时变异方差不确定影响下的疲劳裂纹在线评估  

Online evaluation of fatigue crack under the influence of heteroscedastic uncertainty

作　　者：王卉[1] 袁慎芳[1] 孟义兴 徐秋慧 任元强 Wang Hui;Yuan Shenfang;Meng Yixing;Xu Qiuhui;Ren Yuanqiang(State Key Lab of Mechanics and Control of Mechanical Structures,Nanjing University of Aeronautics and Astronautics,Nanjing 210000,China)

机构地区：[1]南京航空航天大学机械结构力学及控制国家重点实验室,南京210000

出　　处：《仪器仪表学报》2022年第11期181-189,共9页Chinese Journal of Scientific Instrument

基　　金：国家自然科学基金创新群体项目(51921003);国家自然科学基金青年基金(51905266);江苏省自然科学基金青年基金(BK2019043517);机械结构力学及控制国家重点实验室(南京航空航天大学)自主研究课题(MCMS-I-0521K01)项目资助。

摘　　要：主动导波结构健康监测能够实时在线地监测结构状态。但时变因素影响会增加裂纹评估难度,降低评估准确性。时变因素的影响使得导波监测信号特征呈现明显的异方差特征,即导波信号特征分布方差随时间变化而改变。针对此问题,提出了异方差分位数回归辅助的裂纹在线评估方法,利用3条特殊的分位数回归曲线估计时变因素影响下信号特征随时间的分布变化情况,实现对监测数据中的异方差不确定性的处理。基于批量缺口梁结构的疲劳与导波监测试验数据对提出方法的有效性进行验证,实验结果表明,提出的方法能够实现时变影响下的损伤评估,评估最大绝对误差为1.1 mm,均方根误差为0.4 mm,并且可以有效处理时变异方差影响,量化其不确定度,为评估结果提供参考价值。The active guided wave structural health monitoring enables real-time online monitoring of structural condition.However,the time-varying influence can make crack evaluation more difficult and reduce the accuracy.The time-varying factors make the guided-wave monitoring signal characteristics show obvious heteroscedasticity.The variance of the distribution of the characteristics changes with time.To address this issue,this article proposes a quantile regression-assisted online crack evaluation method,which uses quantile regression to estimate the variance of the guided wave monitoring signal characteristics with service time under the time-varying influence,and realizes the treatment of the heteroscedasticity uncertainty in the monitoring data.The proposed method is evaluated by using experimental data of the notched beam structure.The maximum absolute error of the evaluation is 1.1 mm,and the root mean square error is 0.4 mm.The proposed method can effectively deal with the effect of time-varying heteroscedasticity,quantify its uncertainty and provide a reference value for the evaluation results.

关 键 词：疲劳裂纹 异方差 不确定性 导波 结构健康监测 分位数回归 

分 类 号：TB559[理学—物理] TH878[理学—声学]