碳纤维复合材料（CFRP）是航空航天等尖端科技领域一种不可或缺的战略性新材料，研究与之特性相适应的低速冲击损伤评估方法是尚未解决的国际难题。低速冲击损伤评估涉及两个核心问题：特征提取和损伤评估。目前，前者的研究缺乏对强噪声干扰的考量，而后者多从定性的角度开展研究未能实现定量预测。本项目通过将实验、有限元和机器学习有机结合，提出实验/有限元/支持向量回归（SVR）协同的CFRP低速冲击损伤定量评估新方法，实现强噪声小样本下损伤定量预测：提出有限元建模与实验校正相结合的损伤数值模拟方法，解决损伤样本低试验代价获取问题；提出基于同步压缩小波变换和主成分分析的损伤特征提取方法，解决强噪声下微弱损伤特征提取问题；提出基于支持向量回归和粒子群优化算法的损伤定量评估方法，解决小样本下损伤定量评估问题。相关问题的解决对于丰富低速冲击健康监测理论，保障航空等复合材料结构服役安全具有重要的理论意义和应用价值。

Carbon fiber reinforced polymer (CFRP) is an indispensable and strategic new material for aerospace and other advanced technology fields. It is an unsolved international problem to study low velocity impact damage assessment method which is suitable for its characteristics. Low velocity impact damage assessment involves two core problems: feature extraction and damage assessment. At present, the former research lacks the consideration of strong noise interference, while the latter is mostly from the qualitative point of view and fails to realize quantitative prediction. This project combines experiment, finite element and machine learning, and puts forward low velocity impact damage quantitative assessment method of CFRP using a combined experimental/ finite element/ support vector regression (SVR) methodology. It solves the problem of quantitative assessment of damage under strong noise and small sample condition. A damage numerical simulation method combined with finite element modeling and experimental correction is proposed to solve the problem of low test cost acquisition of damage samples. A method of damage feature extraction based on synchrosqueezed wavelet transform and principal component analysis is proposed to solve the problem of feature extraction of weak damage under strong noise. A quantitative damage assessment method based on support vector regression and particle swarm optimization is proposed to solve the problem of damage quantitative assessment under small sample conditions. The solution of related problems is of great theoretical significance and practical value for enriching the theory of low speed impact health monitoring and ensuring the safety of aviation composite materials.