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Development of Virtual Pipe Simulation System for Inspection Robot Design

Part of: Systems Engineering

Published online by Cambridge University Press:  26 July 2019

Satoshi Miura ,
Kazuya Kawamura ,
Masakatsu Fujie ,
Shigeki Sugano  and
Tomoyuki Miyashita
Satoshi Miura
Affiliation:
Waseda University;
Kazuya Kawamura
Affiliation:
Chiba University
Masakatsu Fujie
Affiliation:
Waseda University;
Shigeki Sugano
Affiliation:
Waseda University;
Tomoyuki Miyashita
Affiliation:
Waseda University;

Abstract

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Pipe inspection robots have been developed to reduce the cost and time required for gas pipe inspection. However, these robots have been developed using a scrap and build method and are not used in practice. In this paper, we propose a method of virtual pipe inspection simulation to clarify the parameters that are important in increasing the robot's ease of use. This paper presents the results obtained by a feasibility study with regard to pipe simulation. We developed a virtual pipe by simulating eight actual turns of an external gas pipe, and a robot equipped with camera at the tip. In the experiments, three individuals working in the field of gas inspection carried out the operation. We obtained questionnaire, time, and brain activity data. The results revealed various important points that must be considered in practical simulation and robot design. In conclusion, the virtual pipe simulation can be useful in developing the design of a pipe inspection robot.

Keywords

SimulationDesign for interfacesHuman behaviour in designInfrastructure
Type
Article
Information
Proceedings of the Design Society: International Conference on Engineering Design , Volume 1 , Issue 1 , July 2019 , pp. 3611 - 3620
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Author(s) 2019

References

Bertetto, A.M. and Ruggiu, M. (2001), “In-pipe inch-womn pneumatic flexible robot”, IEEVASME International Conference on Advanced Intelligent Mechatronics Proceedings, pp. 1226–1231.Google Scholar
Carrieri, M., et al. (2016), “Prefrontal Cortex Activation Upon a Demanding Virtual Hand-Controlled Task: A New Frontier for Neuroergonomics”, Frontiers in Human Neuroscience, Vol. 10 No. February, pp. 1–13. https://doi.org/10.3389/fnhum.2016.00053Google Scholar
Cha, Y.J., et al. (2018), “Autonomous Structural Visual Inspection Using Region-Based Deep Learning for Detecting Multiple Damage Types”, Computer-Aided Civil and Infrastructure Engineering, Vol. 33 No. 9, pp. 731–747. https://doi.org/10.1111/mice.12334Google Scholar
Cheraghi, N., Zou, G.P. and Taheri, F. (2005), “Piezoelectric-based degradation assessment of a pipe using fourier and wavelet analyses”, Computer-Aided Civil and Infrastructure Engineering, Vol. 20 No. 5, pp. 369–382. https://doi.org/10.1111/j.1467-8667.2005.00403.xGoogle Scholar
Cole, I.S. and Marney, D. (2012), The science of pipe corrosion: A review of the literature on the corrosion of ferrous metals in soils, Corrosion Science. Elsevier Ltd, Vol. 56, pp. 5–16. https://doi.org/10.1016/j.corsci.2011.12.001Google Scholar
Dridi, L., et al. (2008), “Using evolutionary optimization techniques for scheduling water pipe renewal considering a short planning horizon”, Computer-Aided Civil and Infrastructure Engineering, Vol. 23 No. 8, pp. 625–635. https://doi.org/10.1111/j.1467-8667.2008.00564.xGoogle Scholar
Duchesne, S., et al. (2013), “A Survival Analysis Model for Sewer Pipe Structural Deterioration”, Computer-Aided Civil and Infrastructure Engineering, Vol. 28 No. 2, pp. 146–160. https://doi.org/10.1111/j.1467-8667.2012.00773.xGoogle Scholar
Esposito, S., et al. (2015), “Simulation-Based Seismic Risk Assessment of Gas Distribution Networks”, Computer-Aided Civil and Infrastructure Engineering, Vol. 30 No. 7, pp. 508–523. https://doi.org/10.1111/mice.12105Google Scholar
Fukuda, T. and Engneering, M. (1989), “Rubber Gas Actuator Driven by Hydrogen Storage Alloy for In-pipe Inspection Mobile Robot with Flexible Structure”, Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pp. 1–6.10.1109/ROBOT.1989.100242Google Scholar
Gas Pipe Overview (2018), Tokyo Gas, Available at: https://home.tokyo-gas.co.jp/gas/koji/zentaizou.htmlGoogle Scholar
Hawkes, E.W., et al. (2017), “A soft robot that navigates its environment through growth”, Science Robotics, Vol. 2 No. 8, pp. 1–8. https://doi.org/10.1126/scirobotics.aan3028Google Scholar
Hsu, L. and Mohan, S. (1991), “Computer Aided Configuration of Pipe Systems in Buildings”, Computer-Aided Civil and Infrastructure Engineering, Vol. 6 No. 1, pp. 15–26. https://doi.org/10.1111/j.1467-8667.1991.tb00394.xGoogle Scholar
Iyer, S. and Sinha, S.K. (2006), “Segmentation of pipe images for crack detection in buried sewers”, Computer-Aided Civil and Infrastructure Engineering, Vol. 21 No. 6, pp. 395–410. https://doi.org/10.1111/j.1467-8667.2006.00445.xGoogle Scholar
Komori, M. and Suyama, K. (2012), “Inspection robots for gas pipelines of Tokyo Gas”, Advanced Robotics, Vol. 1864 No. 2001, https://doi.org/10.1163/156855301300235922Google Scholar
Matsuzaka, Y., et al. (2012), “Neuronal activity in the primate dorsomedial prefrontal cortex contributes to strategic selection of response tactics”, Proceedings of the National Academy of Sciences, Vol. 109 No. 12, pp. 4633–4638. https://doi.org/10.1073/pnas.1119971109Google Scholar
Najjaran, H., Sadiq, R. and Rajani, B. (2006), “Fuzzy expert system to assess corrosion of cast/ductile iron pipes from backfill properties”, Computer-Aided Civil and Infrastructure Engineering, Vol. 21 No. 1, pp. 67–77. https://doi.org/10.1111/j.1467-8667.2005.00417.xGoogle Scholar
Ogai, H. and Bhattacharya, B. (2018), Pipe Inspection Robots for Structural Health and Condition Monitoring, Springer.Google Scholar
Schoefs, F., et al. (2009), “Comparison of additional costs for several replacement strategies of randomly ageing reinforced concrete pipes”, Computer-Aided Civil and Infrastructure Engineering, Vol. 24 No. 7, pp. 492–508. https://doi.org/10.1111/j.1467-8667.2009.00603.xGoogle Scholar
Sinha, S.K., Fieguth, P.W. and Polak, M.A. (2003), “Computer vision techniques for automatic structural assessment of underground pipes”, Computer-Aided Civil and Infrastructure Engineering, Vol. 18 No. 2, pp. 95–112. https://doi.org/10.1111/1467-8667.00302Google Scholar
Sinha, S.K. and Pandey, M.D. (2002), “Probabilistic neural network for reliability assessment of oil and gas pipelines”, Computer-Aided Civil and Infrastructure Engineering, Vol. 17 No. 5, pp. 320–329. https://doi.org/10.1111/1467-8667.00279Google Scholar
Sutoa, T., et al. (2004), “Mulitchannel Near-infrared Spectroscopy in Depression and Schizophrenia”, Biological Psychiatry, Vol. 55 No. 1, pp. 501–511.Google Scholar
Sutoko, S., et al. (2016), “Tutorial on platform for optical topography analysis tools”, Neurophotonics, Vol. 3 No. 1, pp. 010801. https://doi.org/10.1117/1.NPh.3.1.010801Google Scholar
Tran, D.H., Perera, B.J.C. and Ng, A.W.M. (2009), “Comparison of structural deterioration models for stormwater drainage pipes”, Computer-Aided Civil and Infrastructure Engineering, Vol. 24 No. 2, pp. 145–156. https://doi.org/10.1111/j.1467-8667.2008.00577.xGoogle Scholar
Videoscopes and Borescopes IPLEX RX/IPLEX RT (2018), Olympus, Available at: https://www.olympus-ims.com/en/rvi-products/iplex-rx/.Google Scholar