光纤光栅与增量极限学习机的航天器结构重构

Spacecraft structure reconstruction with fiber bragg grating and incremental extreme learning machine

为了解决航天器板状结构变形的监测问题,建立了结构应变检测与形变重构系统,提出了一种基于准分布式光纤光栅传感器网络和改进型增量式极限学习机相结合的结构形变重构方法。采用光纤光栅应变传感技术,搭建了四边固支平板结构应变检测与形变重构装置,每条通道由12个传感器按照四行三列等距离分布组成,并采用完全粘贴方式提高测量的准确度与稳定性。设计了基于增量式极限学习机的结构形变预测模型,经过训练,该模型能够有效的预测结构变形位移量,结合三次样条插值法,实现了变形曲面的三维重构。采用平均绝对误差以及均方根误差两个精度指标对重构方法进行评价,实验结果表明,该检测装置及形变重构方法在不同的变形状态下的平均绝对误差小于0.05 mm,均方根误差小于0.005 mm,满足航天器结构的形变监测需求。

A strain detection and reconstruction system was developed to monitor deformations on space⁃craft plate surfaces.To this end,a displacement field reconstruction method was proposed based on fiber Bragg grating sensors and an incremental extreme learning machine(I_ELM).A four sided fixed support flat plate device was designed for strain detection and deformation reconstruction.Each of its panels had 12 sensors evenly distributed in a 4×3 grid.The accuracy and stability were improved by completely sticking method.A model for predicting structural deformation was then designed based on I_ELM.The model could effectively predict structure deformation displacement after training.Finally,3D restoration was re⁃alized after incorporating cubic spline interpolation.The average absolute error of the proposed approach was less than 0.05 mm and root mean square error was less than 0.005 mm.Therefore,this method can be used to monitor the deformation of spacecraft surfaces.