Ma Ji, Yang Zhiqiang, Shi Zhen, Zhang Xuewei, Liu Chenchen
School of Geology Engineering and Geomatics, Chang'an University, Xi'an 710054, China.
Sensors (Basel). 2019 Aug 20;19(16):3624. doi: 10.3390/s19163624.
Conventional wavelet transform (WT) filters have less effect on de-noising and correction of a north-seeking gyroscope sensor exposed to vibration, since the optimal wavelet decomposed level for de-noising is difficult to determine. To solve this problem, this paper proposes an optimized WT filter which is suited to the magnetic levitation gyroscope (GAT). The proposed method was tested on an equivalent mock-up network of the tunnels associated with the Hong Kong‒Zhuhai‒Macau Bridge. The gyro-observed signals exposed to vibration were collected in our experiment, and the empirical values of the optimal wavelet decomposed levels (from 6 to 10) for observed signals were constrained and validated by the high-precision Global Navigation Satellite System (GNSS) network. The result shows that the lateral breakthrough error of the tunnel was reduced from 12.1 to 3.8 mm with a ratio of 68.7%, which suggests that the method is able to correct the abnormal signal of a north-seeking gyroscope sensor exposed to vibration.
传统小波变换（WT）滤波器对受振动影响的寻北陀螺仪传感器进行去噪和校正的效果较差，因为难以确定去噪的最佳小波分解层数。为解决这一问题，本文提出了一种适用于磁悬浮陀螺仪（GAT）的优化小波变换滤波器。该方法在与港珠澳大桥相关的隧道等效模型网络上进行了测试。在我们的实验中，收集了受振动影响的陀螺仪观测信号，并通过高精度全球导航卫星系统（GNSS）网络对观测信号的最佳小波分解层数（从6到10）的经验值进行了约束和验证。结果表明，隧道横向贯通误差从12.1毫米减小到3.8毫米，减小比例为68.7%，这表明该方法能够校正受振动影响的寻北陀螺仪传感器的异常信号。
