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Application and Optimization of Wavelet Transform Filter for North-Seeking Gyroscope Sensor Exposed to Vibration

机译:小波变换过滤器的应用与优化朝向振动传感器暴露于振动

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摘要

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.
机译:传统的小波变换(WT)滤光器对暴露于振动的北陀螺仪传感器的去噪和校正效果较小,因为最佳小波分解水平难以确定。为了解决这个问题,本文提出了一种优化的WT滤波器,其适用于磁悬浮陀螺仪(GAT)。在与港珠海澳大略信相关的隧道的等效模型网络上测试了所提出的方法。在我们的实验中收集了暴露于振动的陀螺仪观察到的信号,并且通过高精度全球导航卫星系统(GNSS)网络被约束和验证了观察到的信号的最佳小波分解水平(6至10)的经验值。 。结果表明,隧道的横穿突破误差从12.1到3.8毫米降低,比率为68.7%,这表明该方法能够校正暴露于振动的象征陀螺仪传感器的异常信号。

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