and objective judgments provided by multiple space exploration experts; and (2) a systematic and structured method for aggregating quantitative and qualitative data concerning a large number of competing and conflicting mission events.