摘要
飞机结构的检修工作需要根据裂纹扩展预测结果制定出检查时间,而裂纹扩展受到多种随机不确定因素的影响.为了综合利用基于物理知识的模型预测结果与基于检查的观测结果、有效地追踪和控制不确定性,论文提出了一种基于数字孪生的飞机蒙皮裂纹智能检查维修策略.该方法以含铆钉孔边裂纹的飞机蒙皮为研究对象,结合降阶的断裂力学仿真模型、疲劳裂纹扩展模型、裂纹长度检查数据,在动态贝叶斯网络框架下综合考虑了裂纹尺寸初始分布、裂纹扩展模型参数、飞行中的压差载荷、测量误差等不确定因素,根据损伤的概率性诊断和预测结果动态调整裂纹的检查时间.仿真结果表明该方法能够有效追踪不确定性的裂纹扩展过程,可以为飞机蒙皮裂纹的智能检查维修提供方法和依据.
In order to ensure the safety of aircraft structures,inspections and repairs must be rationally planned based on the analysis of fatigue crack growth,which is affected by various aleatory and epistemic uncertainties.In order to effectively consider the influences of various uncertainties and track the crack growth process,an intelligent digital-twin-based strategy for planning the inspections and repairs of aircraft skin cracks is proposed in this paper,by fusing the predictions by physical models with ground inspections.In this strategy,the reduced-order fracture mechanics simulation,the fatigue crack growth model,and the crack length inspections are integrated into the framework of dynamic Bayesian network.The strategy comprehensively considers the influences of uncertainties from the initial crack size,crack growth model parameters,and pressure loads during flight on crack growth,so as to dynamically adjust the inspection and maintenance intervals according to the probabilistic damage diagnosis and prognosis results.In an example of an aircraft skin with a single-edge crack near a rivet hole,the intelligent inspection scheme is demonstrated for three hypothetical specimens with various initial crack sizes and crack growth model parameters.The simulation results show that the proposed method can effectively control the uncertainties from various sources and track the crack growth process,which may therefore provide a dynamic inspection and repair plan for the cracked aircraft skin.
作者
赵福斌
周轩
董雷霆
Fubin Zhao;Xuan Zhou;Leiting Dong(School of Aeronautic Science and Engineering,Beihang University,Beijing,100191)
出处
《固体力学学报》
CAS
CSCD
北大核心
2021年第3期277-286,共10页
Chinese Journal of Solid Mechanics
基金
航空科学基金项目(201909051001)
先进无人飞行器北京高校高精尖学科基地种子基金项目(ADBUAS-2019-SP-05)资助。
作者简介
通讯作者:董雷霆.Tel:010-82315159,E-mail:ltdong@buaa.edu.cn.
