Zhang Wenbo, Wang Lu, Zu Yutong
School of Engineering and Technology, China University of Geosciences, Beijing 100083, China.
Sensors (Basel). 2024 Sep 12;24(18):5911. doi: 10.3390/s24185911.
The pipe jacking guidance system based on a fiber optic gyroscope (FOG) has gained extensive attention due to its high degree of safety and autonomy. However, all inertial guidance systems have accumulative errors over time. The zero-velocity update (ZUPT) algorithm is an effective error compensation method, but accurately distinguishing between moving and stationary states in slow pipe jacking operations is a major challenge. To address this challenge, a "MV + ARE + SHOE" three-conditional zero-velocity detection (TCZVD) algorithm for the fiber optic gyroscope inertial navigation system (FOG-INS) is designed. Firstly, a Kalman filter model based on ZUPT is established. Secondly, the TCZVD algorithm, which combines the moving variance of acceleration (MV), angular rate energy (ARE), and stance hypothesis optimal estimation (SHOE), is proposed. Finally, experiments are conducted, and the results indicate that the proposed algorithm achieves a zero-velocity detection accuracy of 99.18% and can reduce positioning error to less than 2% of the total distance. Furthermore, the applicability of the proposed algorithm in the practical working environment is confirmed through on-site experiments. The results demonstrate that this method can effectively suppress the accumulated error of the inertial guidance system and improve the positioning accuracy of pipe jacking. It provides a robust and reliable solution for practical engineering challenges. Therefore, this study will contribute to the development of pipe jacking automatic guidance technology.
基于光纤陀螺仪(FOG)的顶管导向系统因其高度的安全性和自主性而受到广泛关注。然而,所有惯性导向系统都会随着时间产生累积误差。零速更新(ZUPT)算法是一种有效的误差补偿方法,但在缓慢的顶管作业中准确区分运动和静止状态是一项重大挑战。为应对这一挑战,设计了一种用于光纤陀螺仪惯性导航系统(FOG-INS)的“MV + ARE + SHOE”三条件零速检测(TCZVD)算法。首先,建立基于ZUPT的卡尔曼滤波器模型。其次,提出了结合加速度运动方差(MV)、角速率能量(ARE)和姿态假设最优估计(SHOE)的TCZVD算法。最后,进行了实验,结果表明所提出的算法实现了99.18%的零速检测精度,并且可以将定位误差降低到总距离的2%以内。此外,通过现场实验证实了所提出算法在实际工作环境中的适用性。结果表明,该方法可以有效抑制惯性导向系统的累积误差,提高顶管的定位精度。它为实际工程挑战提供了一种强大而可靠的解决方案。因此,本研究将有助于顶管自动导向技术的发展。