基于高斯聚类的航天复合材料多损伤自识别方法  

Multi Damage Self Identification Method for Aerospace Composite Materials Based on Gaussian Clustering

作　　者：陶静雅 于亚平[1] 刘博 潘浚铭 宋冠霖 王照洋 钱剑[1] TAO Jingya;YU Yaping;LIU Bo;PAN Junming;SONG Guanlin;WANG Zhaoyang;QIAN Jian(Shanghai Aerospace Precision Machinery Research Institute,Shanghai 201600,China)

机构地区：[1]上海航天精密机械研究所,上海201600

出　　处：《上海航天(中英文)》2025年第1期119-125,共7页Aerospace Shanghai(Chinese&English)

基　　金：国家自然科学基金资助项目(12472348)。

摘　　要：随着可重复使用航天器的投入研制与初步使用,通过在线监测可重复使用航天器的结构响应,实时掌握其健康状况,并在此基础上对结构的多种损伤状态进行有效识别,是保障重复使用经济性的重要途径。本文针对可重复使用航天器中复合材料的结构损伤在线评估问题,研究了一种多损伤自识别方法。该方法首先基于导波对复合材料结构实现多损伤高精度成像,然后通过概率混合模型对损伤像素点进行聚类,即将监测区域中具有高损伤概率的像素值与高斯模型分量拟合,从而基于高斯模型分量的数量、均值和协方差对结构的损伤状态进行自动化评估。用本文所提方法对航天复合材料结构进行了实验验证。结果显示:该方法能够有效识别损伤个数、损伤位置及损伤方向。With the development and initial use of reusable spacecraft,online monitoring the structural responses,understanding the structural health status in real time,and effectively identifying the structural damage state have become important ways for reusable spacecraft to ensure its economy efficiency.In this paper,a multi-damage selfidentification method is proposed for the online assessment of composite structural damages in reusable spacecraft.The method first achieves the high-precision imaging of multiple damages in composite structures based on guided waves.Then,a probabilistic mixture model is used to cluster the damaged pixels,where the pixel values with high damage probability in the monitoring area are matched with the Gaussian model components.This allows the damage status of the structure to be automatically evaluated based on the number,mean value,and covariance of the Gaussian model components.Finally,experiments are carried out to verify the proposed method.The results show that the method can effectively identify the number,locations,and directions of the damages.

关 键 词：可重复使用航天器 复合材料 导波 损伤成像 概率混合模型 

分 类 号：V416.1[航空宇航科学与技术—航空宇航推进理论与工程]