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

Ma, Ji; Yang, Zhiqiang; Shi, Z.; Zhang, Xuewei; Liu, Chenchen

doi:10.3390/s19163624

Cited by 9 publications

(10 citation statements)

References 39 publications

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“…The selection of the mother wavelet is dependent on the properties of the wavelet and its similarity with collected signals. In this study, Symlets 6 (Sym6) mother wavelet was selected because it can reduce the phase distortion in signal analysis and reconstruction [44], and it is suitable for the characteristics of GNSS measurements [24]. Figure 1a illustrates the scaling and function of the Sym6 wavelet.…”

Section: Methodsmentioning

confidence: 99%

Hybrid Wavelet and Principal Component Analyses Approach for Extracting Dynamic Motion Characteristics from Displacement Series Derived from Multipath-Affected High-Rate GNSS Observations

et al. 2019

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Nowadays, the high rate GNSS (Global Navigation Satellite Systems) positioning methods are widely used as a complementary tool to other geotechnical sensors, such as accelerometers, seismometers, and inertial measurement units (IMU), to evaluate dynamic displacement responses of engineering structures. However, the most common problem in structural health monitoring (SHM) using GNSS is the presence of surrounding structures that cause multipath errors in GNSS observations. Skyscrapers and high-rise buildings in metropolitan cities are generally close to each other, and long-span bridges have towers, main cable, and suspender cables. Therefore, multipath error in GNSS observations, which is typically added to the measurement noise, is inevitable while monitoring such flexible engineering structures. Unlike other errors like atmospheric errors, which are mostly reduced or modeled out, multipath errors are the largest remaining unmanaged error sources. The high noise levels of high-rate GNSS solutions limit their structural monitoring application for detecting load-induced semi-static and dynamic displacements. This study investigates the estimation of accurate dynamic characteristics (frequency and amplitude) of structural or seismic motions derived from multipath-affected high-rate GNSS observations. To this end, a novel hybrid model using both wavelet-based multiscale principal component analysis (MSPCA) and wavelet transform (MSPCAW) is designed to extract the amplitude and frequency of both GNSS relative- and PPP- (Precise Point Positioning) derived displacement motions. To evaluate the method, a shaking table with a GNSS receiver attached to it, collecting 10 Hz data, was set up close to a building. The table was used to generate various amplitudes and frequencies of harmonic motions. In addition, 50-Hz linear variable differential transformer (LVDT) observations were collected to verify the MSMPCAW model by comparing their results. The results showed that the MSPCAW could be efficiently used to extract the dynamic characteristics of noisy dynamic movements under seismic loads. Furthermore, the dynamic behavior of seismic motions can be extracted accurately using GNSS-PPP, and its dominant frequency equals that extracted by LVDT and relative GNSS positioning method. Its accuracy in determining the amplitude approaches 91.5% relative to the LVDT observations.

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Section: Methodsmentioning

confidence: 99%

Hybrid Wavelet and Principal Component Analyses Approach for Extracting Dynamic Motion Characteristics from Displacement Series Derived from Multipath-Affected High-Rate GNSS Observations

et al. 2019

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“…The gyro total station (gyro-theodolite), which integrates the gyroscope and total station (theodolite), is a precise and sensitive measurement and directional instrument that can independently determine true north azimuths in underground spaces where satellite signals are hardly received [1,2]. Recently, it has been widely used to orient tunnel breakthroughs, mining, subway construction, missile launching, weapons guidance, etc [3][4][5]. The processing of the observed gyroscope signal is one of the main elements controlling the accuracy and precision of the gyro total station [3,6].…”

Section: Introductionmentioning

confidence: 99%

“…Several factors influence the quality of gyroscope signals. Previous studies have suggested that the gyroscope signal is not only affected by the error of the sensor itself, but also by external environmental factors, such as ground vibration, wind vibration, electromagnetic interference, temperature, and air pressure changes [3,4,[7][8][9][10]. Some of these factors result in the periodic characteristics of the gyro signal, which decreases the accuracy of the instrument [11].…”

Section: Introductionmentioning

confidence: 99%

Periodic error detection and separation of magnetic levitation gyroscope signals based on continuous wavelet transform and singular spectrum analysis

Wang

Yang

Shi

et al. 2022

Meas. Sci. Technol.

Self Cite

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The accuracy of the north azimuth measured using the magnetic levitation gyroscope (GAT) declines owing to the influence of the periodic errors of GAT signals induced by the systematic error of the gyro rotor system and the influence of external environment. To address this issue, this paper proposes a novel methodological strategy based on continuous wavelet transform (CWT) and singular spectrum analysis (SSA) to process GAT periodic errors and improve the accuracy of north-seeking. Firstly, CWT is used to process a large number of GAT signals to obtain the statistical characteristics of the periodic errors. Subsequently, the reconstructed components (RCs) of the GAT signals are obtained using SSA. After detecting and grouping the periodic terms contained in each RC using CWT, the periodic errors in the GAT signals are clearly separated. Finally, the effectiveness of this method was verified by comparing our north azimuths with those measured using the high-precision global navigation satellite system (GNSS) baseline. Our results indicated that the periodic errors in GAT signals can be accurately divided into the high frequency periodic error and the low frequency periodic error, and both periodic errors can be clearly detected and separated. After processing, the root mean square error of the GAT rotor currents and the absolute difference between the gyro and high-precision GNSS north azimuths were enhanced by 22.6% and 43.2%, respectively. The method presented in this paper to process periodic errors is suitable for use in the preprocessing of GAT signals.

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“…Ma et al. applied the optimized WT filter to the magnetic levitation gyroscope (GAT) and successfully reduced the vibration noise in actual use [ 17 ]. The WT method can effectively reduce the random noise in FOG signal, but this method needs to preset wavelet basis function and decomposition level, so the adaptability is not good.…”

Section: Introductionmentioning

confidence: 99%

A Denoising Method for Fiber Optic Gyroscope Based on Variational Mode Decomposition and Beetle Swarm Antenna Search Algorithm

Wang¹,

Gao²,

Wu³

et al. 2020

Entropy

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Fiber optic gyroscope (FOG) is one of the important components of Inertial Navigation Systems (INS). In order to improve the accuracy of the INS, it is necessary to suppress the random error of the FOG signal. In this paper, a variational mode decomposition (VMD) denoising method based on beetle swarm antenna search (BSAS) algorithm is proposed to reduce the noise in FOG signal. Firstly, the BSAS algorithm is introduced in detail. Then, the permutation entropy of the band-limited intrinsic mode functions (BLIMFs) is taken as the optimization index, and two key parameters of VMD algorithm, including decomposition mode number K and quadratic penalty factor α , are optimized by using the BSAS algorithm. Next, a new method based on Hausdorff distance (HD) between the probability density function (PDF) of all BLIMFs and that of the original signal is proposed in this paper to determine the relevant modes. Finally, the selected BLIMF components are reconstructed to get the denoised signal. In addition, the simulation results show that the proposed scheme is better than the existing schemes in terms of noise reduction performance. Two experiments further demonstrate the priority of the proposed scheme in the FOG noise reduction compared with other schemes.

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

Cited by 9 publications

References 39 publications

Hybrid Wavelet and Principal Component Analyses Approach for Extracting Dynamic Motion Characteristics from Displacement Series Derived from Multipath-Affected High-Rate GNSS Observations

Hybrid Wavelet and Principal Component Analyses Approach for Extracting Dynamic Motion Characteristics from Displacement Series Derived from Multipath-Affected High-Rate GNSS Observations

Periodic error detection and separation of magnetic levitation gyroscope signals based on continuous wavelet transform and singular spectrum analysis

A Denoising Method for Fiber Optic Gyroscope Based on Variational Mode Decomposition and Beetle Swarm Antenna Search Algorithm

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