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Design of modified model of intelligent assembly digital twins based on optical fiber sensor network 认领 引用 被引量：4
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作者 Zhichao Liu Jinhua Yang +1 位作者 Juan Wang Lin Yue 《Digital Communications and Networks》 SCIE CSCD 2024年第5期1542-1552,共11页
Intelligent assembly of large-scale,complex structures using an intelligent manufacturing platform represents the future development direction for industrial manufacturing.During large-scale structural assembly proces... Intelligent assembly of large-scale,complex structures using an intelligent manufacturing platform represents the future development direction for industrial manufacturing.During large-scale structural assembly processes,several bottleneck problems occur in the existing auxiliary assembly technology.First,the traditional LiDARbased assembly technology is often limited by the openness of the manufacturing environment,in which there are blind spots,and continuous online assembly adjustment thus cannot be realized.Second,for assembly of large structures,a single-station LiDAR system cannot achieve complete coverage,which means that a multi-station combination method must be used to acquire the complete three-dimensional data;many more data errors are caused by the transfer between stations than by the measurement accuracy of a single station,which means that the overall system's measurement and adjustment errors are increased greatly.Third,because of the large numbers of structural components contained in a large assembly,the accumulated errors may lead to assembly interference,but the LiDAR-assisted assembly process does not have a feedback perception capability,and thus assembly component loss can easily be caused when assembly interference occurs.Therefore,this paper proposes to combine an optical fiber sensor network with digital twin technology,which will allow the test data from the assembly entity state in the real world to be applied to the"twin"model in the virtual world and thus solve the problems with test openness and data transfer.The problem of station and perception feedback is also addressed and represents the main innovation of this work.The system uses an optical fiber sensor network as a flexible sensing medium to monitor the strain field distribution within a complex area in real time,and then completes real-time parameter adjustment of the virtual assembly based on the distributed data.Complex areas include areas that are laser-unreachable,areas with complex contact surfaces,and areas with large-scale bending deformations.An assembly condition monitoring system is designed based on the optical fiber sensor network,and an assembly condition monitoring algorithm based on multiple physical quantities is proposed.The feasibility of use of the optical fiber sensor network as the real-state parameter acquisition module for the digital twin intelligent assembly system is discussed.The offset of any position in the test area is calculated using the convolutional neural network of a residual module to provide the compensation parameters required for the virtual model of the assembly structure.In the model optimization parameter module,a correction data table is obtained through iterative learning of the algorithm to realize state prediction from the test data.The experiment simulates a largescale structure assembly process,and performs virtual and real mapping for a variety of situations with different assembly errors to enable correction of the digital twin data stream for the assembly process through the optical fiber sensor network.In the plane strain field calibration experiment,the maximum error among the test values for this system is 0.032 mm,and the average error is 0.014 mm.The results show that use of visual calibration can correct the test error to within a very small range.This result is equally applicable to gradient curvature surfaces and freeform surfaces.Statistics show that the average measurement accuracy error for regular surfaces is better than 11.2%,and the average measurement accuracy error for irregular surfaces is better than 14.8%.During simulation of large-scale structure assembly experiments,the average position deviation accuracy is 0.043 mm,which is in line with the designed accuracy. 展开更多
关键词 Digital twins Intelligent manufacturing Intelligent assembly Optical fiber sensor network Assembly condition monitoring algorithm
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Intelligent Assembly Planning System Based on Knowledge 认领 引用
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作者 ZHANG Degao ZHANG Hongxu +2 位作者 CHEN Haifeng LI Yuxi AN Hongwu 《外文科技期刊数据库（文摘版）工程技术》 2021年第3期312-316,共5页
Based on the problems of complex assembly process route, low resource utilization, low assembly efficiency and low quality in the production process of assembly workshop, a knowledge-based intelligent assembly worksho... Based on the problems of complex assembly process route, low resource utilization, low assembly efficiency and low quality in the production process of assembly workshop, a knowledge-based intelligent assembly workshop management and control mode is proposed. By constructing an intelligent assembly workshop with real assembly workshop, knowledge assembly workshop and assembly workshop management and control system working together, On the basis of realizing real-time information collection of resource location information, assembly process information and assembly quality information, Euclidean distance algorithm, Markov method and Manhattan distance algorithm are used to realize resource optimization scheduling, assembly process and quality control. 展开更多
关键词 knowledge intelligent assembly workshop assembly process control assembly quality control
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Research on Intelligent Assembly System Based on Man-machine Integration 认领 引用
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作者 LI Yuxi YIN Wenbin +2 位作者 ZHANG Degao SHEN Zilong DONG Jingchun 《外文科技期刊数据库（文摘版）工程技术》 2021年第2期400-402,共3页
Product assembly occupies an extremely important position in the whole production process of products. At present, due to the growing demand of consumers for personalized and customized products, the traditional manua... Product assembly occupies an extremely important position in the whole production process of products. At present, due to the growing demand of consumers for personalized and customized products, the traditional manual assembly method is inefficient, and pure automatic assembly is difficult and costly, which is difficult to meet the production needs of enterprises. Therefore, the intelligent assembly system of human-computer integration arises at the historic moment and realizes high-quality and high-efficiency product assembly. 展开更多
关键词 intelligent assembly system man-machine integration
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Modular scaffolds with intelligent visual guidance system for in situ bone tissue repair 认领 引用 被引量：2
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作者 Huifeng Shao Pengcheng Xia +8 位作者 Tao Zhang Jinyuan Shi Zhiqiang Huang Xianqi Yuan Zhiheng Nian Xiao Zhao Rougang Zhou Youping Gong Yong He 《International Journal of Extreme Manufacturing》 SCIE EI CAS CSCD 2025年第2期706-721,共16页
In clinical practice,the irregular shapes of traumas pose a significant challenge in rapidly manufacturing personalized scaffolds.To address these challenges,inspired by LEGO■ bricks,this study proposed a novel conce... In clinical practice,the irregular shapes of traumas pose a significant challenge in rapidly manufacturing personalized scaffolds.To address these challenges,inspired by LEGO■ bricks,this study proposed a novel concept of modular scaffolds and developed an innovative system based on machine vision for their rapid and intelligent assembly tailored to defect shapes.Trapezoidal interfaces effectively connect standardized bone units based on magnesium-doped silicate calcium,ensuring high stability of the modular scaffolds,with compressive strength up to 135 MPa and bending strength up to 17 MPa.Through self-developed defect recognition and reconstruction algorithms,defect recognition and personalized assembly schemes for bone scaffolds can be achieved autonomously.Modular scaffolds seamlessly integrate with surrounding bone tissue,promoting new bone growth,with no apparent differences compared to fully 3D printed integral scaffolds in the skull and femur repair experiments.In summary,the adoption of modular scaffolds not only integrates personalization and standardization but also satisfies the optimal treatment window. 展开更多
关键词 3D printing modular scaffolds rapidly manufacturing intelligent assembly traumas repair
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Data-Driven Co-Optimization of Blade Selection and Sequencing for Aeroengine Rotors under Industrial Assembly Constraints 认领 引用 被引量：1
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作者 Chunyu Shao Haixu Yu +6 位作者 Like Zhang Quanyi Ge Bobo Fang Ruirui Li Chuanzhi Sun Yongmeng Liu Jiubin Tan 《Instrumentation》 2025年第4期1-14,共14页
During the rotor assembly of aeroengines,the combined effect of blade mass moment variations and fixed tenon slot constraints makes single-phase rotor unbalance optimization strategies insufficient for real-world indu... During the rotor assembly of aeroengines,the combined effect of blade mass moment variations and fixed tenon slot constraints makes single-phase rotor unbalance optimization strategies insufficient for real-world industrial assembly scenarios.This often leads to excessive residual unbalance after assembly,resulting in engine vibrations and compromised operational stability.To address the lack of blade selection strategies and low qualification rates due to tenon slot constraints in industrial settings,this paper proposes a co-optimization method for blade selection and sequencing under industrial assembly constraints.A two-stage data-driven optimization framework is developed.In the first stage,a Dynamic Replacement Roulette Selection(DRWS)algorithm is introduced for global multi-set blade selection,improving blade utilization and avoiding selection failure caused by excessive moment dispersion.In the second stage,under fixed tenon slot constraints,blade sequencing is optimized using a Constrained Adaptive Genetic Algorithm(CAGA),effectively suppressing residual unbalance.Experimental results demonstrate that the proposed method achieves a blade utilization rate of 92.4%on 145 samples,with well-balanced group sets.Under tenon slot constraints,the residual unbalance is reduced from 58 g·mm and 94 g·mm(random assembly)to 7 g·mm and 10 g·mm,respectively.This study offers a novel solution and technical support for improving assembly precision and enabling intelligent decision-making in aeroengine rotor assembly lines. 展开更多
关键词 aircraft engine rotor intelligent assembly blade selection optimization data-driven optimization residual unbalance control
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Intelligent sorting method for assembly line based on visual positioning and robotic arm model predictive control 认领 引用
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作者 Ruining Zhang Wei Lu +1 位作者 Xingliang Jian Hui Luo 《International Journal of Agricultural and Biological Engineering》 SCIE 2023年第4期206-214,共9页
The existing steering device in the fruit and vegetable packaging assembly line cannot adjust the attitude of lettuce to a unified attitude,affecting the input and packaging process of the packaging machine.This study... The existing steering device in the fruit and vegetable packaging assembly line cannot adjust the attitude of lettuce to a unified attitude,affecting the input and packaging process of the packaging machine.This study proposes an intelligent assembly line sorting method based on the visual positioning and model predictive control of a robotic arm.First,lightweight improvement based on the YOLOv5 is realized,the lettuce stalk in the background of the conveyor belt is promptly identified,the image of the lettuce stalk in the anchor box area is processed,and the edge contour point set is determined to extract the pixel coordinates of the optimal grasp point and mirror inclination angle of the lettuce.For the intelligent assembly line system,a robot arm kinematics model is constructed and the robot kinematics inverse solutions are calculated.Additionally,the lettuce movement speeds are dynamically measured by the vision system.A combination of the model prediction control,dynamic tracking,and rapid sorting of the lettuce by the robot claw is realized.The results show that the average detection time of a single frame image in the visual positioning part is 0.014 s,which is reduced by 50%;the accuracy and recall are 98%and 95%,respectively.The detection time is significantly reduced by ensuring accuracy.Within the current speed range of the packaging assembly line conveyor belt,the manipulator can grasp lettuce at different speeds stably and fast;the average axial error,average radial error,and adjusted average inclination angle error are 0.71 cm,1.02 cm,and 3.79°,respectively,verifying the high efficiency and stability of the model.The proposed method of this study enables application in the intelligent sorting operation of industrial assembly lines. 展开更多
关键词 YOLOv5 deep learning image recognition model predictive control intelligent assembly line
Data fusion and simulation-based planning and control in cyber physical system for digital assembly of aeroplane 认领 引用
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作者 Hui Li Linxuan Zhang +1 位作者 Tianyuan Xiao Jietao Dong 《International Journal of Modeling, Simulation, and Scientific Computing》 EI 2015年第3期66-84,共19页
This paper introduces a CPS application for intelligent aeroplane assembly.At first,the CPS structure is presented,which acquires the characteristics of general CPS and enables“simulation-based planning and control”... This paper introduces a CPS application for intelligent aeroplane assembly.At first,the CPS structure is presented,which acquires the characteristics of general CPS and enables“simulation-based planning and control”to achieve high level intelligent assembly.Then the paper puts forward data fusion estimation algorithm under synchronous and asynchronous sampling,respectively.The experiment shows that global optimal distributed fusion estimation under synchronized sampling proves to be closer to the actual value compared with ordinary weighted estimation,and multi-scale distributed fusion estimation algorithm of wavelet under asynchronous sampling does not need time registration,it can also directly link to data,and the error is smaller.This paper presents hybrid control strategy under the circumstance of joint action of the inner and outer loop to address the problems caused by the less controllable feature of the parallel mechanism when undertaking online process simulation and control.A robust adaptive sliding mode controller is designed based on disturbance observer to restrain inner interference and maintain robustness.At the same time,an outer collaborative trajectory planning is also designed.All the experiment results show the feasibility of above proposed methods. 展开更多
关键词 Intelligent aeroplane assembly cyber physical system multi-sensor data fusion simulation-based control disturbance observer robust adaptive sliding mode controller
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