Abstract
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.
Highlights
A gyro total station is a north-seeking instrument that combines a gyroscope sensor and total station, which can measure true geographical azimuths in narrow spaces where satellite signals cannot be received [1,2]
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
The observed signals on the Global Navigation Satellite System (GNSS) reference baseline in our study can be categorized into four typical types: (a) steady signal; (b) periodic signal; (c) jitter signal; and (d) jumping signal (Figure 4)
Summary
A gyro total station (gyrotheodolite) is a north-seeking instrument that combines a gyroscope sensor and total station (theodolite), which can measure true geographical azimuths in narrow spaces where satellite signals cannot be received [1,2]. During orientation measurement in a tunnel, gyro data are affected by the constant and random drift errors of the sensor and the external environmental factors, such as blasting, construction vibration, air draft-induced vibration of passing vehicles [6,7], magnetic field interference, and changes in temperature, humidity and air pressure [8,9]. These interference factors (especially physical vibration) cause abnormalities of the gyro signal, which contains significant non-stationary noise, leading to distortion of the orientation results [10]. With the development of the WT filter, the application field has been greatly
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