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Design of a wheeled-type In-Pipe Inspection Robot to overcome motion singularity in curved pipes.

Authors :
Sugin Elankavi, Rajendran
Dinakaran, D.
Doss, Arockia Selvakumar Arockia
Kuppan Chetty, R.M.
Ramya, M.M.
Source :
Journal of Ambient Intelligence & Smart Environments; 2024, Vol. 16 Issue 1, p43-55, 13p
Publication Year :
2024

Abstract

This paper discusses the development and design of two wheeled-type In-Pipe Inspection Robots (IPIRs), Kuzhali I and Kuzhali II, which were created to address the limitations of traditional human inspection methods and earlier robot designs. Specifically, the robots aim to overcome the motion singularity experienced by IPIRs when navigating through curved pipes. Kuzhali I was developed with wheels mounted at an asymmetric angle, which enables the wheels to maintain contact with the pipe's surface, preventing motion singularity. However, Kuzhali I had limitations due to its prismatic mechanism, and thus Kuzhali II was developed with a telescopic mechanism to allow it to pass through vertical pipes with obstacles. Motion analysis was conducted on both robots to demonstrate how they overcome motion singularity and navigate through straight and curved pipelines. Simulation results showed that the forces acting on the robots' wheels fell within 5 N to 12 N, demonstrating stability while navigating pipeline junctions. Experimental tests were conducted on Kuzhali II, and the results were compared to simulation results, showing an error of less than 5%. The results of the experiments indicate that Kuzhali II is safe to use for pipeline inspection, can navigate through vertical pipelines with ease and can overcome motion singularity in curved pipes. These robots offer a faster, more accurate, and safer alternative to human inspection, which can reduce the risk of pipeline failures and associated environmental and safety hazards. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
18761364
Volume :
16
Issue :
1
Database :
Complementary Index
Journal :
Journal of Ambient Intelligence & Smart Environments
Publication Type :
Academic Journal
Accession number :
176365856
Full Text :
https://doi.org/10.3233/AIS-220247