摘要
针对MEMS加速度计测量误差大、精度低,难以快速、准确现场标定的问题,提出了一种基于自适应布谷鸟搜索(ACS)算法的MEMS加速度计现场标定方法。通过误差分析,建立了多参数非线性误差模型,并从标定结果的方向性出发构造了标量约束目标函数。在布谷鸟搜索(CS)算法的基础上,通过提出自适应权重和自适应调节因子对算法进行了自适应改进,加快了算法收敛速度。实验结果表明,自适应改进后的CS算法收敛速度提高了16%以上,所提方法相比传统标定法降低了标定误差。
Aiming at the problems of large measurement error,low accuracy and difficult fast and accurate field calibration of MEMS accelerometer,a field calibration method of MEMS accelerometer based on adaptive cuckoo search(ACS)algorithm is proposed.Through error analysis,a multi-parameter nonlinear error model is established,and the scalar constrained objective function is constructed from the directionality of the calibration results.Based on the cuckoo search(CS)algorithm,the adaptive weight and adaptive adjustment factor are proposed to improve the algorithm and accelerate the convergence speed of the algorithm.The experimental results show that the convergence speed of the adaptive improved CS algorithm is increased by more than 16%.Compared with the traditional calibration method,the proposed method reduces the calibration error,which is an effective low-cost field calibration method.
作者
乔美英
高翼飞
李宛妮
赵岩
QIAO Meiying;GAO Yifei;LI Wanni;ZHAO Yan(School of Electrical Engineering and Automation,Jiaozuo 454000,China)
出处
《中国惯性技术学报》
EI
CSCD
北大核心
2021年第3期387-393,共7页
Journal of Chinese Inertial Technology
基金
国家自然科学基金(U1404510)
河南省矿山电力电子装置与控制创新型科技团队基金(CXTD2017085)。
