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A Novel Method for Automatic Detection and Elimination of the Jumps Caused by the Instantaneous Disturbance Torque in the Maglev Gyro Signal
The signal measured by the maglev gyro sensor is sensitive to the influence of the instantaneous disturbance torque caused by the instantaneous strong wind or the ground vibration, which reduced the north-seeking accuracy of the instrument. To address this issue, we proposed a novel method combining...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10007503/ https://www.ncbi.nlm.nih.gov/pubmed/36904966 http://dx.doi.org/10.3390/s23052763 |
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author | Wang, Yiwen Yang, Zhiqiang Ma, Ji Shi, Zhen Liu, Di Shi, Ling Li, Hang |
author_facet | Wang, Yiwen Yang, Zhiqiang Ma, Ji Shi, Zhen Liu, Di Shi, Ling Li, Hang |
author_sort | Wang, Yiwen |
collection | PubMed |
description | The signal measured by the maglev gyro sensor is sensitive to the influence of the instantaneous disturbance torque caused by the instantaneous strong wind or the ground vibration, which reduced the north-seeking accuracy of the instrument. To address this issue, we proposed a novel method combining the heuristic segmentation algorithm (HSA) and the two-sample Kolmogorov-Smirnov (KS) test (named HSA-KS method) to process the gyro signals and improve the north-seeking accuracy of the gyro. There were two key steps in the HSA-KS method: (i) all the potential change points were automatically and accurately detected by HSA, and (ii) the jumps in the signal caused by the instantaneous disturbance torque were quickly located and eliminated by the two-sample KS test. The effectiveness of our method was verified through a field experiment on a high-precision global positioning system (GPS) baseline at the 5th sub-tunnel of the Qinling water conveyance tunnel of the Hanjiang-to-Weihe River Diversion Project in Shaanxi Province, China. Our results from the autocorrelograms indicated that the jumps in the gyro signals can be automatically and accurately eliminated by the HSA-KS method. After processing, the absolute difference between the gyro and high-precision GPS north azimuths was enhanced by 53.5%, which was superior to the optimized wavelet transform and the optimized Hilbert-Huang transform. |
format | Online Article Text |
id | pubmed-10007503 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-100075032023-03-12 A Novel Method for Automatic Detection and Elimination of the Jumps Caused by the Instantaneous Disturbance Torque in the Maglev Gyro Signal Wang, Yiwen Yang, Zhiqiang Ma, Ji Shi, Zhen Liu, Di Shi, Ling Li, Hang Sensors (Basel) Article The signal measured by the maglev gyro sensor is sensitive to the influence of the instantaneous disturbance torque caused by the instantaneous strong wind or the ground vibration, which reduced the north-seeking accuracy of the instrument. To address this issue, we proposed a novel method combining the heuristic segmentation algorithm (HSA) and the two-sample Kolmogorov-Smirnov (KS) test (named HSA-KS method) to process the gyro signals and improve the north-seeking accuracy of the gyro. There were two key steps in the HSA-KS method: (i) all the potential change points were automatically and accurately detected by HSA, and (ii) the jumps in the signal caused by the instantaneous disturbance torque were quickly located and eliminated by the two-sample KS test. The effectiveness of our method was verified through a field experiment on a high-precision global positioning system (GPS) baseline at the 5th sub-tunnel of the Qinling water conveyance tunnel of the Hanjiang-to-Weihe River Diversion Project in Shaanxi Province, China. Our results from the autocorrelograms indicated that the jumps in the gyro signals can be automatically and accurately eliminated by the HSA-KS method. After processing, the absolute difference between the gyro and high-precision GPS north azimuths was enhanced by 53.5%, which was superior to the optimized wavelet transform and the optimized Hilbert-Huang transform. MDPI 2023-03-02 /pmc/articles/PMC10007503/ /pubmed/36904966 http://dx.doi.org/10.3390/s23052763 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Wang, Yiwen Yang, Zhiqiang Ma, Ji Shi, Zhen Liu, Di Shi, Ling Li, Hang A Novel Method for Automatic Detection and Elimination of the Jumps Caused by the Instantaneous Disturbance Torque in the Maglev Gyro Signal |
title | A Novel Method for Automatic Detection and Elimination of the Jumps Caused by the Instantaneous Disturbance Torque in the Maglev Gyro Signal |
title_full | A Novel Method for Automatic Detection and Elimination of the Jumps Caused by the Instantaneous Disturbance Torque in the Maglev Gyro Signal |
title_fullStr | A Novel Method for Automatic Detection and Elimination of the Jumps Caused by the Instantaneous Disturbance Torque in the Maglev Gyro Signal |
title_full_unstemmed | A Novel Method for Automatic Detection and Elimination of the Jumps Caused by the Instantaneous Disturbance Torque in the Maglev Gyro Signal |
title_short | A Novel Method for Automatic Detection and Elimination of the Jumps Caused by the Instantaneous Disturbance Torque in the Maglev Gyro Signal |
title_sort | novel method for automatic detection and elimination of the jumps caused by the instantaneous disturbance torque in the maglev gyro signal |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10007503/ https://www.ncbi.nlm.nih.gov/pubmed/36904966 http://dx.doi.org/10.3390/s23052763 |
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