航空复合材料自动铺丝工艺缺陷检测、表征与工艺优化研究进展

doi:10.7527/S1000-6893.2025.32433

Abstract

Abstract:

As an important method for efficient manufacturing of advanced composites， Automated Fiber Placement （AFP） technology has exhibited significant advantages in the production of large and complex curved structures in the aerospace field. However， due to the limitations in equipment precision， material characteristics， and structural complexity， various types of layup defects are prone to occur during the AFP process， which severely affect the structural performance and service reliability. Accordingly， research on key technologies such as defect detection， characterization， and process optimization has become essential for improving AFP manufacturing quality. This study briefly discusses the foundational research pertaining to typical defects in the AFP processes. Current research progress in defect detection， characterization， and process parameter optimization in AFP technology is systematically reviewed. Existing limitations in detection， characterization， and process optimization methods for AFP defects are summarized， along with future research directions. Based on the findings of the relevant research， a closed-loop technical framework for composite manufacturing quality control is proposed， providing a systematic reference for achieving high-quality， high-reliability， and high-intelligent AFP manufacturing of composites.

Key words: continuous fiber reinforced composites, automated fiber placement, defect detection, defect characterization, process optimization

CLC Number:

V214.8

Runbo MA, Junming ZHANG, Yingjie XU, Wenzhi WANG. Review on defect detection, characterization and process optimization in automated fiber placement of aviation composite[J]. Acta Aeronautica et Astronautica Sinica, 2026, 47(7): 432433.

Figures/Tables 15

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Table 1

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Table 2

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Table 3

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Table 4

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Table 5

Optimization methods and technical characteristics of key process parameters

工艺参数类型	优化方法类型	关键技术特征	适用场景	文献
铺放速度	经验参数设定法	通过人工试验确定经验范围	平面/低曲率结构	［113-114］
	响应面法	统计设计多因素交互作用	典型平面结构	［115］
	响应面与多尺度协同优化组合法	集成响应面与多尺度模型，构建复杂目标函数	高性能曲面结构	［11，116］
铺放压力	经验参数设定法	通过人工试验确定经验范围	平面/低曲率结构	［113］
	压辊结构优化法	采用多自由度结构设计/结合压敏薄膜试验与仿真，迭代改进压辊设计参数	大曲率/异形曲面结构	［106，120-122］
	传感器实时反馈控制法	利用轮廓测量或触感传感器实现压力实时检测与闭环调节	平/曲面结构	［119］
	伺服控制与智能算法调压法	结合慢时变递归识别算法与自整定PID 实现实时闭环调压	多曲率变化结构	［123］
	多源误差建模与机器人姿态优化法	构建误差模型，结合虚拟目标点进行姿态控制	大曲率/异形曲面结构	［124］
铺放温度	经验参数设定法	通过人工试验确定经验范围	平面/低曲率结构	［28，113，125-126］
	响应面法	统计设计多因素交互作用	典型平面结构	［127，132］
	数据驱动法	FNN/TgNN预测温度场分布，实时在线控制	多曲率变化结构	［128-130］
	加热器角度控制法	利用可编程逻辑控制器控制激光加热器角度，实现能量精确分布	热塑性复合材料结构/ 大曲率曲面结构	［131］
丝束张力	经验参数设定法	通过人工试验确定经验范围	平面/低曲率结构	［113］
	理论模型法	建立张力动态变化模型	平面/低曲率结构	［136］
	模糊自适应PID控制法	融合模糊逻辑与自适应PID，实现张力实时控制	多曲率变化结构	［137］

Table 5

Fig.9

Table 6

Classification and comparative analysis of AFP path optimization methods

优化方法类别	方法描述	优势	局限性	适用场景	文献
几何优化方程类	STL模型文件重构优化数学模型	自动化程度高，人为干预少	曲面适应性差，路径精度有限	规则结构、定角度铺放	［140-141］
几何优化方程类	曲面方程与微分几何	避免褶皱和重叠，拓展设计空间	适应性差，计算复杂	压力容器、穹顶类结构	［142］
自适应与多参考路径类	分区域多参考路径设计	适应性强，适合多层铺放	适应性差	中低曲率结构	［143-145］
	网格动态表示与自适应算法	高度自适应，路径等距、纤维方向一致	实施复杂，计算量大	大曲率曲面结构	［146］
	网格划分与多参考线方向向量优化	路径规划效率高，适应性强	精度受限于网格划分质量	连续曲面大型结构	［150］
	自动预分析与遗传算法优化	误差小，褶皱少	算法参数依赖性强，耗时长	变刚度曲面结构	［148］
智能优化算法类	基于路径离散误差分解的优化	离散点少，精度高	高精度算法依赖性强	双曲面结构	［149］
	基于高斯过程回归的贝叶斯优化	缺陷率低，适用于多种缺陷优化	初始采样与模型训练依赖性强	双曲面结构	［150］
	基于数字图像反卷积算法	全局优化，考虑纤维对齐度和厚度一致性	高质量网格化建模依赖性强	高复杂度曲面结构	［151］
	基于点云结构的定向投影算子算法	精度高，通用性强，避免表面重构误差	点云质量要求高	非参数化、自由曲面结构	［152］
其他优化技术类	快速局部曲率校正	误差小，厚度均匀	曲率控制精度高，计算量大	变刚度结构	［153-154］
	基于纤维方向聚类与 B样条拟合	保留有限元最优设计信息，路径平滑且制造约束友好	聚类划分依赖参数选择	变刚度结构	［155］
	主从控制系统视觉测量与轨迹补偿	定位精度高，稳定性好	硬件复杂，需高精度协同	复杂曲面结构	［156-159］

Table 6

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缺陷类型	形成机理	文献
间隙/重叠	轨迹控制精度不足，导致丝束重新送入路径时与预设位置不一致，产生位置偏差	［25-26，28］
缺丝	张力过大或压辊压力不足，造成丝束贴合度差，易脱落或无法正常铺放	［22，29］
扭转	丝束制造或导入过程控制不当，导向阻塞或设备振动引起轴向扭转	［17，29］
褶皱	轨迹曲率大或路径控制精度低，铺放头运行抖动导致丝束折叠变形	［17］
桥接	凹面铺放中张力与压力控制不协调，导致丝束抬起，无法紧贴模具表面	［9，17，22］
异物	丝束边缘摩擦生成绒毛堆积或生产环境中混入杂质，附着于铺层表面	［22，30-31］
纤维波纹	多种缺陷积累引起贫/富树脂区，纤维排列错位，形成局部起伏的厚度不均	［17，29］

方法类别	检测方法	优势	局限性	文献
基于点云分析和图像分割的方法	结构光点云分析与PointNet++	精度高，实时性强，成本低	点云数据量大，算力要求高	［88］
	SiamMask图像分割	精度高，处理速度快	对图像清晰度与角度敏感	［45］
	图像滤波与自适应阈值	抗干扰能力强，适应复杂纹理	通用性较弱	［94］
基于物理特性的方法	电阻变化检测	原位检测，适合层间缺陷监测	依赖电导率数据库，设备需频繁校准	［95］
基于红外热成像与时空数据的方法	空间-时间热成像重建	精度高，抗热扩散影响	依赖热像仪性能，速度受帧率影响	［96］
基于红外热成像与时空数据的方法	综合热成像框架	多功能集成，定量分析能力强	对设备帧率与空间分辨率依赖强	［97-98］
基于深度学习目标检测的方法	改进YOLOv7（BiFormer+AFPN）	精度高，识别小缺陷能力强	模型复杂，部署成本高	［99］
	改进YOLOv5与空间金字塔扩张卷积	运行快，多尺度适应性强	数据集依赖高，剪枝敏感	［100］
	深度学习网络SMSDDNet	精度高，适应复杂目标形态	网络结构复杂，算力要求高	［102］

表征方法	关键技术特征	优势	局限性	文献
X射线计算机断层扫描	无损三维成像，孔隙定量可视	分辨率高，三维结构信息完整	穿透深度有限，热塑性复材存在盲区	［104-105］
中子成像技术	中子对孔隙敏感，穿透性强	穿透深、对轻质缺陷识别能力强	成本高，设备少，分辨率较低	［106］
超声无损检测	脉冲回波与衰减分析	非接触，成本低，识别效率高	空间分辨率低，易误判	［107-108］
点云数据三维建模	分层点云重构真实间隙缺陷形貌	可用于有限元仿真	点云噪声大，建模流程复杂	［109］
CASF三维几何重建	基于铺放压实行为与几何轨迹重建缺陷形貌	缺陷形貌真实、预测性能准确	未考虑树脂流动，建模复杂，对厚度依赖大	［110］
显微XCT自动建模	高分辨显微CT图像和分层网格自动生成	建模精度高，适用于中尺度仿真	计算量大，耗时长	［111］

Review on defect detection, characterization and process optimization in automated fiber placement of aviation composite

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