Sliding mode control design for oblique wing aircraft in wing skewing process

When the wing of Oblique Wing Aircraft (OWA) is skewed, the center of gravity, inertia and aerodynamic characteristics of the aircraft all significantly change, causing an undesirable flight dynamic response, affecting the flying qualities, and even endangering the flight safety. In this study, the dynamic response of an OWA in the wing skewing process is simulated, showing that the three-axis movements of the OWA are highly coupled and present nonlinear characteristics during the wing skewing. As the roll control efficiency of the aileron decreases due to the shortened control arm in an oblique configuration, the all-moving horizontal tail is used for additional roll and the control allocation is performed based on minimum control energy. Given the properties of pitch-roll-yaw coupling and control input and state coupling, and the difficulty of establishing an accurate aerodynamic model in the wing skewing process due to unsteady aerodynamic force, a multi-loop sliding mode controller is formulated by the time-scale separation method. The closed-loop simulation results show that the asymmetric aerodynamics can be balanced and that the velocity and altitude of the aircraft maintain stable, which means that a smooth transition is obtained during the OWA’s wing skewing.     

Direct position determination using single moving rotating linear array: Noncoherent and coherent processing

To improve the resolution and accuracy of Direct Position Determination (DPD), this paper investigates the problem of positioning multiple emitters directly with a single moving Rotating Linear Array (RLA). Firstly, the geometry of the RLA is formulated and analysed. According to its geometry, the intercepted noncoherent signals in multiple interception intervals are modeled. Correspondingly, the MUltiple SIgnal Classification (MUSIC) based noncoherent DPD approach is proposed. Secondly, the synchronous coherent pulse signals are individually considered and formulated. And the coherent DPD approach which aims for localizing this special type of signal is presented by stacking all array responses at different interception intervals. Besides, we also derive the constrained Cramér-Rao Lower Bound (CRLB) expression for both noncoherent and coherent DPD with RLA under the constraint that the altitudes of the emitters are known. At last, computer simulations are included to examine the performance of the proposed approach. The results demonstrate that the localization accuracy and resolution of DPD with single moving linear array can be significantly improved by the array rotation. In addition, coherent DPD with RLA further improves the resolution and increases the maximum emitter number that can be localized compared with the noncoherent DPD with RLA.     

基于随机维纳过程的航空发动机性能衰退研究

针对发动机下发间隔预测的问题，研究了发动机性能衰退规律。基于发动机排气温度裕度（EGTM）数据，建立了随机维纳模型，并使用严酷度因子修正模型，表征不同的工作条件对发动机的影响。利用期望最大化（EM）算法结合贝叶斯定理，对模型参数求解，最终得到了基于性能衰退的发动机平均下发间隔。研究结果表明，在严酷度因子为1.2696的使用条件下，某型号航空发动机性能衰退平均下发间隔为8219循环；基于该模型预测的发动机平均下发间隔与厂商建议的下发时间之间的误差仅为1.7%。     

谐振式加速度计自激振荡电路性能评价方法的研究

针对谐振式加速度计成品率不高、精度低等问题，以石英振梁加速度计为例，采用引进标准信号，将谐振电路作为“黑盒子”，对其开展独立的评价。通过评价电路的驱动电压幅值稳定性、移相稳定性、全温幅值/相位对称性等指标，与加速度计实际指标建立了一一对应的关系，为加速度计研制与性能提升提供了有效依据。实际运用表明，电路噪声性能、温度性能大幅提升，产品成品率从70%提高到了约90%。     

基于Hilbert-Huang变换的航天器发射段力学环境分析

文章基于Hilbert-Huang变换,对某载人航天器发射过程中整流罩分离期间测量的力学环境参数进行处理分析,利用HHT的基函数自适应性特点,得到振动时间历程信号的时频域Hilbert谱,准确识别出信号主频率及对应时间范围。此应用案例可为地面力学试验条件制定以及运载接口条件确定提供参考。     

Modelling ignition probability with pairwise mixing-reaction model for flame particle tracking

Reduced order models for ignition analysis can offer insights into ignition processes and facilitate the combustor optimization. In this study, a Pairwise Mixing-Reaction (PMR) model is formulated to model the interaction between the flame particle and the surrounding cell mixture during Lagrangian flame particle tracking. Specifically, the model accounts for the two-way coupling of mass and energy between the flame particle and the surrounding shell layer by modelling the corresponding turbulent mixing, chemical reaction and evaporation process if present. The state of a flame particle, e.g., burnt, hot gas or extinguished, is determined based on particle temperature. This model can properly describe the ignition process with a spark kernel being initiated in a nonflammable region, which is of practical importance in certain turbine engines and has not been rigorously accounted for by the existing models based on the estimation of local Karlovitz number. The model is integrated into an ignition probability analysis platform and is demonstrated for a methane/air bluff-body flame with the flow and fuel/air mixing characteristics being extracted from a non-reacting simulation. The results show that for the spark location being at the extreme fuel-lean outer shear layer of the recirculation zone, PMR can yield ignition events with a significant number of active flame particles. The mechanisms for the survival of the initial flame particles and the entrainment of the survived flame particles into the recirculation zone are analyzed. The results also show that the ignition probability map from PMR agrees well with the experimental observation: a high ignition probability in the shear layer of the recirculation zone near the mean stoichiometric surface, and low ignition probabilities inside the recirculation zone and the top stagnation region of the recirculation zone. The parametric study shows that the predicted shape of the ignition progress factor and ignition probability is in general insensitive to the model parameters and the model is adequate for quantifying the regions with high ignition probabilities.     

A progressive approach to predict shot peening process parameters for forming integral panel of Al7050-T7451

In this paper, a progressive approach to predict the multiple shot peening process parameters for complex integral panel is proposed. Firstly, the invariable parameters in the forming process including shot size, mass flow, peening distance and peening angle are determined according to the empirical and machine type. Then, the optimal value of air pressure for the whole shot peening is selected by the experimental data. Finally, the feeding speed for every shot peening path is predicted by regression equation. The integral panel part with thickness from 2 mm to 5 mm and curvature radius from 3200 mm to 16000 mm is taken as a research object, and four experiments are conducted. In order to design specimens for acquiring the forming data, one experiment is conducted to compare the curvature radius of the plate and stringer-structural specimens, which were peened along the middle of the two stringers. The most striking finding of this experiment is that the outer shape error range is below 3.9%, so the plate specimens can be used in predicting feeding speed of the integral panel. The second experiment is performed and results show that when the coverage reaches the limit of 80%, the minimum feeding speed is 50 mm/s. By this feeding speed, the forming curvature radius of the specimens with different thickness from the third experiment is measured and compared with the research object, and the optimal air pressure is 0.15 MPa. Then, the plate specimens with thickness from 2 mm to 5 mm are peened in the fourth experiment, and the measured curvature radius data are used to calculate the feeding speed of different shot peening path by regressive analysis method. The algorithm is validated by forming a test part and the average deviation is 0.496 mm. It is shown that the approach can realize the forming of the integral panel precisely.     

正弦压力信号幅值测量无差算法研究

正弦压力校准常用比较法，通过比较标准压力传感器与被校压力传感器在同一正弦压力源中的响应完成被校传感器的幅值校准。对正弦压力信号幅值的测量算法进行了研究，提出了一种控制采样频率为标准激励信号频率整数倍的算法，可实现幅值的无差运算，理论推导和仿真实验表明，该算法能有效提高单频校准的准确度。     

氟塑料-阀芯黏结工艺

为了解决液体火箭发动机主阀阀芯氟塑料与金属黏结不良问题,对其成因与黏结工艺进行研究。采用阀芯压制氟塑料前涂覆自制聚全氟乙丙烯胶黏剂的黏结工艺方法,通过扫描电镜观察黏结面微观结构形貌并进行能谱分析,进而对涂聚全氟乙丙烯胶黏剂的黏结工艺方法进行机理分析,最后开展菌状物试样黏结工艺验证、阀芯工艺验证、工作性能试验验证。试验表明:采用涂聚2遍全氟乙丙烯胶黏剂黏结的工艺方法,可提高氟塑料和金属黏结强度,黏结强度可提高到19 MPa以上,达到未涂胶氟塑料与金属黏结强度的3倍,阀芯黏结合格率达到100%,使用性能满足使用要求,有效解决液体火箭发动机主阀阀芯黏结不良问题。     

Semi-supervised gear fault diagnosis using raw vibration signal based on deep learning

In aerospace industry, gears are the most common parts of a mechanical transmission system. Gear pitting faults could cause the transmission system to crash and give rise to safety disaster. It is always a challenging problem to diagnose the gear pitting condition directly through the raw signal of vibration. In this paper, a novel method named augmented deep sparse autoencoder (ADSAE) is proposed. The method can be used to diagnose the gear pitting fault with relatively few raw vibration signal data. This method is mainly based on the theory of pitting fault diagnosis and creatively combines with both data augmentation ideology and the deep sparse autoencoder algorithm for the fault diagnosis of gear wear. The effectiveness of the proposed method is validated by experiments of six types of gear pitting conditions. The results show that the ADSAE method can effectively increase the network generalization ability and robustness with very high accuracy. This method can effectively diagnose different gear pitting conditions and show the obvious trend according to the severity of gear wear faults. The results obtained by the ADSAE method proposed in this paper are compared with those obtained by other common deep learning methods. This paper provides an important insight into the field of gear fault diagnosis based on deep learning and has a potential practical application value.