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.     

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.     

Multi-Criteria Decision Analysis integrated with GIS and remote sensing for astronomical observatory site selection in Antalya province,Turkey

Astronomical observatory site selection is a complex problem that involves evaluation of multiple factors from different sources. The aim of this study is to select the best possible candidates for astronomical observations sites using Multi-Criteria Decision Analysis integrated with Geographical Information Systems and remote sensing technologies. The study was implemented in the Antalya province of Turkey, which is convenient for astronomical site observatory facilities with its appropriate climate properties and weather conditions. Eleven factors (cloud cover, precipitable water, earthquake zones, geology, landslide inventory, active fault lines, Digital Elevation Model, city lights, mining activities, settlement areas, roads) were determined, splitting into three categories; meteorological, geographical and anthropogenic criteria. These factors were evaluated using Analytical Hierarchy Process method and the weights of criteria layers were determined. As a result, the most suitable areas were located extensively in western and eastern part of Antalya. This study offers a robust, accurate, cost and time effective procedure for preliminary site selection for astronomical observatory. However, for a final decision of the best location of astronomical observatory, site testing measurements and atmospheric seeing observations will be further required in these preliminary areas.     

旋转飞行器应答式速度测量研究

由于受单天线的方向性限制,采用传统的天线模式不能实现对旋转飞行器连续跟踪测量。通过多天线分集和合成2种模式,可以实现信号的全向接收和转发,但同时带来接收信号阶跃以及信号干涉区等新问题,这些问题会导致信号变化剧烈,能否正确描述信号动态下的特征,并分析其对设备多普勒回路的影响是实现连续高精度跟踪的关键。本文推导了多天线动态下的双程应答多普勒测速方程,详细分析了分集、合成2种天线模式下信号的特征及信号对多普勒回路的影响,并根据分析结果对多普勒回路提出改进建议。     

双星定位系统及其备份星在近地卫星联合定轨建模中的应用

建立了基于双星定位系统距离和观测数据的近地卫星联合定轨模型,设计了相应的数值融合联合定轨算法;为进一步提高近地卫星定轨精度,考虑融合双星及备份星距离和观测数据,建立了基于双星和备份星的近地卫星联合定轨模型及实现算法,并针对不同仿真条件进行了联合定轨仿真实验。仿真计算结果表明,联合定轨方式较传统近地卫星精密定轨方式可以更好地抑制双星星历误差对近地卫星定轨精度的影响,近地卫星和双星的定轨精度均得到了一定程度的提高;同时,融合备份星观测数据的近地卫星联合定轨精度得到进一步改善,达到5.17m。     

数控技术专业双证书认证试点方案制定——以西安航专数控技术专业双证书认证方案为例

以制定数控技术专业双证书认证试点方案为目的，结合市场需求，采用职业岗位能力分析的方法，将职业资格证书认证体系嵌入学历教育，构建了核心课程体系，设计了培养该专业学生核心职业能力的学习包，并设计了相对应的职业资格证书体系，从而制定了该专业双证书认证试点方案，通过实施，取得了好的效果。     

基于继承因子的飞机弹射救生座椅可靠性Bayes评估

为了更有效地解决飞机弹射救生座椅可靠性评估的问题,考虑飞机弹射救生座椅子系统试验数据与系统试验数据之间既有联系又有区别的特点,采用继承因子描述这两种试验数据之间的相似性,建立了一种基于继承因子的飞机弹射救生座椅Bayes可靠性评估方法。采用该方法对某型飞机弹射救生座椅可靠性进行了评估,在置信度90%的情况下其可靠度下限达到了0.954。结果表明,在相同的系统级试验样本量情况下,评估结果比经典统计方法更合理。     

基于贝叶斯理论的低循环疲劳寿命模型不确定性量化

为量化低循环疲劳寿命模型中的不确定性因素,利用贝叶斯理论,采用经典的模型校准形式确立了寿命模型的不确定性量化形式,并结合正态性检验对误差项进行验证;应用马尔可夫链-蒙特卡罗(MCMC)算法获得了模型参数后验分布的抽样样本,在小子样试验数据条件下确定了低循环疲劳寿命的95%不确定性区间,较好地覆盖了寿命的分散性;对参数样本进行了相关性分析,并将异方差回归概率模型与贝叶斯概率模型进行了比较。最后,利用Morris全局灵敏度分析方法获得了Manson-Coffin模型参数的全局灵敏度指标;同时,验证了在模型参数对先验信息敏感,或者说在先验信息影响极大的情况下,采用无信息先验处理方法的合理性。     

基于响应表面法的钛合金零件磨抛加工工艺参数优化

钛合金的化学活性高、热导率低、弹性模量小,是一种典型的难加工材料。随着工业技术的发展,现代工业对钛合金的表面质量提出了更高的要求,因此,对于钛合金磨抛加工这种能够获取高表面质量的加工方法的研究显得非常重要。采用Box-Behnken试验设计方法,进行了工艺参数对表面粗糙度的影响试验,然后基于响应表面法,建立了钛合金磨抛加工表面粗糙度二阶预测模型,并对工艺参数进行了优化。     

船体变形对航天测量船外弹道测量的影响

简要介绍了航天测量船船体变形测量系统的基本构成、测量原理和测量元素,分析了变形测量数据的基本特性,给出了船载外测数据船体变形修正的方法和计算公式;重点考察研究了船体变形数据对航天测量船外测数据和外测定轨的影响。