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2021 Vol. 64, No. 5
Published: 2021-03-01
FEATURE
FORUM
RESEARCH
C0NTENTS
COVER STORY
APPROACHING SCIENCE
 
       FEATURE
14 Research on Strengthening Mechanism of Aluminum Alloy Pipe for Aero-Engine Weight-Reduction
QU Ligang, JING Qiyu, LI Ming, YANG Yingduo
DOI: 10.16080/j.issn1671-833x.2021.05.014
In order to promote the effective improvement of thrust-to-weight ratio of new generation of large aeroengines, the research on autofrettage mechanism of high-strength aluminum alloy pipe fittings for aero-engine weightreduction requirements was carried out. It is a feasible way to reduce the weight of aero-engines that using effectively strengthened high-strength aluminum alloy pipe fittings to replace stainless steel high-pressure pipe fittings in the low temperature section of aero-engine on a large scale. To obtain the mathematical model of the high-pressure autofrettage process of aviation pipeline，the strengthening mechanism of high-pressure pipeline autofrettage process was researched and Bauschinger effect, strain aging and strain hardening based on the triple shear unified failure criterion were considered. The bilinear kinematic hardening model was used to analyze the elasto-plastic behavior of the pipeline during the hardening process and the evolution of the residual stress distribution. Based on ANSYS, the fatigue strength of reinforced aluminum alloy pipe and stainless steel fittings were simulated and analyzed under rated conditions. Finally, pulse fatigue experiments were done to verify that it is feasible to replace existing stainless steel fittings with strengthened aluminum alloy pipe fittings.
2021 Vol. 64 (5): 14-23 [Abstract] ( 70 ) HTMLNew PDF (11923 KB)  ( 55 )
       COVER STORY
24 Nondestructive Characterization of Titanium Alloy Lattice Materials Prepared by Laser Selective Melting
LIU Xiaotong,WANG Bingyang,DAI Ning,WU Liming,WANG Jingzhao,HU Quandong,LI Huaixue
DOI: 10.16080/j.issn1671-833x.2021.05.024
The titanium alloy lattice with BCC and DOD structure is prepared by laser selective melting. Micro– CT is used to scan and 3D reconstruct the titanium alloy lattice materials with these two kinds of structures. Clear internal structure can be seen in these lattices and a few round and oval defects can be found. BCC and DOD cells are arranged neatly and periodically with no slag, collapse or rod bending. Through comparison of CATIA model and 3D reconstruction data of lattice structures, it is found that the alloy lattice is bended. In addition, the surface roughness of BCC and DOD metal lattices is measured and calculated using confocal microscope based on Micro–CT image. The results show that Micro–CT has significant application value in the characterization of the internal structure, defects, preparation errors and roughness testing of titanium alloy lattice materials.
2021 Vol. 64 (5): 24-29 [Abstract] ( 104 ) HTMLNew PDF (4109 KB)  ( 251 )
       FORUM
32 Application of Mobile Industrial Robot in Aircraft Assembly Production Line
TAO Yong, GAO He,WANG Tianmiao,JIANG Shan,REN Fan,WEN Yufang
DOI: 10.16080/j.issn1671-833x.2021.05.032
This paper summarizes the typical applications of mobile industrial robots in aviation manufacturing scenarios such as aircraft assembly lines. It focuses on the analysis of key technologies such as multi-sensor fusion SLAM, navigation control of mobile robots, precision control of robot arms and digital measurement. The development trends such as human-robot collaboration, multi-sensor information fusion, planning decision, and digital twin system for mobile robots in aviation manufacturing field are described.
2021 Vol. 64 (5): 32-41/67 [Abstract] ( 105 ) HTMLNew PDF (19622 KB)  ( 135 )
42 Adaptive Robot Scheduling Using SP–MCTS for Industrial Internet of ThingsEnabled Hybrid Flow Shop
GUO Jian，SHI Yaoyao，HU Hao,CHEN Zhen，ZHANG Junfeng,ZHAO Pan
DOI: 10.16080/j.issn1671-833x.2021.05.042
With the deep integration of industrial internet of things (IIoT) and artificial intelligence (AI) technology, automated guided vehicles (AGVs) and mobile robots have been widely used in internet of things-enabled floor shop. In view of many complex factors such as real-time dynamic changes and uncertain conditions in the workshop, the SP– MCTS (Single-player Monte-Carlo tree search algorithm) method with each job group as a subtree and real-time state as the root node is proposed to implement adaptive scheduling of workshop. The problem of robot scheduling is formulated as a Markov decision process (MDP) in which state representation, action representation, reward function, and optimal policy, are described in detail. In the real-time scheduling process, the proposed search method establishes a subtree for each job group, and only the state relationship between two adjacent groups is considered in optimization, thereby the calculation difficulty is simplified. In the subtree search process, SP–MCTS is used to search with the real-time state as the root node. At the same time, the expansion method and the pruning method are used to carry out strategy exploration and information accumulation respectively. Therefore, the deeper the real-time status node in the subtree, the faster and more accurate the optimal strategy is obtained. The case study based on a real-world shop is proven and the results validate the effectiveness and superiority of the proposed approach.
2021 Vol. 64 (5): 42-51 [Abstract] ( 65 ) HTMLNew PDF (4107 KB)  ( 186 )
52 Research on Optimization Algorithm of Robot Load Gravity Compensation Based on Genetic Algorithm
LI Gen, LI Pengcheng, WU Chao, SHEN Ye
DOI: 10.16080/j.issn1671-833x.2021.05.052
In the field of aeronautical and astronautical assembly, the six–dimensional force sensors installed on the end of robot is commonly used to derive external forces, which is one of the key technologies to realize the compliance control of industrial robots, but the presence of loads will interfere the perception of external forces. To compensate the gravity of end load of industrial robots, a genetic algorithm-based gravity compensation optimization algorithm is proposed. Based on the least squared method, this method considers the influence of force sensor installation deflection angle on compensation effect, and an optimal solution model is established with the objective of minimizing the sum of squared error, by using genetic algorithm. As a result, the installation deflection angle of force sensor can be estimated without use of measuring instruments, and the accuracy of gravity compensation can be improved. In the meantime, the system errors are reduced effectively by designing specific robot measuring attitude. The experiments show that arbitrary angles of the installation deflection angle can be compensated by optimization algorithm. Compared with before compensation, maximum gravity compensation errors in each direction and average gravity compensation errors are both generally reduced.
2021 Vol. 64 (5): 52-59 [Abstract] ( 93 ) HTMLNew PDF (2341 KB)  ( 145 )
60 Design and Research of Aircraft Landing Gear Omni-Directional Mobile Assembly Robot
XU Bo1, 2, ZHAO Chaoze1, 2, ZHANG Yumei1, 2, YAN Dong1, 2, GONG Bo1, 2, PANG Xuefeng1, 2
DOI: 10.16080/j.issn1671-833x.2021.05.060
As an important part supporting the weight of aircraft and absorbing the impact energy, landing gear is faced with the special requirements of narrow assembly space and high assembly precision in the process of assembly and test. Therefore, it is urgent to develop a flexible assembly platform with movable and multi-degree of freedom adjustment functions. Through analysis of gear assembly requirements, the 6-DOF assembly robot was designed based on Mecanum wheel omni-directional mobile and 3–RPS parallel mechanism. The structure and control method were introduced in detail. By analyzing robot kinematics characteristics, a kinematics model was obtained, and the kinematic parameters and accuracy are analyzed. Finally, through the landing gear assembly test, the function and performance of the robot can meet the operational requirements.
2021 Vol. 64 (5): 60-67 [Abstract] ( 73 ) HTMLNew PDF (2548 KB)  ( 225 )
       APPROACHING SCIENCE
68 Aligning With the National Major Project Needs and Keeping up With International Aviation Science and Technology Frontier
2021 Vol. 64 (5): 68-69 [Abstract] ( 64 ) HTMLNew PDF (386 KB)  ( 48 )
       RESEARCH
70 Research Progress of Liquid Molding Resin Matrix Composites and Its Technology
JIANG Shicai,BAO Jianwen, ZHANG Lianwang, LI Weidong, AN Xuefeng
DOI: 10.16080/j.issn1671-833x.2021.05.070
This paper introduces the main categories and characteristics of LCM composites, and discusses the progress of LCM resin, tackifier for LCM resin and preparation process of LCM preform in China and abroad. Some new processes of LCM, such as HP-RTM process, thermoplastic resin liquid molding process, automatic laying liquid forming process and SQRTM forming process are introduced. And the future development trends of LCM are prospected.
2021 Vol. 64 (5): 70-81/102 [Abstract] ( 166 ) HTMLNew PDF (8171 KB)  ( 132 )
82 Simulation Based Planning and Optimization of Aircraft Tube Automation Production Line
ZHANG Xiwen,L Ruiqiang,BU Yong,ZHENG Luhan,LI Guangjun,CAO Jindou
DOI: 10.16080/j.issn1671-833x.2021.05.082
The aviation product processing line is developing in direction of automation, digitization and intellectualization. The automatic production line puts forward more strict requirements on workshop layout, logistics and production rhythm. The planning and simulation of production line can reflect the possible problems in the process directly and accurately, and solve and optimize these problems through scientific methods. The planning and simulation technology of production line is introduced in this paper. The production process, process layout and logistics scheme of a certain aircraft tube automatic production line are planned, and the running state of the tube production line is simulated using DELMIA/Quest software. Key factors such as the bottlenecks of production line, production capacity and equipment utilization are analyzed, and the improvement plan of production line layout and process route is proposed. The simulation results of different production organization modes are compared, and suggestions on the production line scheduling are given.
2021 Vol. 64 (5): 82-88 [Abstract] ( 67 ) HTMLNew PDF (1201 KB)  ( 152 )
89 Development and Application of Intelligent Mistake Proofing Auxiliary Manual Operating System
LIU Nuoshi, ZOU Fang, HE Zhaoyan, MU Xinwei
DOI: 10.16080/j.issn1671-833x.2021.05.089
In order to solve the problems of operation error, low efficiency, high cost of training and unstable quality in manual assembly in aviation manufacturing, an auxiliary manual operation system was developed. The system assists the personnel to assemble workpiece by means of projection indication, motion sensing camera, touch display and so on. Meanwhile, the intelligent mistake proofing design is carried out for operation guidance, part selection, screw tightening and other problems that are prone to occur. Through an airborne electromechanical product manual assembly engineering application, the auxiliary guidance and monitoring of assembly process are realized, and the quality and efficiency of manual assembly are also improved.
2021 Vol. 64 (5): 89-97 [Abstract] ( 53 ) HTMLNew PDF (5392 KB)  ( 260 )
98 Period Prediction of Autoclave Curing Based on Data Mining Algorithm
WEI Shipeng, WANG Ning, YUAN Zhe
DOI: 10.16080/j.issn1671-833x.2021.05.098
At present, the planners can only arrange autoclave continuously according to the curing parameters of relevant process documents and historical data of the curing period, causing planners failure to make a detailed production scheduling plan. Now, data mining algorithm hasn’t been used to predict the curing period of autoclave. To solve the curing time of the autoclave, support vector regression（SVA） method and K–nearest neighbor （KNN） method are used to calculate. The proposed SVR and KNN comparative experiments are performed. Experimental results show that 90% of KNN prediction result is better than support vector regression prediction method, and 90% of the error is less than 0.5 hours. Meanwhile, the reasons for the prediction results of two methods are analyzed.
2021 Vol. 64 (5): 98-102 [Abstract] ( 69 ) HTMLNew PDF (990 KB)  ( 121 )
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