测试技术学报2025，Vol.39Issue(1)：13-19,7.DOI:10.62756/csjs.1671-7449.2025003
基于BP神经网络的压力传感器原位温度补偿技术
In-Situ Temperature Compensation Technology for Pressure Sensors Based on BP Neural Network
摘要
Abstract
Due to the temperature drift of piezoresistive pressure sensors,existing software temperature compensation methods rely on additional temperature sensors to obtain temperature signals.To simplify this process,a pressure sensor in-situ temperature compensation method based on BP neural networks is proposed.Utilizing a multi-parameter measurement method,it can achieve in-situ temperature and pres-sure measurements of the sensor based solely on its electrical signals,without the need to introduce new sensors.Furthermore,it achieves pressure sensor temperature-pressure decoupling and temperature com-pensation through BP neural networks.The results show that the sensor output error is reduced to within±0.5%FS after compensation,with the zero-position temperature drift reduced from 0.021%FS/℃to 0.002 5%FS/℃,and the sensitivity temperature drift reduced from 0.15%FS/℃to 0.005 5%FS/℃,significantly reducing the zero-position temperature drift and sensitivity temperature drift.关键词
压力传感器/温度补偿/多参数测量/BP神经网络Key words
pressure transducer/temperature compensation/multi-parameter measurement/BP neural network分类
计算机与自动化引用本文复制引用
刘雨桥,张姝,雷程,余建刚,唐梦璇,王涛龙,梁庭..基于BP神经网络的压力传感器原位温度补偿技术[J].测试技术学报,2025,39(1):13-19,7.基金项目
国家重点研发计划资助项目(2023YFB3208500) （2023YFB3208500）
山西省重点研发计划资助项目(2023020302010) （2023020302010）
中央引导地方科技发展资金资助项目(YDZJSX20231B006) （YDZJSX20231B006）
