Automatic placement was carried out using domestic dry fibers. The process parameters for the automatic placement of domestic dry fibers were formulated and verified. The laying quality of layer skipping was investigated. A T-shaped stringer preform was prepared. Vacuum-assisted molding was performed on the preform with layer skipping laying and the T-shaped stringer preform. Metallographic microscopic observation and ultrasonic C-scanning were conducted on their molding quality. The results show that the automatic placement preform of domestic dry fibers can achieve effective automatic placement preforming. The automatic placement preform of domestic dry fibers has good infiltration characteristics and can meet the process requirements of vacuum-assisted molding. The vacuum-assisted liquid molding quality of the automatic placement preform of dry fibers after the optimization of the resin flow channel design basically meets the requirements of molding quality.

Due to the inefficiency, high labor intensity, poor sealing quality, and challenges in controlling the amount of glue applied of traditional manual gluing methods, this study proposes a solution of the automatic gluing process using multi-parameter coupling based on colloid morphology to enhance the stable control of glue amount and colloid morphology of automated gluing processes. First, an orthogonal experimental design is conducted to analyze the impact of multiple parameters on the automated gluing process, with Pearson correlation coefficient analysis used to identify the key influencing parameters. Next, gluing experiments are performed on three different gluing objects to explore the optimal gluing parameters. Ultimately, the three-dimensional detection technology is employed to acquire the point cloud data of the colloid. By utilizing point cloud data processing algorithms, more accurate positional information is obtained. The crosssectional area of the colloid is calculated using the trapezoidal numerical integration method to determine the colloid’s morphological type. Through comprehensive analysis of the multi-parameter coupled automated gluing experiments, the optimal gluing parameters are identified: a speed of 5 mm/s, a pressure of 103 kPa, a distance of 3 mm, and an angle of 90°, the glue morphology is optimal, effectively preventing problems such as glue leakage, breaks, and excessively narrow or wide glue bodies. This approach improves the efficiency and precision of the gluing process.

This study integrates metal 3D printing technology, optical fiber metallization, and laser welding preparation – encapsulation processes to design a high-temperature, large-strain optical fiber sensor with low stiffness and a wide measurement range. The aim is to address the challenge of monitoring thermal and mechanical parameters in aeroengine turbine blades. The designed sensor employs a hybrid demodulation method based on fiber Bragg grating (FBG) wavelength and light intensity, enabling precise measurement of temperature and strain. Through theoretical modeling, finite element simulation, and structural optimization of a grooved “8”-shaped spring substrate, the sensor’s reaction force on the measured structure is reduced to 167 N/ε. Experimental results demonstrate that the sensor can achieve a large-range strain measurement of 37520 με, with a temperature linearity of 0.9878 within the range of room temperature to 500 ℃. Additionally, the sensor exhibits excellent temperature-strain decoupling performance, with a maximum decoupling error of less than 8%. These outstanding characteristics indicate that the designed sensor has promising application prospects for high-temperature strain monitoring in aero-engine turbine blades.

Advanced composite structures have been widely applied in aircraft. Compared with traditional metallic materials, their application not only enables the lightweight aircraft design but also enhances damage tolerance. The harsh service environment and complex load conditions pose severe challenges to the aerospace composite structures. Therefore, health monitoring of composite structures has become an inevitable way to ensure the in-service safety of aircraft. This paper analyzes the damage mechanism and typical damage modes of composite structures, and introduces the health monitoring requirements of aerospace composite structures. Regarding the monitoring of macroscopic and microscopic damage, health status, and lifespan of aircraft composite structures, the application status of traditional monitoring methods is summarized. Research progress of advanced structural health monitoring (SHM) technologies, such as flexible electronic skins and selfpowered sensors, is introduced. Innovative application of intelligence technologies such as multi-sensor data fusion technology, digital twin and machine learning in the SHM system of aerospace composite structures is also discussed. A brief overview of the practical engineering applications of SHM technology in aerospace sector, both domestically and internationally, is presented, and the future research priorities for its future development directions and intelligence are discussed, which offers reference for the research on the health monitoring of aerospace composite structures.

To address the issue of multiple sensor requirements in current blade tip timing (BTT) techniques, which limit their practicality, this study proposes a strategy for identifying the blade natural frequency using a single sensor without prior knowledge by investigating the aliasing pattern in single-sensor BTT signals. The strategy involves time-frequency analysis of variable-speed BTT signals, projecting the time-frequency diagram onto the frequency axis, and performing peak searching on the projected diagram to identify the blade’s natural frequency using a single sensor without prior knowledge. Simulation and experimental results demonstrate the feasibility and effectiveness of the proposed identification strategy. Compared with traditional identification methods, this approach has the ability to filter out synchronous components and offers a new solution for the application of low-intrusion BTT techniques.

In response to the instantaneous temperature changes caused by complex operating conditions in the service state of aero-engine, the temperature sensor exhibits hysteresis due to the thermal inertia of its own materials, and the collected temperature signals are susceptible to noise interference. We conducted pre-processing analysis anddynamic compensation research on the dynamic response measured temperature signal of a certain type of aero-engine using platinum resistance sensors in service. By using the optimized CEEMDAN algorithm to extract and filter out mid to high frequency noise features from measured signals, and based on Hilbert transform to filter out small random noise and reconstruct the final signal, the denoising results are characterized by the correlation coefficient with the theoretical response curve of the sensor. On this basis, the ARX model with parameter optimization of the reconstructed signal was used for overall dynamic error compensation. Comparative analysis was conducted through root mean square dynamic error and time constant calculation, and uncertainty of the reconstructed signal was evaluated. The results show that the optimized CEEMDAN and Hilbert transform can more effectively remove noise and reconstruct the original signal, with a correlation coefficient of 99.9% with the sensor response curve and a relative expanded uncertainty of about 3.3%. The ARX model parameter w is relatively large, the maximum reduction in overall dynamic error after compensation is 71.36%, and the time constant is reduced by 2.76 s.

Due to the influence of external loads such as gravity, the structure of aircraft assembly positioning tool is inevitably deformed, which directly affects the assembly accuracy of aircraft structure. However, due to the occlusion of product shape, the traditional vision-based structural deformation measurement method can’t directly obtain the structural deformation of tooling. In this paper, an accurate and fast prediction method of terminal deformation of positioning structure based on laser data inversion is proposed. The positioning structure is scanned and measured by laser scanner, and the measured numerical model is obtained. Based on the digital simulation model of the positioning structure, the simulation data set is obtained automatically, and the mapping model between the deformation of the terminal and the deformation of the visible region is established by using the multi-layer perceptron network. On this basis, the inverse differential optimization method of the terminal deformation of the tool structure is constructed, and the inverse solution of the terminal deformation of the positioning tool structure is realized. The results show that the maximum error between the predicted value and the measured value is 8.25%, which verifies the validity of the proposed method.

The integrated molding technology of T-shaped composite stiffened panel is an important means to realize light weight, high strength and low cost of composite product. The work based on the structural changes of the composite during the layering process, a skin-stiffener integrated T-shaped stiffened panel structure was designed. Through solid modeling, combined with the Young’s modulus, shear modulus, Poisson’s ratio and linear elastic constitutive model, the service behavior of the integrated T-shaped stiffened panel structure was simulated by finite element method. The results of finite element analysis show that the static mechanical properties of the integration composite T-shaped stiffened panel structure are better than those of the traditional structure. Meanwhile, the dynamic impact resistance of the integrated T-shaped stiffened panel can reach the similar level of the traditional T-shaped stiffened panel by adjusting the thickness of the skin. In addition, in order to verify the feasibility of the integrated molding technology of T-shaped stiffened panel, the integrated molding die with easy operation, low cost, uniform temperature distribution, and controllable thermal deformation was designed, and the integrated molding process of T-shaped stiffened panel was explored. The results have guiding significance for the quality control of the integrated molding of T-shaped stiffened panel.

To further enhance the wear resistance and corrosion resistance of micro-arc oxidation (MAO) film on 2A12 aluminum alloy, MAO process based on sodium hexametaphosphate solution system was carried out. The effects of doping graphene on the properties (such as morphology, thickness, wear resistance, corrosion resistance and hardness) of MAO film were studied by adding different concentrations of graphene dispersions. The results show that the MAO
film with the best properties is obtained when the mass concentration of graphene is 0.4 g/L. Micro-pores and microcracks in the MAO film are significantly reduced, and the thickness of film is also increased. Compared to the MAO film prepared without doping graphene, the hardness of the graphene-doped MAO film is increased by 73%, the wear amount is decreased by 8.2 mg, the self-corrosion potential is increased by 0.294 V and the self-corrosion current density is decre ased by 2 orders of magnitude.

Aiming at the attitude control problem of quadrotor unmanned aerial vehicles under the conditions of model uncertainty and unknown external disturbances, an improved linear active disturbance rejection attitude control method capable of realizing error-free disturbance tracking has been designed. Firstly, the error correction mechanism is introduced into the extended state observer to achieve disturbance-free tracking and estimation of the system, and the Levant differentiator is used to accurately extract the input signals of the controller. The cascade control strategy is adopted to decompose the attitude control into a cascade dual-loop control structure, that is, the angular velocity control is the inner loop and the angle control is the outer loop, thereby improving the anti-interference ability and robustness of the controller. Based on the semi-physical simulation environment, the attitude control effects under different disturbance conditions are simulated and tested. The simulation results prove that the controller designed in this paper has high control accuracy and stability and can meet the requirements of the attitude control of quadrotor unmanned aerial vehicles.

The static tensile test was conducted on composite materials embedded with buckypaper sensor to verify the ability of buckypaper sensors to monitor the crack propagation in composite materials. Taking glass fiber composites as an example, the resistance response of buckypaper sensors at various stages of crack generation was studied. The stage of crack generation is predicted by the change rate of resistance, so as to realize the monitoring of composite crack. The composite specimens were stretched to the crack initiation, propagation and fracture stages, respectively. Observe the change of the resistance change rate of the buckypaper sensor. The change rate of sensor resistance shows different trends with different stages of crack development. The cross-section image near the sensor is obtained by cross-section metallographic microscopic test. It is proved that the buckypaper sensors has the ability to monitor the crack propagation of composite materials.

In order to study the correlation law between the pit foundation morphology and residual stress field and the parameters of shot peening, the main factors affecting the effect of shot peening and their internal correlation were summarized. In the experiment, the pre-mixed water jet shot peening (WJSP) device independently developed by the research group was used to carry out a platform test on 18CrNiMo7–6 carburized steel. The shot peening coverage rate of the sample surface was changed by adjusting the nozzle moving speed and changing the damping, so as to verify the relationship between the coverage rate and the single-pass pit depth and the residual stress field. The effect of shot peening parameters on the diffusion width and angle is studied by analyzing the jet structure and experiment. The relationship of shot peening intensity and residual stress field was verified by changing the parameters of shot peening. The test results show that the coverage rate is the main factor affecting the single pass pit depth. At high coverage rate, material removal is caused by repeated erosion of pellets, resulting in the increase rate of single pass pit depth is much higher than that at low coverage rate. The pressure is the main factor affecting the jet diffusion angle, and the jet diffusion angle reaches its stable value of 3.3° after 12 MPa. The relationship between the nozzle inlet pressure and the diffusion angle is established by regression analysis. The residual stress field is greatly affected by the peening intensity, the depth of the layer where the surface residual stress and the maximum residual stress value are located, and the total residual stress layer is greatly
affected by the pellet diameter. Compared with the large-size pellet, the small-size pellet can introduce a larger surface residual stress, and the maximum residual stress value is greatly affected by the pellet velocity.