Underground pipeline trajectory measurement method based on reduced inertial navigation

LI Hao; CHEN Qiang; XU Yixiong

doi:10.12299/jsues.22-0106

Volume 36 Issue 4

Dec. 2022

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Article Navigation > Journal of Shanghai University of Engineering Science > 2022 > 36(4): 364-368

LI Hao, CHEN Qiang, XU Yixiong. Underground pipeline trajectory measurement method based on reduced inertial navigation[J]. Journal of Shanghai University of Engineering Science, 2022, 36(4): 364-368. doi: 10.12299/jsues.22-0106

Citation:

LI Hao, CHEN Qiang, XU Yixiong. Underground pipeline trajectory measurement method based on reduced inertial navigation[J]. Journal of Shanghai University of Engineering Science, 2022, 36(4): 364-368. doi: 10.12299/jsues.22-0106

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Underground pipeline trajectory measurement method based on reduced inertial navigation

doi: 10.12299/jsues.22-0106

LI Hao^1
,,
CHEN Qiang^{1
,
,},
XU Yixiong²

1.
School of Electronic and Electrical Engineering, Shanghai University of Engineering Science, Shanghai 201620, China
2.
Shanghai Aerospace Control Technology Institute, Shanghai 201109, China

Received Date: 2022-05-02
Publish Date: 2022-12-30

Abstract

Abstract

In view of the high cost of current underground pipeline trajectory measurement system based on inertial navigation principle, the cost of the system was effectively reduced by reducing the number of inertial sensors. Firstly, the formula of using only uniaxial angular velocity and biaxial acceleration data to restore pipeline trajectory was derived. Then, the complete ensemble empirical mode decomposition with adaptive noise was used to process the original data of inertial sensors. Finally, the pipeline trajectory was reconstructed by using the derived formula and the processed data. In the 75 m long test pipeline, the maximum deviation of the reconstruction track is less than 0.2% of the total length, and the cost of the sensor is reduced by half, which has strong practical value.
- underground pipeline,
- inertial navigation,
- ensemble empirical mode decomposition,
- fiber optic gyroscope

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References(15)

References

[1]	陈思静, 胡祥云, 彭荣华. 城市地下管线探测研究进展与发展趋势[J] . 地球物理学进展,2021,36(3):1236 − 1247. doi: 10.6038/pg2021EE0257
[2]	胡玉洋, 叶荣华, 陈长青. 宁波市深埋非开挖管线探测方法与应用研究[J] . 测绘通报,2021(S2):156 − 161.
[3]	黄鹏飞. 非开挖管线精细探测方法分析[J] . 测绘通报,2021,530(5):140 − 144.
[4]	卢晓龙. 超深地下管道精确定位技术的研究及应用[J] . 测绘与空间地理信息,2021,44(10):177 − 180. doi: 10.3969/j.issn.1672-5867.2021.10.048
[5]	赵显鹏. 基于MIMU/里程计的地下管线定位技术研究 [D]. 哈尔滨: 哈尔滨工程大学, 2020.
[6]	许晓东. 地下管道定位系统及误差补偿方法的研究 [D]. 杭州: 中国计量大学, 2018.
[7]	司马健. 一种基于惯性测量的管线测绘仪的设计与实现 [D]. 南京: 东南大学, 2018.
[8]	WANG X H, SONG H. The inertial technology based 3-dimensional information measurement system for underground pipeline[J] . Measurement: Journal of the International Measurement Confederation,2012,45(3):604 − 614. doi: 10.1016/j.measurement.2011.08.016
[9]	VERMA A, KAIWART A, DUBEY N D, et al. A review on various types of in-pipe inspection robot[J] . Materials Today:Proceedings,2021,50(5):1425 − 1434.
[10]	HUANG N E, SHEN Z, LONG S R, et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J] . Proceedings of the Royal Society of London Series A: Mathematical, Physical and Engineering Sciences,1998,454(1971):903 − 995.
[11]	TORRES M E, COLOMINAS M A, Schlotthauer G, et al. A complete ensemble empirical mode decomposition with adaptive noise[C]// Proceedings of the International Conference on Acoustics, Speech and Signal Processing (ICASSP). New Jersey: IEEE, 2011: 4144 − 4147.
[12]	ZHAO Y, XU J. Denoising of ECG signals based on CEEMDAN[C]// Proceedings of the International Conference on Intelligent Computing and Signal Processing (ICICSP). New Jersey: IEEE, 2021: 430 − 433.
[13]	吴全玉, 张文强, 潘玲佼, 等. 一种结合自适应噪声完备经验模态分解和盲反卷积去除脑电中眼电伪迹的新方法[J] . 数据采集与处理,2020,35(4):720 − 729.
[14]	孙苗, 吴立, 袁青, 等. 基于CEEMDAN的爆破地震波信号时频分析[J] . 华南理工大学学报(自然科学版),2020,48(3):76 − 82.
[15]	汤俊, 李垠健, 高鑫. 基于CEEMDAN的GNSS变形监测去噪方法[J] . 大地测量与地球动力学,2021,41(4):408 − 412.