基于UIO的航空发动机执行机构故障诊断

为了提高航空发动机诊断过程中对噪声干扰和模型参数变化的鲁棒性,应用UIO(Unknown Input Ob-server)理论估计发动机动态系统的工作状态,通过干扰正交投影弱化外界干扰对状态估计的影响,处理了航空发动机执行机构的故障诊断问题。对航空发动机执行机构设计一组UIO观测器,其中每个UIO用于监测估计对应执行机构的故障偏移量,计算系统输出理论估计值与发动机实际测量信号间的残差数据,分析残差队列的幅值特性,实现航空发动机执行机构系统的故障检测和隔离。某型涡扇发动机上的实验结果表明,与Kalman滤波算法相比,UIO诊断方法更能鲁棒地检测和隔离出执行机构故障。     

液体火箭发动机参数计算及误差确定

通过地面试验取得的数据所建立的液体火箭发动机参数计算和误差确定的经验公式，在导弹飞行试验中，对发动机参数计算起重要作用。本文就发动机主要参数及误差的经验公式进行推导和确定。     

综合电子调节器喘振信号器的仿真与虚拟设计研究

某型涡扇发动机喘振信号器是综合电子调节器的重要附件之一，如何仿真和虚拟喘振信号器，对发动机喘振试验仿真及综合电子调节器的数字化研究都具有重要意义。通过MATLAB软件仿真论证了虚拟传感器设计的可行性，并根据虚拟仪器技术，充分利用现有资源，设计完成了替代原喘振信号器的虚拟传感器。     

Reliability assessment of engine electronic controllers based on Bayesian deep learning and cloud computing

The reliability of an Engine Electronic Controller (EEC) attracts attention, which has a critical impact on aircraft engine safety. Reliability assessment is an important part of the design phase. However, the complex composition of EEC and the characteristic of the Phased-Mission System (PMS) lead to the difficulty of assessment. This paper puts forward an advanced approach, considering the complex products and uncertain mission profiles to evaluate the Mean Time Between Failures (MTBF) in the design phase. The failure mechanisms of complex components are deduced by Bayesian Deep Learning (BDL) intelligent algorithm. And copious samples of reliability simulation are solved by cloud computing technology. Based on the result of BDL and cloud computing, simulations are conducted with the Physics of Failure (PoF) theory and Failure Behavior Model (FBM). This reliability assessment approach can evaluate MTBF of electronic products without reference to physical tests. Finally, an EEC is applied to verify the effectiveness and accuracy of the method.     

Sequential ensemble optimization based on general surrogate model prediction variance and its application on engine acceleration schedule design

The Efficient Global Optimization (EGO) algorithm has been widely used in the numerical design optimization of engineering systems. However, the need for an uncertainty estimator limits the selection of a surrogate model. In this paper, a Sequential Ensemble Optimization (SEO) algorithm based on the ensemble model is proposed. In the proposed algorithm, there is no limitation on the selection of an individual surrogate model. Specifically, the SEO is built based on the EGO by extending the EGO algorithm so that it can be used in combination with the ensemble model. Also, a new uncertainty estimator for any surrogate model named the General Uncertainty Estimator (GUE) is proposed. The performance of the proposed SEO algorithm is verified by the simulations using ten well-known mathematical functions with varying dimensions. The results show that the proposed SEO algorithm performs better than the traditional EGO algorithm in terms of both the final optimization results and the convergence rate. Further, the proposed algorithm is applied to the global optimization control for turbo-fan engine acceleration schedule design.     

固体发动机静止试验噪声分析的新途径

喷流噪声和气动噪声引起的声振是固体发动机静止试验时最严重的振环境。噪声分析通常是用精密声级计和滤波器，倍频程谱分析需用１１个档位的滤波器，１／３倍频程则需用３４个档位的滤波器。     

固体火箭发动机静止试验振动特性分析

以动力学、声学和信号系统分析等基础理论为依据,通过大量的实测数据,揭示了固体火箭发动机静止试验的全过程中在地面和高空模拟两种试验状态下,发动机壳体振动特性与发动机工作时产生的喷气噪声两者之间的内在关系。     

基于激光自准直的发动机轴孔同轴度在线检测方法

涡扇发动机定子轴孔的同轴度会影响发动机整体质量和运转情况,故而定子轴孔同轴度的大小是影响发动机质量的一个重要指标,减小同轴度误差可以提高发动机的运行质量,因而对发动机同轴度精密检测的要求也越来越高。为了解决现有人工检测方法中存在的效率低、精度不高的问题,且为了克服定子装配后的待测孔位置较深导致现有通用检测仪器无法直接测量装配后同轴度的困难,在分析了国内外同轴度检测研究现状的基础上,将激光准直技术、轴孔定心测量技术相结合,设计基于激光自准直的检测方法和装置。所设计针对规定型号涡扇发动机定子轴孔的同轴度检测装置,系统变形量约4μm,定心误差小于4μm,并得出了具有普适性的发动机定子轴孔同轴度检测方法,有望实现发动机定子轴孔同轴度误差的在线检测,并有效缩短装配时长、优化总装工艺。     

混合管面积和位置对排气引射器性能的影响

通过对一个轴对称波瓣主喷管与４种不同截面积的圆形混合管、并分别在不同轴向位置时的组合试验,研究了混合管与主喷管截面积之比Ａｍ／Ａｐ及轴向间距Ｌｍｐ对排气引射系统的引射系数、压力损失系数和气动性能综合参数等的影响。结果表明：在试验范围内,Ａｍ／Ａｐ增大,系统的引射系数增大、综合氯动性能改善;Ｌｍｇ增大,４系统的引射系数和压力损失系数也增大。对于不同范围,压力损失系数增加的斜率不同,;总的趋势则是综合     

加力涡扇发动机过失速/旋转失速特性分析

研究了混合加力涡扇发动机过失速特性数值模拟方法。采用了轴流压综系统的逐级动态响应模型,并发展了风扇出口分流环内外流耦合分析模型。采用两种不同方式诱导了涡扇发动机过失不稳定流态。结果表明发动机的函道比的动态突变可成为预测涡扇发动机进入不可忧复失速状态的关键参数。