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首页> 美国卫生研究院文献>Sensors (Basel Switzerland) >Multi-Sensor Combined Measurement While Drilling Based on the Improved Adaptive Fading Square Root Unscented Kalman Filter
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Multi-Sensor Combined Measurement While Drilling Based on the Improved Adaptive Fading Square Root Unscented Kalman Filter

机译：基于改进的自适应衰落平方根无味卡尔曼滤波器的随钻多传感器组合测量

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In the process of the attitude measurement for a steering drilling system, the measurement of the attitude parameters may be uncertain and unpredictable due to the influence of server vibration on bits. In order to eliminate the interference caused by vibration on the measurement and quickly obtain the accurate attitude parameters of the steering drilling tool, a new method for multi-sensor dynamic attitude combined measurement is presented. Firstly, by using a triaxial accelerometer and triaxial magnetometer measurement system, the nonlinear model based on the quaternion is established. Then, an improved adaptive fading square root unscented Kalman filter is proposed for eliminating the vibration disturbance signal. In this algorithm, the square root of the state covariance matrix is used to replace the covariance matrix in the classical unscented Kalman filter (UKF) to avoid the filter divergence caused by the negative definite state covariance matrix. The fading factor is introduced into UKF to adjust the filter gain in real-time and improve the adaptive ability of the algorithm to mutation state. Finally, the computational method of the fading factor is optimized to ensure the self-adaptability of the algorithm and reduce the computational complexity. The results of the laboratory test and the field-drilling data show that the proposed method can filter out the interference noise in the attitude measurement sensor effectively, improve the solution accuracy of attitude parameters of drilling tools in the case of abrupt changes in the measuring environment, and thus ensuring the dynamic stability of the well trajectory.
机译：在转向钻探系统的姿态测量过程中，由于服务器振动对钻头的影响，姿态参数的测量可能不确定且不可预测。为了消除振动对测量的干扰，快速获得转向钻具的精确姿态参数，提出了一种多传感器动态姿态组合测量的新方法。首先，利用三轴加速度计和三轴磁力计测量系统，建立了基于四元数的非线性模型。然后，提出了一种改进的自适应衰落平方根无味卡尔曼滤波器，以消除振动干扰信号。在该算法中，状态协方差矩阵的平方根用于替换经典的无味卡尔曼滤波器（UKF）中的协方差矩阵，以避免由负定状态协方差矩阵引起的滤波器发散。衰落因子被引入UKF，以实时调整滤波器增益并提高算法对突变状态的自适应能力。最后，对衰落因子的计算方法进行了优化，以保证算法的自适应性，降低计算复杂度。实验室测试结果和现场钻探数据表明，该方法能够有效滤除姿态测量传感器中的干扰噪声，在测量环境突变的情况下提高了钻具姿态参数的求解精度。 ，从而确保了井眼轨迹的动态稳定性。

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