传感技术学报2016，Vol.29Issue(12)：1864-1868,5.DOI:10.3969/j.issn.1004-1699.2016.12.014
基于混合优化算法的压力传感器温度补偿
Temperature Compensation of Pressure Sensor Based on Hybrid Optimization Algorithm*
摘要
Abstract
Aiming at the temperature drift of the pressure resistance sensor,the measurement accuracy is greatly af?fected by the temperature,and the temperature compensation model of pressure sensor is established by using the least square fitting method and the RBF neural network. The RBF neural network is used to compensate the low tem?perature and high temperature region,and the least square fitting method is used to compensate the middle linear re?gion. At the same time in order to improve the RBF neural network fitting effect,using the evolutionary algorithm and the descent gradient algorithm to optimize the RBF neural network parameters. Experimental results show that the use method and simple use of RBF neural network and least square fitting method for temperature compensa?tion,has higher training efficiency and effect of temperature compensation,can improve the pressure sensor under various environmental measurement precision and reliability.关键词
压力传感器/温度补偿/最小二乘法拟合/RBF神经网络/混合优化/融合算法Key words
pressure sensor/temperature compensation/least square fitting/RBF neural network/hybrid optimiza⁃tion/fusion algorithm分类
信息技术与安全科学引用本文复制引用
王慧,宋宇宁..基于混合优化算法的压力传感器温度补偿[J].传感技术学报,2016,29(12):1864-1868,5.基金项目
国家青年自然科学基金项目(51405213) （51405213）
