摘要
针对光纤布拉格光栅流量温度复合传感解耦困难的问题,提出了一种基于粒子群解耦算法的光纤布拉格光栅流量温度复合传感器。首先,结合光纤布拉格光栅传感理论和流量温度复合传感理论,研究了基于光纤布拉格光栅的流量温度复合传感机理。然后,设计了悬臂梁为空心圆柱的一体靶式结构的光纤布拉格光栅流量温度复合传感器,搭建了流量温度实验系统平台,进行了温度和流量复合传感实验。最后,提出了一种基于粒子群算法的FBG流量温度复合传感解耦方法,并运用所设计的粒子群算法对实验数据进行流量与温度解耦研究。研究结果表明,解耦后传感器在3~8 m^(3)/h的范围内其流量最大误差为0.014 m^(3)/h,温度最大误差为0.021℃,流量测量误差为0.28%,温度测量误差为1.5%,流量均方误差为1.16×10^(-4)m^(3)/h,温度均方误差为1.53×10^(-4)℃,与神经网络算法进行性能比较后,结果表明所采用的粒子群算法解耦效果良好,有效地提高了传感器的测量精度。
The decoupling in the fiber Bragg grating flow and temperature composite sensing is a difficult problem.To address this issue,a fiber Bragg grating flow and temperature composite sensor based on particle swarm decoupling algorithm is proposed.Firstly,combining the fiber Bragg grating sensing theory and the flow and temperature composite sensing theory,the flow and temperature composite sensing mechanism based on the fiber Bragg grating is studied.Then,a fiber Bragg grating flow and temperature composite sensor that integrate target structure with the cantilever beam of hollow cylinder is designed,a flow and temperature experiment system platform is established.The temperature and flow composite sensing experiments are carried out.Finally,a FBG flow and temperature composite sensor decoupling method based on the particle swarm algorithm is proposed.The proposed particle swarm optimization algorithm is used to decouple the experimental data from the flow and temperature.Research results after decoupling show that the maximum flow error of the sensor in the range of 3~8 m^(3)/h is 0.014 m^(3)/h,the maximum temperature error is 0.021℃,the flow measurement error is 0.28%,the temperature measurement error is 1.5%,the flow mean-square error is 1.16×10^(-4)m^(3)/h,and the temperature mean-square error is 1.53×10^(-4)℃.Compared with the neural network algorithm,results show that the particle swarm optimization algorithm has a good decoupling effectiveness.The measurement accuracy of the sensor could be improved effectively.
作者
孙世政
向洋
党晓圆
张辉
何盛港
Sun Shizheng;Xiang Yang;Dang Xiaoyuan;Zhang Hui;He Shenggang(School of mechatronic and vehicle engineering,Chongqing Jiaotong University,Chongqing 400074,China;School of intelligent Engineering,Chongqing College of Mobile Communication,Chongqing 401520,China)
出处
《仪器仪表学报》
EI
CAS
CSCD
北大核心
2022年第1期2-10,共9页
Chinese Journal of Scientific Instrument
基金
重庆市教委科学技术研究计划重点项目(KJZD-K202002401)
重庆市普通本科高校新型二级学院建设项目(渝教高[2018]22号)
上海市轨道交通结构耐久与系统安全重点实验室开放基金(202004)
成渝地区双城经济圈建设科技创新项目(KJCK2020032)资助
关键词
粒子群算法
光纤布拉格光栅
流量
温度
复合测量
particle swarm algorithm
fiber Bragg grating
flow
temperature
composite measurement
作者简介
通信作者:孙世政,2015年于合肥工业大学获得博士学位,现为重庆交通大学副教授、硕士生导师,主要研究方向为精密仪器与机械、智能传感技术。E-mail:ssz091011@163.com
