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.     

Aircraft engine fault detection based on grouped convolutional denoising autoencoders

Many existing aircraft engine fault detection methods are highly dependent on performance deviation data that are provided by the original equipment manufacturer. To improve the independent engine fault detection ability, Aircraft Communications Addressing and Reporting System (ACARS) data can be used. However, owing to the characteristics of high dimension, complex correlations between parameters, and large noise content, it is difficult for existing methods to detect faults effectively by using ACARS data. To solve this problem, a novel engine fault detection method based on original ACARS data is proposed. First, inspired by computer vision methods, all variables were divided into separated groups according to their correlations. Then, an improved convolutional denoising autoencoder was used to extract the features of each group. Finally, all of the extracted features were fused to form feature vectors. Thereby, fault samples could be identified based on these feature vectors. Experiments were conducted to validate the effectiveness and efficiency of our method and other competing methods by considering real ACARS data as the data source. The results reveal the good performance of our method with regard to comprehensive fault detection and robustness. Additionally, the computational and time costs of our method are shown to be relatively low.     

融合静电信号和气路参数的发动机性能评估方法

为了研究静电监测技术对航空发动机的监测效果,开展了航空涡喷发动机静电监测台架实验,获得了140个完整试车阶段的静电信号数据。针对发动机传统气路性能评估方法的信息源有限的问题,提出了一种融合静电信号和气路参数的发动机性能评估流程和方法,进一步采用了基于逻辑回归模型的评估算法对发动机的综合性能进行量化评估,通过融合试车实验的静电数据和性能参数,对发动机的健康状态评价方法进行研究。结果表明:当健康值为0.9以上可以认为发动机为健康状态,当健康值小于0.3时可以认为发动机已经发生了较为严重的退化,所提出的融合评估方法要优于传统的性能参数评估方法,能够提前预警气路性能严重退化。     

大子午扩张涡轮扇形叶栅变工况性能实验研究

为了研究大子午扩张低压涡轮变工况下的流动性能,分别对大子午扩张低压涡轮的两套不同的扇形叶栅进行气动实验研究。在设计进口气流角条件下,分别进行不同高亚声速马赫数出口变工况实验研究;在出口马赫数不变的条件下,完成变攻角实验。分析了大子午叶栅流动损失特点和二次流的影响规律。结果表明:大子午扩张实验叶栅出口存在两个明显的高损失通道涡,上通道涡位于展向1/3位置,远离上端壁,且强度明显大于下通道涡。随着马赫数增加,叶栅出口流动损失增加了15%。大子午扩张涡轮端壁曲率影响近端壁叶片的压强分布和变工况敏感性,优化端壁曲率将有助于流动状态的改善。     

主流湍流度对涡轮导叶吸力面W型气膜孔冷却效率影响的实验研究

为了获得亚声速涡轮导叶吸力面不同位置处单排W型气膜孔的气膜冷却特性,在短周期跨声速风洞中实验研究了吹风比、主流湍流度对W型气膜孔冷却效率的影响。两列单排气膜孔分别布置在吸力面16%和21%相对弧长处,实验进口雷诺数范围为3.0×10⁵~9.0×10⁵,吹风比范围是0.5~2.0,叶栅出口等熵马赫数为0.8,高低湍流度分别为14.7% 和1.3%。实验结果表明：低湍流度时孔排1和孔排2下游的气膜冷却效率都随吹风比的增大先增大后减小,最佳吹风比分别为BR=1.2和BR=0.8。由于孔排1和孔排2所处位置的主流边界层状态不同,导致湍流度对于气膜冷却效率有不同的影响。对于孔排1,大吹风比时高湍流度使冷气核心向壁面移动,提高了气膜冷却效率;而小吹风比时,湍流度对冷却效率的影响随雷诺数升高而减弱。对于孔排2,大吹风比时高湍流度提高了孔附近区域的冷却效率,同时加快了冷却效率沿流向下降的速度,而在小吹风比时高湍流度显著降低了孔排下游气膜冷却效率。     

外加磁场对脉冲等离子体推力器性能的影响

为了研究外加磁场对PPT性能的影响,建立了PPT带外加磁场的机电模型,并用三种不同放电能量水平的PPT验证了该模型的可靠性。利用该模型研究了外加磁场强度、模式、位置以及长度对PPT性能的影响。结果表明,对于尾部馈送型PPT,当外加磁场增加时,PPT性能先增加后减小,存在最优的外加磁场强度。对于LES-6 PPT和LES-8/9 PPT,外加磁场从极板的最左端开始施加效果最好;当外加磁场强度分别为0.25T,0.50T,0.75T,1.00T时,这两种PPT对应的最适合施加磁场长度分别是1.3mm,1.8mm,2.1mm,2.3mm和1.6mm,2.8mm,3.4mm,3.7mm。对于TMU PPT,外加磁场从极板的最右端开始施加效果最好,但是施加磁场长度应该根据具体实验结果并结合仿真计算来决定。     

Inconel718多通道放电烧蚀铣削加工技术研究

为了提高高温合金Inconel718电火花放电烧蚀加工效率,改善工件表面质量,使用多通道放电烧蚀加工新方法对Inconel718进行多通道放电烧蚀铣削加工试验。研究表明:在多通道放电烧蚀加工过程中,放电通道的个数是随机的;在一个脉冲放电周期中,随着通道数目的增加,电压波形呈阶梯下降,总回路电流波形呈阶梯上升。对比常规电火花烧蚀加工,多通道放电烧蚀加工的总回路电流提高,使得材料蚀除率提高73.7%;同时,多通道放电分散放电能量,使得多通道放电烧蚀加工后工件表面粗糙度较常规电火花烧蚀加工下降14.6%,工件表面微裂纹变少,裂纹的宽度和长度变小。     

BN纤维/Nylon1010复合电子基板材料的制备与性能

采用挤压注塑法制备BN／Nylonl010复合电子基板材料,研究了不同BN纤维填充量的复合基板材料的微观组织结构和复合电子基板材料的介电性能及导热性能。结果表明,当BN纤维体积含量小于40％时,BN纤维基本上以孤岛形式分布在Nylon1010基体上;当BN纤维体积含量大于40％时,BN纤维开始形成连续网络。复合基板的介电常数随着BN纤维含量的增加而线性增加,介质损耗则随着BN纤维含量的增加而线性降低,复合基板的热导率随BN纤维的加入量增加而增大,但起初变化较小。当BN纤维体积含量大于40％时,热导率开始迅速增加。     

一种面向运载火箭自动对接的三维测量场构建方法

旋转激光自动经纬仪系统(R-LATs)是一种基于前方角度交汇的分布式大尺寸测量系统。各激光扫描基站的布局位置直接影响着测量区域内的测量精度和应用性能。从测量区域的测量不确定度量化着手,利用蒙特卡罗法获取各点的测量不确定度,以测量区域的最大不确定度作为主要优化目标,利用差分进化算法自动寻优,更简单有效地实现了面向运载火箭自动对接的R-LATs系统布站优化。最后进行了运载火箭对接测量场的实际应用验证。应用结果表明:该方法能有效优化激光扫描基站布局,提高系统测量精度,满足实际应用需求。