为了提高耐高温传感网络检测精度并优化其性能,针对传统光纤布拉格光栅(FBG)传感网络结构测量精度低及可靠性差的缺点,设计了一种高精度高可靠传感网络结构;并基于多传感器数据融合原理,构建了改进的支持度矩阵数据融合模型对初始采样值进行融合处理。实验结果表明,290℃时,应用改进的支持度矩阵模型的传感系统测温估计值总绝对误差为o.220℃,且估计值波动幅度较小;20~290℃范围内,系统精度达到±0.2℃;当传感器发生故障时,构建的支持度矩阵模型稳健性好,传感网络测温可靠性高。本文的高温传感系统具有精度高、可靠性好和抗干扰能力强等特点,适用于实际工程的温度测量。
In order to improve the detection accuracy of high-temperature resistant sensing network and optimize its performance, a fiber Bragg grating(FBG) high-temperature sensing system based on im- proved support degree matrix model is developed. A high precision and reliability sensing network struc- ture is designed to improve the poor performance of the traditional FBG sensing network. An improved support degree matrix data fusion model is established on the basis of multi-sensor data fusion principle to fuse raw temperature data. Experimental results show that the total absolute temperature estimated error of the new system is 0. 220 ℃ when the experimental temperature is 290 ℃, and the accuracy of the system is ±4-0.2 ℃ within the range from 20 ℃ to 290 ℃ ;the fluctuation range of estimated value is small;the robustness of the established data fusion model is good and the system is steady enough to measure temperature when a sensor fails. Obtained results indicate that the sensing system has advanta ges of high precision,good reliability and strong anti-jamming, which can be used in the practical projects for temperature measurement.