摘要
钻井过程中,底部钻具的强烈振动和快速旋转导致姿态测量信号中含有多频高幅值的干扰信号。根据上述过程的特点,提出一种改进的自适应无迹卡尔曼滤波(UKF)算法。算法在标准UKF中引入自适应因子,通过改变量测量的协方差矩阵实时调整滤波增益,提高算法对突变状态的自适应能力;并且对传统自适应因子计算方法进行改进,在保证算法精度的同时降低计算复杂度,满足随钻测量对实时性的要求。实验室振动平台系统的仿真结果表明,在振动噪声突然变强的情况下,所提方法可以有效滤除姿态测量传感器中的干扰噪声,提高导向钻具姿态参数的解算精度。
In the process of drilling,the strong vibration and fast rotation of the bottom drilling tool lead to the interference signal of multi frequency and high amplitude in the attitude measurement signal.According to the characteristics of this process,an improved adaptive unscented Kalman filter(UKF)algorithm is proposed.In this algorithm,the adaptive factor is introduced into the standard UKF,and the filter gain is adjusted in real time by changing the covariance matrix of the measurement,so as to improve the adaptive ability of the algorithm to the abrupt state;And the traditional adaptive factor calculation method is improved to ensure the accuracy of the algorithm and reduce the calculation complexity,so as to meet the real-time requirements of the measurement while drilling.The simulation results of the vibration platform system in the laboratory show that,when the vibration noise suddenly becomes strong,this method can effectively filter out the interference noise in the attitude measurement sensor and improve the accuracy of the attitude parameters of the steering drilling tool.
作者
杨一
蔡泉堃
田丹丹
YANG Yi;CAI Quan-kun;TIAN Dan-dan(School of Electronic Engineering,Xi'an Shiyou University,Xi'an Shaanxi 710065,China)
出处
《计算机仿真》
2024年第3期342-346,440,共6页
Computer Simulation
基金
国家自然科学基金面上项目(52174005)。
