Online condition diagnosis for a two-stage gearbox machinery of an aerospace utilization system using an ensemble multi-fault features indexing approach

China manned space station is designed to operate for over ten years. Long-term and sustainable research on space science and technology will be conducted during its operation. The application payloads must meet the ‘‘long life and high reliability" mission requirement. Gearbox machinery is one of the essential devices in an aerospace utilization system, failure of which may lead to downtime loss even during some disastrous catastrophes. A fault diagnosis of gearbox has attracted attentions for its significance in preventing catastrophic accidents and guaranteeing sufficient maintenance. A novel fault diagnosis method based on the Ensemble Multi-Fault Features Indexing(EMFFI) approach is proposed for the condition monitoring of gearboxes. Different from traditional methods of signal analysis in the one-dimensional space, this study employs a supervised learning method to determine the faults of a gearbox in a two-dimensional space using the classification model established by training the features extracted automatically from diagnostic vibration signals captured. The proposed method mainly includes the following steps. First, the vibration signals are transformed into a bi-spectrum contour map utilizing bi-spectrum technology,which provides a basis for the following image-based feature extraction. Then, Speeded-Up Robustness Feature(SURF) is applied to automatically extract the image feature points of the bi-spectrum contour map using a multi-fault features indexing theory, and the feature dimension is reduced by Linear Discriminant Analysis(LDA). Finally, Random Forest(RF) is introduced to identify the fault types of the gearbox. The test results verify that the proposed method based on the multi-fault features indexing approach achieves the target of high diagnostic accuracy and can serve as a highly effective technique to discover faults in a gearbox machinery such as a two-stage one.     

Experimental investigation on dynamic response of flat blades with underplatform dampers

One test rig with three blades and two Under-Platform Dampers (UPDs) is established to better understand the dynamical behavior of blades with UPDs. A pre-loaded spring is used to simulate the centrifugal load acting on the damper, thereby achieving continuous adjustment of the pressing load. UPDs with different forms, sizes and materials are carefully designed as experimental control groups. Noncontact measurement via a laser Doppler velocimeter is employed and contact excitation which is performed by an electromagnetic exciter is adopted to directly obtain the magnitude of the excitation load by a force sensor mounted on the excitation rod. Particular attention is paid to the influence of the contact status of the contact surfaces, e.g. the pressure-sensitive paper is used to measure the effective contact area of the UPDs. The experimental variables are selected as the centrifugal force, the amplitude of the excitation force, the damper mass, the effective contact area, and the damper material. The Frequency Response Function (FRF) of the blade under different experimental parameters is obtained by slow frequency sweep under sinusoidal excitation to study the influence of each parameter on the dynamic characteristics of the blade and the mechanism analysis is carried out combined with the experimental results.     

基于高保真有限元模型失谐叶盘受迫响应的统计特性

采用极值理论分析失谐叶盘最大受迫响应的统计特性并应用于某压气机叶盘上。对失谐叶盘进行减缩建模,运用蒙特卡洛方法模拟响应计算,研究不同激励阶次下最大响应放大因子的分布特性。采用极值理论对最大响应放大因子分布进行统计学建模,以极大似然估计方法求解未知参数,进行分布拟合,并采用K-S(Kolmogorov-Smirnov)检验方法检验各分布函数拟合的好坏程度。对某压气机叶盘进行失谐响应统计特性分析,对比了7种分布函数对最大响应放大因子的拟合效果,结果表明:极值分布、二参数威布尔分布、正态分布、对数正态分布和伽马分布拟合效果较差;常用的三参数威布尔分布不如广义极值分布的拟合效果好。因此,说明广义极值分布更能准确地描述失谐叶盘动力响应的统计特性。      

塑料与纸包装材料的生命周期评价研究

由于塑料在自然界中的难降解,“以纸代塑”引起人们的关注,然而生命周期的评价结构表明,纸在环境保护方面并不具有优势,本文采用简式生命周期矩阵对这两种包装材料进行了分析和评价。     

飞行器力学环境参数分布特性及飞行散差研究进展

因各方对飞行器力学环境散布特性、散差量级等的认知和理解存在较大差异,相关标准的规定也不一致,故在实际使用过程中存在较大歧异。文章搜集整理了大量关于飞行力学环境方面的国内外文献资料,论述散布特点、统计分析方法以及飞行散差等的研究历史及现状,提出了设计过程中的应对措施以及后续研究建议,为环境条件的精细化设计以及产品的可靠性分析提供参考。     

基于融合伽马变换全卷积神经网络的火星地貌分割方法

为了让火星巡视器在有限的寿命内能获得更多的科学产出,需要提高巡视器在火星表面的自主通过能力,而火星表面地貌类型是评估巡视器可通过性的重要信息。因此,提出了融合伽马变换的全卷积神经网络(FCN)火星表面地貌分割算法。首先,考虑对巡视器通过性的影响,确认地貌分类的类型,基于好奇号拍摄的火星地表图像Mars32K数据库,构建地貌分割数据集;其次,使用自适应伽马变换(AGT)对灰度单一的火星图像进行预处理,减弱了光照等因素干扰;最后,利用数据集训练一个FCN,以实现对火星表面地貌的分割预测。仿真结果表明:网络测试准确率达到83.03%,地形分割预测结果可靠,验证了方法的可行性。     

含故障统计相依组件的多态复杂系统故障树分析

为精确评估可重复使用火箭发动机系统可靠性,采用带约束变量的布尔算法将状态分析与故障树分析恰当结合,从而对含故障统计相依组件的复杂多态可重复使用火箭发动机系统进行可靠性分析.以航天飞机主发动机（SSME）为研究对象,对管路多态性及预燃室和涡轮泵之间的故障相依性进行深入研究.结果表明:该布尔算法能够很好地消除组件统计相依性从而简化复杂多态系统故障树,组件之间失效相依性对系统可靠性影响较大,因此需要加强组件多态及相依性的研究来获得更精确的系统可靠度.      

Aero-engine fault diagnosis applying new fast support vector algorithm

A new fast learning algorithm was presented to solve the large-scale support vector machine ( SVM ) training problem of aero-engine fault diagnosis.The relative boundary vectors ( RBVs ) instead of all the original training samples were used for the training of the binary SVM fault classifiers.This pruning strategy decreased the number of final training sample significantly and can keep classification accuracy almost invariable.Accordingly , the training time was shortened to 1 / 20compared with basic SVM classifier.Meanwhile , owing to the reduction of support vector number , the classification time was also reduced.When sample aliasing existed , the aliasing sample points which were not of the same class were eliminated before the relative boundary vectors were computed.Besides , the samples near the relative boundary vectors were selected for SVM training in order to prevent the loss of some key sample points resulted from aliasing.This can improve classification accuracy effectively.A simulation example to classify 5classes of combination fault of aero-engine gas path components was finished and the total fault classification accuracy reached 96.1%.Simulation results show that this fast learning algorithm is effective , reliable and easy to be implemented for engineering application.     

基于设计变量空间范围自适应优化设计方法研究

通过对翼型优化设计方法的研究,对设计变量在设计空间的分布进行了探讨,建立了设计变量空间范围自适应优化设计方法,解决了优化设计模型建立过程中的设计变量空间范围的选择问题.该方法建立了聚集度的概念,利用聚集度对优化设计过程中设计变量在设计空间内的分布规律进行统计分析,并根据统计分布规律对设计变量的设计空间进行调整,将设计变量重构,实现了优化设计过程中的设计变量空间自适应.该设计变量空间范围自适应优化设计方法,一方面能够在给定的条件下扩大搜索范围来搜索满足工程设计需要的最优解,一方面又能够通过对设计变量的重构提高搜索算法的搜索效率.利用该方法对NACA 0012和NLF(1) 0416翼型进行了优化设计,并与固定设计变量空间范围的优化设计方法进行对比分析.优化结果验证了本文提出的优化设计方法具有一定的可行性,可以在更大范围内找到最优解,并具有较高的优化搜索效率.     

直流磁控溅射ZnO:Al薄膜的光电和红外发射特性

以锌、铝合金(ω(Al)=3%)为靶材,利用直流反应磁控溅射法制备了系列掺铝氧化锌ZnO:Al(ZAO)薄膜样品,通过X射线衍射(XRD)、扫描电子显微镜(SEM)、分光光度计、霍耳效应及红外发射率测量仪等测试仪器或方法表征了样品的结构、形貌、光学、电学及红外发射特性.测得样品最低电阻率达到1.8×10^-6(Ω·m),最大禁带宽度为3.47?eV,可见光区平均透过率达到90%,8~14?μm波段平均红外发射率在0.26~0.9之间.上述特性均随衬底温度和溅射功率的变化有着规律的变化.当方块电阻小于45?Ω时,薄膜在8~14?μm波段平均红外发射率与方块电阻遵循二阶函数变化规律.