An optimization method was presented for cold stretch forming of titanium-alloy aircraft skin to determine process parameters and to reduce springback.In the optimization model,a mathematical formulation of stress dif...An optimization method was presented for cold stretch forming of titanium-alloy aircraft skin to determine process parameters and to reduce springback.In the optimization model,a mathematical formulation of stress difference was developed as an indicator of the degree of springback instead of implicit springback analysis.Explicit finite element method(FEM)was used to analyze the forming process and to provide the stress distribution for calculating the amount of the stress indicator.In addition,multi-island genetic algorithm(MGA)was employed to seek the optimal loading condition.A case study was performed to demonstrate the potential of the suggested method.The results show that the optimization design of process parameters effectively reduces the amount of springback and improves the part shape accuracy.It provides a guideline for controlling springback in stretch forming of aircraft skin.展开更多
A process design approach for multi-stage stretch forming was proposed by combining the strain distribution method and finite element method(FEM)to determine the minimum stage number and deformation amount of each sta...A process design approach for multi-stage stretch forming was proposed by combining the strain distribution method and finite element method(FEM)to determine the minimum stage number and deformation amount of each stage.The strain distribution method was used to calculate the deformation amount of each stage and evaluate the formability through a safety criterion.FE simulation was taken as an analysis tool to reveal the deformation behaviour,to predict the strain contour and to determine the process parameters at each stage.To evaluate the effect of heat treatment after pre-strain on occurrence of deformation defects during the subsequent deformation,a multi-stage uniaxial tension test for 2B06 aluminium alloy sheet was carried out.A case study demonstrates that the approach has high reliability and good practicability.展开更多
Weight penalty has been a challenge for design engineers of aerospace vehicles.Today’s high-efficiency combat aircraft undergoes intense stress and strain during flying missions,which require stronger and stiffer mat...Weight penalty has been a challenge for design engineers of aerospace vehicles.Today’s high-efficiency combat aircraft undergoes intense stress and strain during flying missions,which require stronger and stiffer materials to retain structural integrity.Though metallic materials have been successfully used for the construction of aircraft structures and components,metals still have a low strength-to-weight ratio.This paper aims to develop an alternate optimised material selection methodology to replace the metallic skin of a medium-sized military aircraft.The search for the optimum material will result in reduced aircraft weight which will be benefitted by extra payload on the aircraft.The selection methodology is comprised of finding design pressure limits on the aircraft skin,and comparison of properties(strength,elastic modulus,shear modulus,etc.)and performance(safety factor,deflection,and stress)of the existing metallic skin with alternate optimised material.The comparison was made under aerodynamic pressure,bending force,and twisting moment.Carbon Fibre Reinforced Polymer/Epoxy(CFRP)Uni-Directional(UD)prepreg(elastic modolus is 209 GPa)was selected as an alternate optimum material to replace the aluminium alloy skin of the aircraft studied.The selected alternate optimum material resulted in the reduction of aircraft skin weight by 30%.展开更多
Skin defect inspection is one of the most significant tasks in the conventional process of aircraft inspection.This paper proposes a vision-based method of pixel-level defect detection,which is based on the Mask Scori...Skin defect inspection is one of the most significant tasks in the conventional process of aircraft inspection.This paper proposes a vision-based method of pixel-level defect detection,which is based on the Mask Scoring R-CNN.First,an attention mechanism and a feature fusion module are introduced,to improve feature representation.Second,a new classifier head—consisting of four convolutional layers and a fully connected layer—is proposed,to reduce the influence of information around the area of the defect.Third,to evaluate the proposed method,a dataset of aircraft skin defects was constructed,containing 276 images with a resolution of 960×720 pixels.Experimental results show that the proposed classifier head improves the detection and segmentation accuracy,for aircraft skin defect inspection,more effectively than the attention mechanism and feature fusion module.Compared with the Mask R-CNN and Mask Scoring R-CNN,the proposed method increased the segmentation precision by approximately 21%and 19.59%,respectively.These results demonstrate that the proposed method performs favorably against the other two methods of pixellevel aircraft skin defect detection.展开更多
为提高蒙皮损伤检测的自动化程度,提出一种基于改进YOLOv7通道冗余的机器视觉检测方法。首先针对飞机蒙皮损伤数据集背景单一的特点,提出增强型颈部特征融合改进算法,提高了飞机蒙皮损伤的识别精度和检测速度;其次针对主干特征提取网络...为提高蒙皮损伤检测的自动化程度,提出一种基于改进YOLOv7通道冗余的机器视觉检测方法。首先针对飞机蒙皮损伤数据集背景单一的特点,提出增强型颈部特征融合改进算法,提高了飞机蒙皮损伤的识别精度和检测速度;其次针对主干特征提取网络的卷积通道冗余的问题,引入部分卷积PConv(Partial convolution),提出主干特征提取网络轻量化,减少模型的参数量,同时提高损伤的识别效率。试验部分首先在飞机蒙皮损伤数据集上探索了不同增强型颈部特征融合改进算法,确定了最优的改进方案;接着在飞机蒙皮损伤数据集上做消融和对比试验,改进算法与原YOLOv7算法比较,mAP(Mean average precision)提升了2.3%,FPS(Frames per second)提升了22.1 f/s,模型参数量降低了34.13%;最后将改进的YOLOv7模型与主流目标检测模型对比,证明了改进算法的先进性。展开更多
基金Project(50905008)supported by the National Natural Science Foundation of ChinaProject(2007AA041905)supported by the National High-tech Research and Development Program of ChinaProject(YWF-10-01-B08)supported by the Fundamental Research Funds for the Central Universities,China
文摘An optimization method was presented for cold stretch forming of titanium-alloy aircraft skin to determine process parameters and to reduce springback.In the optimization model,a mathematical formulation of stress difference was developed as an indicator of the degree of springback instead of implicit springback analysis.Explicit finite element method(FEM)was used to analyze the forming process and to provide the stress distribution for calculating the amount of the stress indicator.In addition,multi-island genetic algorithm(MGA)was employed to seek the optimal loading condition.A case study was performed to demonstrate the potential of the suggested method.The results show that the optimization design of process parameters effectively reduces the amount of springback and improves the part shape accuracy.It provides a guideline for controlling springback in stretch forming of aircraft skin.
基金Project(2006AA04Z143) supported by the National High-tech Research and Development Program of ChinaProject(2006BAF04B00) supported by the National Key Technologies R&D Program of ChinaProject(2007ZE51055) supported by the Aviation Science Foundation of China
文摘A process design approach for multi-stage stretch forming was proposed by combining the strain distribution method and finite element method(FEM)to determine the minimum stage number and deformation amount of each stage.The strain distribution method was used to calculate the deformation amount of each stage and evaluate the formability through a safety criterion.FE simulation was taken as an analysis tool to reveal the deformation behaviour,to predict the strain contour and to determine the process parameters at each stage.To evaluate the effect of heat treatment after pre-strain on occurrence of deformation defects during the subsequent deformation,a multi-stage uniaxial tension test for 2B06 aluminium alloy sheet was carried out.A case study demonstrates that the approach has high reliability and good practicability.
基金funding this work through the Large Groups Research Project(No.RGP.2/163/43).
文摘Weight penalty has been a challenge for design engineers of aerospace vehicles.Today’s high-efficiency combat aircraft undergoes intense stress and strain during flying missions,which require stronger and stiffer materials to retain structural integrity.Though metallic materials have been successfully used for the construction of aircraft structures and components,metals still have a low strength-to-weight ratio.This paper aims to develop an alternate optimised material selection methodology to replace the metallic skin of a medium-sized military aircraft.The search for the optimum material will result in reduced aircraft weight which will be benefitted by extra payload on the aircraft.The selection methodology is comprised of finding design pressure limits on the aircraft skin,and comparison of properties(strength,elastic modulus,shear modulus,etc.)and performance(safety factor,deflection,and stress)of the existing metallic skin with alternate optimised material.The comparison was made under aerodynamic pressure,bending force,and twisting moment.Carbon Fibre Reinforced Polymer/Epoxy(CFRP)Uni-Directional(UD)prepreg(elastic modolus is 209 GPa)was selected as an alternate optimum material to replace the aluminium alloy skin of the aircraft studied.The selected alternate optimum material resulted in the reduction of aircraft skin weight by 30%.
基金National Natural Science Foundation of China(Nos.U2033201 and U1633105)。
文摘Skin defect inspection is one of the most significant tasks in the conventional process of aircraft inspection.This paper proposes a vision-based method of pixel-level defect detection,which is based on the Mask Scoring R-CNN.First,an attention mechanism and a feature fusion module are introduced,to improve feature representation.Second,a new classifier head—consisting of four convolutional layers and a fully connected layer—is proposed,to reduce the influence of information around the area of the defect.Third,to evaluate the proposed method,a dataset of aircraft skin defects was constructed,containing 276 images with a resolution of 960×720 pixels.Experimental results show that the proposed classifier head improves the detection and segmentation accuracy,for aircraft skin defect inspection,more effectively than the attention mechanism and feature fusion module.Compared with the Mask R-CNN and Mask Scoring R-CNN,the proposed method increased the segmentation precision by approximately 21%and 19.59%,respectively.These results demonstrate that the proposed method performs favorably against the other two methods of pixellevel aircraft skin defect detection.
文摘为提高蒙皮损伤检测的自动化程度,提出一种基于改进YOLOv7通道冗余的机器视觉检测方法。首先针对飞机蒙皮损伤数据集背景单一的特点,提出增强型颈部特征融合改进算法,提高了飞机蒙皮损伤的识别精度和检测速度;其次针对主干特征提取网络的卷积通道冗余的问题,引入部分卷积PConv(Partial convolution),提出主干特征提取网络轻量化,减少模型的参数量,同时提高损伤的识别效率。试验部分首先在飞机蒙皮损伤数据集上探索了不同增强型颈部特征融合改进算法,确定了最优的改进方案;接着在飞机蒙皮损伤数据集上做消融和对比试验,改进算法与原YOLOv7算法比较,mAP(Mean average precision)提升了2.3%,FPS(Frames per second)提升了22.1 f/s,模型参数量降低了34.13%;最后将改进的YOLOv7模型与主流目标检测模型对比,证明了改进算法的先进性。
基金YANG Yuxin,WANG Xuexin,ZHANG Xu,YU Bing,LI Siwei,XIE Yi,YAN Xiaoyu(The First Scale Optical Metrology Station of the Science,Technology and Industry for National Defense,Xi'an Institute of Applied Optics,Xi'an 710065,China)。
