Research on Identification and Suppression of Vibration Error for MEMS Inertial Sensor in Near-Bit Inclinometer

Abstract

The measurement information of the traditional conventional measurement while drilling (MWD) method lags seriously because the installation position is far from the bit. However, the near-bit inclinometer will generate a large number of vibration interference signals when the bit breaks the rock in the drilling process, resulting in the continuous increase in errors measured by the microelectromechanical system (MEMS) inertial sensor. Aiming at the problems of low accuracy and poor stability of near-bit inclinometer under the interference of long-term complex vibration signals, a vibration error identification and suppression method of MEMS inertial sensor of near-bit inclinometer is proposed in this article. Firstly, the characteristics of the vibration signal of near-bit inclinometer are analyzed. The near-bit vibration errors of first-order linear vibration and high-order nonlinear vibration are identified, and the vibration characteristics are analyzed, the error model of gyroscope and accelerometer under complex vibration interference is established, and then the vibration error suppression model of inclinometer gyroscope and accelerometer is established based on the hybrid Kalman filter (KF) and unscented KF (UKF) algorithm. Finally, the hardware and software experimental platform of near-bit inclinometer is built. The experimental results show that the dynamic measurement errors of inclination, toolface, and azimuth are kept within ±0.6°, and the vibration errors of gyroscope and accelerometer are effectively suppressed.