Error parameter identification method of MEMS accelerometers while drilling based on IAO

被引：0
作者：
Yang J. [1 ,2 ]
Wang S. [1 ,2 ]
Shen L. [1 ,2 ]
Yuan X. [1 ,2 ]
Cai J. [1 ,2 ]
Yin F. [1 ,2 ]
机构：
[1] School of Electrical Engineering and Automation, Henan Polytechnic University, Jiaozuo
[2] Henan Key Laboratory of Intelligent Detection and Control of Coal Mine Equipment, Jiaozuo
来源：
Zhongguo Guanxing Jishu Xuebao/Journal of Chinese Inertial Technology | 2023年 / 31卷 / 05期
关键词：
adaptive opposition based learning; aquila optimizer; error parameter identification; interpolation; MEMS accelerometer;
D O I：
10.13695/j.cnki.12-1222/o3.2023.05.013
中图分类号：
学科分类号：
摘要：
Aiming at the problem that it is difficult to accurately identify the error changes of MEMS accelerometer in the measurement while drilling, an error parameter identification method of MEMS accelerometer while drilling based on the improved aquila optimizer (IAO) algorithm is proposed. Firstly, the nonlinear error function is obtained by transforming the output model of MEMS accelerometer, and the optimal value of the nonlinear error function is solved by the aquila optimizer (AO) algorithm. On the basis of AO algorithm, the average value of error parameters and the number of iterations are used to improve the global search ability of mining parameters of AO algorithm, and radial factors are constructed based on the optimal value and average value of error parameters to improve the accuracy of AO algorithm error parameter identification. Then, IAO algorithm is used to approximate the optimal parameters of the nonlinear error function, and the error parameters are calibrated through the sampling point interpolation error database. Finally, IAO algorithm is applied to identify the error parameters of the accelerometer. The results show that the recognition accuracy of IAO algorithm is 1~2 orders of magnitude higher than that of PSO algorithm, SSA algorithm and AO algorithm, and the output error of the accelerometer is obviously reduced after compensation. © 2023 Editorial Department of Journal of Chinese Inertial Technology. All rights reserved.
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页码：516 / 522and530
相关论文
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