Quantitative Analysis of Laser-Induced Breakdown Spectroscopy of Heavy Metals in Water Based on Support-Vector-Machine Regression

1 信阳师范学院物理电子工程学院, 河南信阳 464000 2 河南机电职业学院, 河南郑州 450000 3 南京航空航天大学机械结构力学及控制国家重点实验室, 江苏南京 210016 摘要针对光纤布拉格光栅(FBG)传感器监测飞机机翼盒段试验件上的静态载荷，对多主体协作技术实现结构健康监测中光纤 Bragg 光栅传感器网络的自修复性进行研究。当某个主体的光纤 Bragg 光栅传感器发生故障时，首先，传感主体依据采集到的传感器信号利用支持向量回归机算法对外部载荷位置进行预测，然后系统协作主体对两个主体的预测结果进行协作，共同对故障传感器信号进行修复，最终获得损伤位置的识别结果。研究表明：多主体协作之后的损伤位置平均识别精度比单独采用任何一个主体的平均识别精度都高，可以对失效传感器信号进行一定的补偿、修复。关键词光纤光学; 传感器; 光纤 Bragg 光栅; 结构健康监测; 多主体; 自修复中图分类号 TP391; O43; TN711 献标识码 AAbstract In view of the Fiber Bragg Grating (FBG) sensor network monitoring the static loading on the aircraft wing box test piece, self-repairability of the FBG structural health monitoring system based on multi-agent technology is studied. When partial sensors signal can′ t be acquired in certain agent, firstly, the support vector regression algorithm is used to predict the external loading damage position with the acquired sensor signals in each agent, and then the cooperative agent is used to cooperate each agent predicting result, so as to compensate the invalid sensor signals, thus the final predicting results are obtained for the structural health monitoring system. The research results indicate that the average predicting accuracy of the external loading position by the multi-agent technique is higher than that of any one agent, the invalid sensor signals can be compensated to some extent by the multi-agent technology.

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