基于优化神经网络的磁弹电感传感器温度补偿试验研究  

Experimental Study on Temperature Compensation of Magneto-Elastic Inductance Sensor Based on Optimized Neural Network

作　　者：周建庭[1,2] 谭奎 张向和 张森华 尹昌华 ZHOU Jianting;TAN Kui;ZHANG Xianghe;ZHANG Senhua;YIN Changhua(School of Civil Engineering,Chongqing Jiaotong University,Chongqing 400074,China;State Key Laboratory of Bridge and Tunnel Engineering in Mountainous Areas Jointly Constructed byProvincial and Ministry,Chongqing Jiaotong University,Chongqing 400074,China;Chongqing Municipal Facilities Management Bureau,Chongqing 400015,China)

机构地区：[1]重庆交通大学土木工程学院,重庆400074 [2]重庆交通大学省部共建山区桥梁及隧道工程国家重点实验室,重庆400074 [3]重庆市市政设施管理局,重庆400015

出　　处：《重庆交通大学学报（自然科学版）》2023年第1期15-20,共6页Journal of Chongqing Jiaotong University(Natural Science)

基　　金：国家自然科学基金项目(U20A20314);重庆市自然科学基金创新群体科学基金项目(cstc2019jcyj-cxttX0004);重庆市技术创新与应用发展专项重点项目(cstc2019jscx-gksbX0047);重庆交通大学研究生科研创新(创新基金)项目(2020S0014)。

摘　　要：磁弹电感传感器是磁弹电感法监测预应力钢绞线应力的主要设备。温度会引起监测误差,为提升监测精度,首先,分析了磁弹电感法监测应力的原理以及温度影响机理;其次,对4组不同张拉控制力的预应力钢绞线进行温度补偿试验,研究了传感器的温度敏感性,发现传感器电感漂移与变温幅度和路径相关,温度引起的相对误差最大达11.1%;最后,利用K折交叉验证方法,分别采用BP神经网络与优化后的GA-BP神经网络进行温度补偿。研究结果表明:相较于BP神经网络,GA-BP神经网络可有效修正温度误差,提升泛化能力,优化后相对误差降至3.3%。Magneto-elastic inductance sensor is the main equipment to monitor the stress of prestressed steel strand by magneto-elastic inductance method,but the temperature will cause monitoring error.In order to improve the monitoring accuracy,firstly,the principle of stress monitored by magneto-elastic inductance method and the influence mechanism of temperature were analyzed.Secondly,four groups of prestressed steel strands with different tension control forces were tested for temperature compensation,and the temperature sensitivity of the sensor was studied to find that the sensor inductance drift was related to the temperature variation amplitude and path,and the relative error caused by temperature was up to 11.1%.Finally,BP neural network and optimized GA-BP neural network were respectively used to compensate temperature by K-fold cross verification method.The research results show that:compared with BP neural network,GA-BP neural network can effectively correct the temperature error,improve the generalization ability,and reduce the relative error to 3.3%after optimization.

关 键 词：桥梁工程 磁弹电感法 预应力监测 温度补偿 K折交叉验证 优化神经网络 

分 类 号：U448.35[建筑科学—桥梁与隧道工程]