摘要
为了提高对微小空间碎片超高速撞击造成的复杂损伤红外检测准确度,本研究提出了一种基于虚拟目标向量的超高速撞击损伤缺陷红外检测和评估框架。该框架结合了多目标优化与红外特征提取,通过聚类多目标优化方法,针对不同类别缺陷提取红外特征。利用动态时间规整法提取典型瞬态热响应,并采用虚拟目标向量扩展权重向量集以提升Pareto前沿的估计精度。实验结果表明,该方法能够有效提高超高速撞击下的红外缺陷检测精度,为航天器的损伤评估提供了可靠依据。
This study proposes an infrared defect detection and evaluation framework for hypervelocity impacts based on virtual objective vectors.The framework integrates multi-objective optimization with infrared feature extraction,employing a clustering multi-objective optimization approach to extract infrared features for different defect categories.Dynamic time warping is used to extract typical transient thermal responses,while virtual objective vectors are applied to extend the weight vector set and enhance the estimation accuracy of the Pareto front.Experimental results demonstrate that this method effectively improves infrared defect detection accuracy under hypervelocity impacts,providing a reliable basis for spacecraft damage assessment.
作者
高延
殷春
张昊
黄雪刚
李文学
彭啸
Gao Yan;Yin Chun;Zhang Hao;Huang Xuegang;Li Wenxue;Peng Xiao(School of Automation Engineering,University of Electronic Science and Technology of China,Chengdu 611731,China;People′s Liberation Army 32382 Troops,Beijing 100071,China;China Aerodynamics Research and Development Center,Super High Speed Aerodynamics Research Institute,Mianyang 621000,China)
出处
《电子测量技术》
北大核心
2025年第23期1-10,共10页
Electronic Measurement Technology
基金
国家自然科学基金(62273074)
四川省科技厅杰出青年基金(2024NSFJQ0015)项目资助。
关键词
红外热成像
超高速撞击
特征提取
多目标算法
infrared thermography
hypervelocity impact
feature extraction
multi-objective algorithm
