In order to solve the issue of missing high-frequency information of flight data in servo system of launch vehicles, a high-frequency feature restoration method based on wavelet multi-resolution analysis is proposed. Initially, features are extracted from ground hot firing test data through wavelet multi-resolution analysis. Subsequently, leveraging the correlation between the angular velocity signal and high-frequency features, a feature matching approach is put forward for predicting the high-frequency features of the flight data. Finally, the linear superposition method is conducted to achieve feature fusion, thus completing the feature restoration process of the flight data. The experimental verification is carried out. It shows that, compared to the baseline data, the restoration results have a consistent commutation frequency pattern, which imply that the proposed feature restoration method is feasible and effective. The study can provide data support for obtaining the characteristics of actual flight profile for aerospace servo products.

Aiming at the damage problem of experimental facilities caused by unsteady chamber pressure in experiment of high temperature gas flow wind tunnel, the mechanism of the influence of collector positions and dimensions on the stability of experimental flow field is studied. Study mainly focuses on the interaction between the waves and separated vortexes. Utilizing CFD method, the pressure distribution is obtained in the chamber. Then the relationship between the interaction of the waves and separated vortexes and experimental stability are also explored, which will provide a reference for the optimal design of the collector. The results show that appropriate collector position and reasonable collector dimensions can reduce the overflow in the chamber. It can also avoid the separated vortex dominating the collector port, and increase the flow of mainstream. It is helpful to the conduction of experiment.

When the power unit of the series hybrid vehicle is overloaded suddenly, the engine torque load rate would be too high, which would lead to abnormally operation. In order to solve this problem, a load compensation strategy based on fuzzy control is designed. By controlling the torque of generator, the engine torque load rate could be regulated, so that avoiding the engine working near the critical condition. The simulation and test results show that the strategy improves the working characteristics of the power unit effectively, makes it operates stable and smoothly until achieve the expected operating point, improves the robustness of the power unit.

The combat effectiveness of equipment strongly depends on the support of ground equipment. Under system combat conditions, how to achieve system empowerment, system enhancement and system collaboration through innovative ground equipment is a major issue of the overall ground profession. An equipment system is taken as the research object. Firstly, the capability requirements of the system operation on the weapon system are analyzed, and the combat mode, task flow and system composition of the weapon system are combined to form a condensed list of the support capability requirements. Secondly, aiming at improving the operational accompanying support management ability and improving the allocation of accompanying support resources, the technical approaches of applying intelligent technology to mobile operations support and enhancing the effectiveness of ground equipment are sorted out, and a technical scheme of intelligent support of equipment is formed. Based on the above research, the preliminary design of information and intelligent support vehicle scheme is completed, and its mobile combat support capability is evaluated.

The flow field simulation and scanning electron microscope observation methods are used to analyze the surface micromorphology of a certain type of turbine blade before and after operation, and the effect of high temperature and high pressure environment on the surface morphology of the blade is investigated. First, in order to improve the calculation efficiency, according to the blade form, a periodic symmetric CFD model of the turbine blade flow field is established, and the temperature and pressure of the flow field are calculated and analyzed by the finite volume method. Then, the surface of the working blade is measured by scanning electron microscope. The morphology is observed to analyze the form of micro-defects on the blade surface. Finally, based on the results of simulation and experimental observations, the reasons for the blade defects and the factors affecting the changes of the blade surface microstructure are analyzed. The results show that the temperature of the leading edge of the blade reaches the highest ${860}\mathrm{\;K}$. Under the combined effect of geometric structure and wave system, the flow characteristics of the flow field near the leading and trailing edge, blade tip, and hub are complicated, and the temperature and pressure distribution in the flow channel is inhomogeneous. The hub near the trailing edge of the blade appears with a cross-grain/inter-grain mixed mode of microcracks about ${180\mu }\mathrm{m}$ in length, and an inclusion crack with a length of about ${30\mu }\mathrm{m}$ appears at the tip of the trailing edge. This is due to the thermal stress of the blade, the metallographic transformation of the blade surface, and the oxidation, hydrogen embrittlement and other effects. According to the actual task of the turbopump, the turbopump ground hot test program should be reasonably arranged, especially in the shutdown stage, consider whether to take atmospheric environmental isolation measures for the cooling of the turbine blades. The current work can provide a reference for the life evaluation of liquid rocket engine turbine blades.

Focusing on the main working phase of liquid rocket engine, with the aid of multivariate non-linear time series analysis, and based on Dual Stage Attention Based Recurrent Neural Networks (DA-RNN), a new time series analysis tool, Convolutional Dual Stage Attention Based Recurrent Neural Networks (CDA-RNN), is proposed, by which a fault trend prediction model is established. Compared with LSTM, DA-RNN, etc, this model shows higher prediction accuracy. Combined with autocorrelation analysis of the prediction residual, a quantitative basis of fault detection is proposed after introducing failure confidence probability. Using hot test data with weak fault to validate the model, result shows that the CDA-RNN model enables robust weak fault muti-parameter detection in unsteady working process. This strategy is so effective that it calls for direct engineering application.

In radar countermeasures, the jammer detects the radar signal, then the signal is sampled by AD and input to FPGA for processing and generating interference signal. When using the FFT IP core officially provided by the FPGA platform Xilinx to perform FFT processing on the data output by the high-speed ADC, data preprocessing of "parallel-serial" is required, which greatly slows down the FFT processing speed. At the same time, the internal resources of FPGA is not maximized. An data processing method based on FPGA input block remapping is proposed. This method uses the data input remapping module to optimize the input data into a parallel block data stream format. Then the FFT butterfly networks process the input data into blocks to obtain the discrete Fourier transform data. Finally, parallel data are output. Experimental results show that this method can effectively save FPGA computing time, improve radar data processing speed, optimize the utilization of FPGA internal resources, and has the characteristics of good real-time performance and high flexibility.

In order to timely and accurately understand the development trend of world aerospace field in 2023, the latest developments in world space transportation system, ballistic missile and hypersonic technology are comprehensively reviewed, involving key model research and development, flight tests and major hot events in the aerospace field of the United States, Russia and other countries. The development of world aerospace field in 2024 is forecasted by summarizing and analyzing.

Considering the dispersion of small signal flow characteristics of servo valve, the control parameters of electro-hydraulic servo system need to be matched and adjusted. An off-line self-optimizing method for electro-hydraulic servo system control parameters based on particle swarm optimization is proposed. The control system task book and manual debugging results decide optimization target characteristics, and the parameter optimization range is determined by the analysis results of servo system stability and statistics of batch production data envelopment. This parameter optimization method takes about 100-240 seconds. Compared with manual approaches, it can greatly improve the mass production debugging efficiency of the control parameters for electro-hydraulic servo system.

In order to achieve lightweight, low cost and refined thermal design, the refined design method of coating thermal protection structure based on ablation mechanism is proposed. It can calculate the thickness of ablative carbon layer with using ablation mechanism, build thermal simulation model of ablation refinement and calculat accurate thermal simulation results. The application of this method can provide an effective and scientific theoretical analysis method for the demonstration of coating thermal protection scheme. It can guide the design of thermal protection scheme, reduce the design cost and shorten the development period.