分布式光纤传感器应变读数异常的自适应后处理算法  

An Adaptive Post-Processing Algorithm for Strain Reading Anomalies in Distributed Optical Fiber Sensors

作　　者：梁智洪 邓凯文 马云龙 王明华 刘德博 吴会强 王奕首 Liang Zhihong;Deng Kaiwen;Ma Yunlong;Wang Minghua;Liu Debo;Wu Huiqiang;Wang Yishou(School of Aerospace Engineering,Xiamen University,Xiamen 361005,Fujian,China;Beijing Institute of Astronautical Systems Engineering,Beijing 100076,China)

机构地区：[1]厦门大学航空航天学院,福建厦门361005 [2]北京宇航系统工程研究所,北京100076

出　　处：《光学学报》2024年第1期343-354,共12页Acta Optica Sinica

基　　金：国家重点研发计划(2018YFA070144);国防基础科研计划重大项目(JCKY2019203A003);基础加强计划重点项目(JCJQZD-203);国家自然科学基金(U2141245)。

摘　　要：针对分布式光纤传感器在航空航天领域应用中存在的应变读数异常现象,提出一种可检测和快速清除分布式光纤传感器应变读数异常的自适应后处理算法,以提高传感器监测精度与数据可靠性。该算法采用K均值聚类方法进行自适应定义阈值,以区分不同结构特征及不同服役环境导致的数据分布与噪声响应的差异性。在此基础上,对扭曲的应变曲线实行连续的几何偏置来消除应变读数异常。最后以航天燃料贮箱压力循环实验中采集的分布式光纤传感数据处理为例验证所提方法的有效性,使用Pearson相关系数来表征后处理曲线与无异常曲线的相关性,并与其他后处理算法进行对比。结果表明,针对2种主要类型、8种典型案例的应变异常现象,所提方法均能获得最佳的后处理结果,与无异常曲线的相关性系数不低于0.917。Objective Distributed optic fiber sensor(DOFS)is widely used for status monitoring and damage detection of aerospace vehicles due to its ability to achieve large-area and high-density sensing of structures.However,in the face of uncertainties caused by the harsh service environment of aerospace,a phenomenon of strain reading anomalies(SRAs)occurs in DOFS measurements.These SRAs result in significant strain peaks occurring in localized regions or at specific moments in time,thereby posing challenges for DOFS to accurately measure physical quantities and making it even more difficult to interpret these measurements.To minimize the negative effects of SRAs,some researchers have adopted a series of data processing methods,such as polynomial fitting method,spectral shift quality(SSQ)method,geometrical threshold method(GTM),and polynomial interpolation comparison method(PICM).Although these data processing methods are effective in reducing random errors in measurement data,they fail to completely remove the phenomenon of SRAs,and there is still a risk of removing highly reliable measurement readings.Meanwhile,the above methods still use the fixed threshold method to detect and determine the anomalies,and the determination of the fixed threshold relies on manual experience,which has low detection efficiency and a high false alarm rate,thus limiting its application in complex service environments.Therefore,we propose an intelligent adaptive post processing method for detecting and quickly removing SRAs from DOFS.Methods The proposed algorithm,namely the adaptive geometrical threshold offset method(AGTOM),adopts the K-means clustering method to adaptively determine thresholds for distinguishing differences of thresholds caused by various structural features and service conditions.A continuous geometric correction is implemented on the distorted strain curves to effectively eliminate SRAs.To verify the effectiveness of the proposed method,a case study is conducted on the processing of DOFS measurement data collected during

关 键 词：光纤光学 瑞利散射 分布式光纤传感 K均值聚类 自适应阈值 复合材料贮箱 

分 类 号：O439[机械工程—光学工程] V19[理学—光学]