0
Research Papers

Pipeline Inspection Gauge Position Estimation Using Inertial Measurement Unit, Odometer, and a Set of Reference Stations

[+] Author and Article Information
Md Sheruzzaman Chowdhury

Mechatronics Graduate Program,
American University of Sharjah,
P.O. Box 26666, Sharjah, United Arab Emirates
e-mail: sheruz@gmail.com

Mamoun F. Abdel-Hafez

American University of Sharjah,
P.O. Box 26666, Sharjah, United Arab Emirates
e-mail: mabdelhafez@aus.edu

Manuscript received January 2, 2015; final manuscript received June 1, 2015; published online January 4, 2016. Assoc. Editor: Athanasios Pantelous.

ASME J. Risk Uncertainty Part B 2(2), 021001 (Jan 04, 2016) (10 pages) Paper No: RISK-15-1002; doi: 10.1115/1.4030945 History: Received January 02, 2015; Accepted June 30, 2015

This paper presents a low-cost methodology to estimate the position of a pipeline inspection gauge (PIG). The environment in which the PIG navigates is inside the thick walls of a metallic pipeline, where it is not possible to receive a global positioning system (GPS) signal. As a consequence, it is necessary to use other means of navigation. A technique is presented in the paper that uses an inertial measurement unit (IMU), a speedometer, and a set of reference stations. A Kalman filter is used to fuse the measurements from the IMU, the speedometer, and the reference stations. The reference stations, with known GPS coordinates, are installed for every set interval to correct the PIG’s state estimate from the errors that accumulate due to the integration of the IMU measurements. The paper presents three scenarios. These scenarios differ in the way the update step of the Kalman filter is performed. Experimental results are presented along with a 100-run Monte Carlo test to verify the estimator’s consistency.

Copyright © 2016 by ASME
Your Session has timed out. Please sign back in to continue.

References

Tolmasquim, S. T., and Nieckele, A. O., 2008, “Design and Control of Pig Operations Through Pipelines,” J. Pet. Sci. Eng., 62(3–4), pp. 102–110. 0920-4105 10.1016/j.petrol.2008.07.002
Quarini, J., and Shire, S., 2007, “A Review of Fluid-Driven Pipeline Pigs and Their Applications,” Proc. Ins. Mech. Eng., Part E: J. Proc. Mech. Eng., 221(1), pp. 1–10. [CrossRef]
Zhu, X., Zhang, S., Li, X., Wang, D., and Yu, D., 2015, “Numerical Simulation of Contact Force on Bi-Directional Pig in Gas Pipeline: At the Early Stage of Pigging,” J. Nat. Gas Sci. Eng., 23, pp. 127–138. 10.1016/j.jngse.2015.01.034
Podgorbunskikh, A. M., 2008, “Devices for Automated Regulation of the Velocity of In-Tube Pig Flaw Detectors (Review),” Russ. J. Nondestr. Test., 44(5), pp. 343–350. 1061-8309 10.1134/S1061830908050070
Lee, D.-H., Moon, H., and Choi, H.-R., 2011, “Autonomous Navigation of In-Pipe Working Robot in Unknown Pipeline Environment,” 2011 IEEE International Conference on Robotics and Automation (ICRA), IEEE Robotics and Automation Society, Shanghai, China, pp. 1559–1564.
Liu, Z., and Krys, D., 2012, “The Use of Laser Range Finder on a Robotic Platform for Pipe Inspection,” Mech. Syst. Sig. Proc., 31, pp. 246–257. 10.1016/j.ymssp.2012.03.006
Fallon, M. F., Folkesson, J., McClelland, H., and Leonard, J. J., 2013, “Relocating Underwater Features Autonomously Using Sonar-Based SLAM,” IEEE J. Oceanic Eng., 38(3), pp. 500–513. 0364-9059 10.1109/JOE.2012.2235664
Jaradat, M. A., and Abdel-Hafez, M. F., 2014, “Enhanced, Delay Dependent, Intelligent Fusion for INS/GPS Navigation System,” IEEE Sens. J., 14(5), pp. 1545–1554. 10.1109/JSEN.2014.2298896
Abdel-Hafez, M. F., 2012, “On the GPS/IMU Sensors’ Noise Estimation for Enhanced Navigation Integrity,” Math. Comput. Simul., 86, pp. 101–117. 0378-4754 10.1016/j.matcom.2010.03.005
Zhao, H., and Wang, Z., 2012, “Motion Measurement Using Inertial Sensors, Ultrasonic Sensors, and Magnetometers With Extended Kalman Filter for Data Fusion,” IEEE Sens. J., 12(5), pp. 943–953. 1530-437X 10.1109/JSEN.2011.2166066
Saadeddin, K. M., Abdel-Hafez, M. F., and Jarrah, M. A., 2014, “Estimating Vehicle State by GPS/IMU Fusion With Vehicle Dynamics,” J. Intell. Rob. Syst., 74(2), pp. 147–172. 0921-0296 10.1007/s10846-013-9960-1
Abdel-Hafez, M. F., 2014, “Detection of Bias in GPS Satellites’ Measurements: A Probability Ratio Test Formulation,” IEEE Trans. Control Syst. Technol., 22(3), pp. 1166–1173. 1063-6536 10.1109/TCST.2013.2267093
Emran, B. J., Al-Omari, M., Abdel-Hafez, M. F., and Jaradat, M. A., 2015, “Hybrid Low-Cost Approach for Quadrotor Attitude Estimation,” ASME J. Comput. Nonlinear Dyn., 10(3), p. 031010. 10.1115/1.4028524
Jin, S., and Ping, Y., 2011, “Research on the Describing of Trajectory for Subsea Pipeline Based on Inertial Navigation System,” 2011 IEEE Power Engineering and Automation Conference, IEEE Beijing Section, Wuhan, China, pp. 463–468.
Beiter, S., Poquette, R., Filipo, B. S., and Goetz, W., 1998, “Precision Hybrid Navigation System for Varied Marine Applications,” Position Location and Navigation Symposium, IEEE, New York, pp. 316–323.
Sadovnychiy, S., 2000, “Automation System for Pipelines Plan Reconstruction, Industrial Electronics,” Proceedings of the IEEE International Symposium on ISIE, 2, pp. 762–765.
Porter, T. R., Knickmeyer, E. H., and Wade, R. L., 1990, “Pipeline Geometry Pigging: Application of Strapdown INS,” Position Location and Navigation Symposium, IEEE PLANS ‘90, IEEE, Las Vegas, NV, pp. 353–358.
Santana, D. D. S., Maruyama, N., and Furukawa, M. C., 2010, “Estimation of Trajectories of Pipeline PIGs Using Inertial Measurements and Nonlinear Sensor Fusion,” 9th IEEE/IAS International Conference on Industry Applications (INDUSCON), IEEE South Brazil Section, Sao Paulo, Brazil, pp. 1–6.
Santana, D. D. S., 2011, “Navegação Terrestre Usando Unidade de Medição Inercial de Baixo Desempenho e Fusão Sensorial com Filtro de Kalman Adaptativo Suavizado,” Ph.D. Dissertation, EPUSP, São Paulo, Brazil.
Bar-Shalom, Y., and Li, X. R., 2001, Estimation with Applications to Tracking and Navigation: Theory, Algorithms and Software, John Wiley and Sons, Hoboken, NJ.
MIDG II INS/GPS Combined Inertial Navigation and GPS Unit, Omni Instruments Inc., 2015, http://www.omniinstruments.co.uk/products/product/moredetails/midg.id107.html, Jan. 2015.

Figures

Grahic Jump Location
Fig. 1

MIDG II INS/GPS unit

Grahic Jump Location
Fig. 2

Path traveled in experiment

Grahic Jump Location
Fig. 3

Odometer simulation from experimental data

Grahic Jump Location
Fig. 4

Speedometer simulation from experimental data

Grahic Jump Location
Fig. 5

Estimation using speedometer only

Grahic Jump Location
Fig. 6

Position and velocity standard deviation

Grahic Jump Location
Fig. 7

100-run Monte Carlo position errors

Grahic Jump Location
Fig. 8

Estimation using speedometer and reference stations that are 500 m spaced

Grahic Jump Location
Fig. 9

Position and velocity standard deviation

Grahic Jump Location
Fig. 10

100-run Monte Carlo position errors

Grahic Jump Location
Fig. 11

Estimation using speedometer and reference stations every 100 m

Grahic Jump Location
Fig. 12

Position and velocity standard deviations

Grahic Jump Location
Fig. 13

100-run Monte Carlo simulation

Grahic Jump Location
Fig. 14

Position estimate using speedometer and update points every 10 m

Grahic Jump Location
Fig. 15

Position and velocity standard deviations

Grahic Jump Location
Fig. 16

Monte Carlo simulation for 100 runs

Tables

Errata

Discussions

Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Articles from Part A: Civil Engineering
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In