时变环境下航空结构损伤的波动概率统计成像方法研究

The problem of reliable damage evaluation under aircraft service condition is a main obstacle for applying elastic wave based structural health monitoring and management (SHM) technology to aviation engineering application because the coupling influence of the complex aircraft structure and the time-varying condition existed in the service condition can introduce large uncertainties to the propagation property of the elastic wave. To deal with this problem, this project will perform deep research by combining the elastic wave based damage imaging method with probability and statistics modeling method. Firstly, physical simulation and experimental research on elastic wave propagation under the coupling influence of the complex aircraft structure and the time-varying condition will be performed, and a probability and statistics modeling method will be studied as well to characterize the probability distribution property of the elastic wave under the coupling influence. Secondly, deep research will be performed on adaptive modeling, updating and quantitative migration of the probability and statistics model of the elastic wave. The extraction method of damage-sensitive statistical features will be proposed to reduce the coupling influence and reveal the influence caused by structural damage. Thirdly, a construction method of wave imaging feature based on the probability and statistics model of the elastic wave will be studied, and the delay-and-sum imaging method will be also improved. Based on the wave imaging feature and the improved delay-and-sum imaging method, the synthetic imaging of the array wave imaging features can be realized to enhance the influence of the damage. Moreover, a damage evaluation method based on the imaging results will be studied. Based on all the researches mentioned above, a delay-and-sum and probability-statistics based wave imaging method which can improve the damage evaluation reliability will be proposed. Finally, the imaging method will be validated on real aircraft structures under time-varying condition so as to promote the aviation engineering application of the elastic wave based SHM technology.

航空结构服役环境中弹性波传播特性受到复杂结构时变环境因素耦合的不确定性影响导致结构损伤难以可靠监测，是阻碍弹性波结构健康监测与管理（SHM）技术航空工程应用的瓶颈问题。针对该问题，本项目将损伤波动成像方法和概率统计建模方法相结合：开展复杂结构时变环境因素耦合影响下弹性波传播的物理仿真和实验研究以及概率统计建模方法研究，表征弹性波受该影响的概率分布特性；深入研究弹性波概率统计模型的自适应建立和更新机制及其迁移量化方法，建立损伤敏感统计特征提取方法以揭示损伤影响；研究基于弹性波概率统计模型的波动成像特征建立方法，优化延迟-累加成像方法，实现阵列波动成像特征合成成像以增强损伤影响；研究基于波动概率统计成像结果的损伤评估方法，提出时变环境下航空结构损伤的延迟-累加概率统计成像方法，提高损伤监测的可靠性。最后针对真实航空结构时变环境对成像方法进行验证，以此促进弹性波SHM技术的航空工程应用。

本项目针对航空结构时变服役环境带来监测的强不确定性导致损伤可靠诊断难这一领域应用亟待解决的共性难题和瓶颈，围绕压电-弹性波结构健康监测方法，理清了时变影响机理、提出了弹性波特征不确定性的概率统计建模方法、建立了波动概率统计成像机制，实现了航空飞行器型号应用：理清了弹性波受温度和载荷影响的物理机理，提出了结构-损伤-弹性波-时变环境因素的多物理直接耦合仿真建模方法，实现了温度、载荷影响下的弹性波传播仿真，建立了基于零件级结构的弹性波受时变环境因素耦合影响的标准数据库；提出了利用概率混合模型对弹性波受时变环境因素耦合影响的不确定性特征进行概率统计建模及表征的方法，提出了强化型和自适应型两种高效的概率混合模型建立方法，建立了概率混合模型在线动态更新机制以及基于概率散布距离和模型自相似的概率混合模型动态迁移量化方法，通过弹性波-动态概率混合模型的在线更新和迁移量化来揭示损伤的发生和累积扩展过程，实现了对时变环境因素耦合影响的第一级抑制；提出了弹性波阵列信号动态概率路径合成成像方法和动态概率时间反转聚焦成像方法，建立了基于损伤波动概率统计成像方法的四维成像历史损伤评估方法，实现了对时变环境因素影响的第二级抑制的同时对损伤影响的聚焦增强和损伤定位，显著提高了时变环境影响下的航空结构损伤监测可靠性。项目提出的方法已应用于运-20、C919、ARJ21-700等多个航空飞行器型号。发表期刊论文15篇，其中SCI源刊论文11篇（IF>3的论文7篇，JCR Q1区论文10篇，中科院1区Top期刊论文5篇），发表国际会议论文12篇；申请国家发明专利9项（授权5项），申请美国发明专利1项，授权软著2项；作为组委会主席主办国际会议1次，大会/特邀报告4次，国际会议分会报告11人次，国际互访13人次；培养博士研究生4名，硕士研究生8名；获结构健康监测领域顶级国际会议全球唯一最佳论文奖；项目成果作为团队成果的重要组成部分获2019年江苏省科学技术一等奖。