The composite wing skin has the characteristics of large size, complex shape and easy rebound. It can’t be used for nondestructive testing by traditional methods such as machine tools. But the robot has the characteristics of flexibility and intelligence, which provides a new idea for nondestructive testing. A scanning path optimization method of large wing skin continuous surface is proposed to solve this kind of problems. Dual robots equipped with ultrasonic scanning equipment, adopting the strategy of two-time inspection: the composite surface is reconstructed by the first scanning, so the accuracy of the second transmission nondestructive inspection is improved. According to the shape of the wing, a general scanning strategy parallel to the stringer is proposed. The points are grouped by the least squares method according to the curvature, the path is optimized by the hybrid genetic LM algorithm. The algorithm means the improved genetic algorithm is used for heuristic global optimization and the LM algorithm is used for deterministic local optimization, so that the optimal scanning path can be obtained efficiently. Then, the simulation is carried out in RoboDK, and the robot is equipped with  ultrasonic detection end to scan the skin. Finally, the precision of the optimized path is verified by the laser scanner on the robot. Simulation and experiment results show that, compared with traditional detection methods, the average detection efficiency of this method is improved by 9.2%. It meets the constraints of ultrasonic detection.

Self-piercing riveting technology is suitable for joining dissimilar materials such as aluminum and steel, and the joint performance is reliable, so it has a wide application scenario in the aviation industry. However, there are few relevant researches on nondestructive detection of self-piercing riveting defect at present. This paper proposes a deep learning-based partial riveting defect detection algorithm for self-piercing riveting. Firstly, the mechanical properties of partial riveting self-piercing riveting parts decreased by 5.6% compared with normal riveting parts through shear mechanical properties test. Then, the degree of partial riveting was defined in the range of 0 – 10 by the external features of self-piercing partial riveting parts. Finally, the detection algorithm was studied, and the detection effect difference between single-step detection and two-step detection was explored. The detection scheme of YOLOv5s (You Only Look Once v5s) and ResNet18 was proposed. In addition, the Gradient-weighted Class Activation Mapping (Grad-CAM) was used to visually explain the differences in the effects of different detection schemes. The test results showed that the proposed detection scheme of YOLOv5s plus ResNet18 could achieve 100% accuracy in the collected data test set, which was higher than the 95.18% accuracy achieved by only using YOLOv5s, and much higher than the 84.1% accuracy achieved by only using ResNet18.

In order to continuously improve the operational performance of the aircraft final assembly production line and promote the reform of the business model, this paper proposed a new management and control mode of aircraft final assembly production line based on digital twin. Firstly, the evolution process of aircraft final assembly production line from physical space to information space is analyzed，as well as the operation control requirements of production line. Secondly, the digital twin composition of aircraft final assembly production line is expounded, at the same time, the digital twin model of assembly production line is constructed based on five-dimension digital twin model. Finally, the virtual model is established based on 3DMAX technology, and a digital twin system for final assembly is built by system development technology. The mapping between physical entity and virtual space is realized by collecting the process data of production line, and the digital twin technology in aircraft final assembly production line is preliminarily applied. The results show that the control mode of aircraft final assembly production line based on digital twin plays an important role in improving production efficiency and quality.

Metal Cutting is one of the main processing methods in the field of aviation manufacturing, and strain and strain rate have a great impact on the chip formation and surface quality. The monitor and control of the strain and strain rate can contribute to the study of the cutting mechanism and conditioning of the machining process. In this paper, we developed an experimental setup for monitoring and controlling of strain rate in the primary shear zone. An in-situ imaging platform of orthogonal cutting is built, which can acquire the images of shear zone in the orthogonal cutting process. A global DIC algorithm accelerated by multithreading is developed to improve the efficiency of image analysis. The image analysis and strain rate calculation can be conducted as well by the DIC software. An online adjustment of spindle controlled by computer is established, which can adjust the spindle magnification in real time according to the relationship between the measured strain rate and the target strain rate. Two experiments for the control of the strain rate in the primary shear zone during orthogonal cutting are carried out. The experimental results show that this system can monitor and control the strain rate in the shear zone with an error less than 10% compared with target value, and less than 23% compared with theoretical predicted value.

Aiming at the problems of the lack of perceptual monitoring accuracy of the existing industrial robot intelligent equipment modeling and the low accuracy of modelling based on theoretical parameters, this paper takes the industrial robot milling system as the research object and constructs a digital twin measurement system that measures the robot joint turning angle data in real time with a high-precision scale to avoid the influence of joint turning angle errors such as gear gap and encoder code loss on the accuracy of digital twin modelling. The digital twin drive model was developed based on the MD – H kinematic modelling method, and the L – M algorithm was used to identify and correct the industrial robot modelling parameters to reduce the influence of geometric errors in the digital twin modelling of the robot. The use of the identified robot joint parameters for modelling has improved the accuracy of the twin model for modelling the motion points of the industrial robot from ±1.6905 mm to ±0.3304 mm, increased by 4.12 times, which demonstrates the correctness of the digital twin modelling method and the feasibility of the identification of the modelling parameters.

Focus on the low pass rate and bottleneck of mass production in air film hole machining of aeroengine turbine blade, breakthrough in adaptive machining system, intelligent network control system, equipment network data interface, quick-change tooling and other technologies, based on the lean “U-shaped” layout, an electric discharge machining digital production line for turbine blade air film hole machining was built, which has characteristics of automation, digitalization, integration and intelligence. This line can realize“ 24 h unmanned production” and multi-model collinear mass production. After 2 years of operation, various economic indicators such as the one-time inspection pass rate and the comprehensive efficiency of equipment have reached the leading level in China, which has significantly improved the productivity and pass rate, reduced the cost of blade machining, and the bottleneck of mass production of aero-engine turbine blade was solved. The composition and architecture, key technologies and design process of the digital production line for electric discharge machining are demonstrated, which has important reference value for the construction of the digital production line of the aero-engine manufacturing industry.

The automated three-dimensional warehouse is an important unit in the intelligent production line, which can realize the accurate query of real-time inventory information, and its usage efficiency is directly related to the production efficiency of the intelligent production line. To address the problem of arbitrary and unintelligent allocation of storage location in the intelligent production line, a digital twin-based storage location assignment (SLA) optimization method is proposed. Firstly, a multi-dimensional modeling method of data-driven digital twin fusion is used to build a multi-dimensional model of the digital twin of the automated warehouse. Secondly, the communication mechanism and information interaction principle of the digital twin system of the automated warehouse are studied and analyzed. Then, an improved ant colony optimization (IACO) is proposed to optimize the model, and the obtained level information is integrated into the digital twin system of the automated warehouse and mapped to physical entities. Finally, it is proved through experiments that the method can meet the requirements of intelligent selection of cargo level for process-based material entry and exit in stereo warehouses, which is important for improving the intelligence of aerospace equipment production mode and increasing the productivity of intelligent production lines.

Compared with land aircraft and helicopter, amphibious aircraft has its unique advantages and wide application prospects. During the design, in order to ensure the normal use of amphibious aircraft under the water environment, it is necessary to carry out sufficient structural strength design according to the hydrodynamic load induced by the water movement so as to ensure the integrity of the structure. This paper mainly focuses on the development demand of amphibious aircraft, the research status and technical progress on the design and validation of aircraft hydrodynamic load at home and abroad. The researches of wedge model simulation, wave model simulation, water surface effect simulation, whole aircraft model simulation and scaled model test in the development of Chinese large amphibious aircraft are introduced, and the development trend of hydroelastic design for amphibious aircraft is also discussed.

Mg alloys have been widely used in aerospace and other fields because of its low density, light-weighting effects and abundant mineral resources. It has become a“ new green material of the 21st century”. However, Mg has strong electrochemical activity and is prone to corrosion, which has been limiting the wide application of magnesium alloys. At present, exploring the corrosion mechanism of Mg alloys and designing the composition of corrosion-resistant Mg alloys have attracted world-wide attention. This review discusses the research progress on the design of corrosion resistant of Mg alloys. It mainly describes the corrosion mechanism of Mg alloy and anomalous hydrogen reaction phenomenon, as well as the corrosion types such as galvanic corrosion, pitting corrosion, exfoliation corrosion and stress corrosion. And the effects of different alloying elements on the corrosion resistance of Mg alloy are summarized. Focuses on the application of firstprinciples, molecular dynamics, and X-CT technology in Mg alloy corrosion, which is expected to provide principles for the chemistry design of corrosion-resistant Mg alloys.

In order to improve the adaptability of scheduling strategy to the change of the arrival density of the workpiece, the dynamic scheduling method in flexible job-shop was studied. Firstly, the dynamic scheduling system of flexible manufacturing based on multi-agent system is constructed according to the investigation results and agent modeling method. And combining with the complex structure processing characteristics of flexible manufacture, the operation mechanism of scheduling task decomposition, machine tool selection and task allocation is improved, and forming the task decomposition mechanism based on the process, machine tool selection mechanism based on the machining accuracy and dynamic time windows scheduling method based on scheduling rules. Finally, the feasibility of the proposed dynamic scheduling method in the scenario of work-piece density change is verified by experiments, which has a certain guiding significance for the current actual flexible job-shop production activities.

As an advanced lightweight material, Al–Li alloy has relatively low density, high specific strength and stiffness and good fatigue properties. It is widely used in the field of aerospace. However, adhesion wear is easy to occur in the cutting of Al–Li alloy, which leads to a series of problems, such as poor machining quality and service performance. Therefore, domestic and foreign scholars have carried out relevant research on the machining of Al–Li alloy. This paper summarizes the research on the cutting experiments of Al–Li alloy in recent years, focuses on the research results of cutting force, cutting temperature, machined surface quality, tool wear and parameter optimization. The existing problems and future development direction are pointed out. It can promote the development of Al–Li alloy cutting technology.