摘要
石英振梁加速度计在温变环境中存在输出漂移,文中采用一种新型软件补偿方法抑制温度漂移。该方法利用石英振梁自身谐振频率表征参考温度,并建立温度补偿模型。较于以温度传感器输出作为参考温度,该方法没有测温误差。在补偿算法上,提出一种基于麻雀搜索算法优化BP神经网络的温度补偿模型,能够克服BP神经网络易陷入局部最优的问题和提升补偿准确性。通过多次温度实验进行建模,对比补偿前后的输出值,零偏稳定性从392.8μg下降至65.5μg,证明该补偿方法的有效性。
Quartz vibrating beam accelerometer has output drift in temperature-changing environment.This article used a new software compensation method to suppress the temperature drift.This solution used the quartz beams'own resonant frequency to characterize the reference temperature and established a temperature compensation model.Compared with using the temperature sensor output as the reference temperature,this method had no temperature measurement error.Regarding the compensation algorithm,a temperature compensation model based on the sparrow search algorithm to optimize the BP neural network was proposed,which can overcome the problem that the BP neural network easily falled into local optimality and improve the compensation accuracy.Model was established based on many temperature experiments,and the output values before and after compensation were compared.The bias stability dropped from 392.8μg to 65.5μg,which can prove the effectiveness of the compensation method.
作者
毛志成
张晗
杨泽宇
林盛受
梁金星
MAO Zhicheng;ZHANG Han;YANG Zeyu;LIN Shengshou;LIANG Jinxing(School of Instrument Science and Engineering,Southeast University;Key Laboratory of Micro-inertial Instrument and Advanced Navigation Technology,Ministry of Education)
出处
《仪表技术与传感器》
CSCD
北大核心
2024年第7期19-24,共6页
Instrument Technique and Sensor
基金
东南大学教学改革研究项目(2021-ly-12)。
关键词
石英振梁加速度计
温度补偿
麻雀搜索算法
BP神经网络
quartz vibrating beam accelerometer
temperature compensation
sparrow search algorithm
back propagation neural network