Development of an adaptive pipe inspection robot with rust detection

• Main Authors: Bandala, Argel A., Maningo, Jose Martin Z., Jose, John Anthony C., Fernando, Arvin H., Vicerra, Ryan Rhay P., Antonio, Micah Antoinette B., Diaz, Julianne Alyson I., Ligeralde, Manuel I., Jr., Mascardo, Philix Anton R.
• Format: text
• Published: Animo Repository 2018
• Subjects: Pipelines—Corrosion; Pipelines—Maintenance and repair; Mobile robots; Electrical and Computer Engineering; Electrical and Electronics
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/1390; https://animorepository.dlsu.edu.ph/context/faculty_research/article/2389/type/native/viewcontent
• Institution: De La Salle University

In response to addressing the issue of pipe quality checking, the researchers developed an adaptive in-pipe inspection robot that is able to detect rust. The robot is traversed in a pipe network of horizontal, vertical, elbow, and tee type with diameters of 8, 10 and 12 inches for all. Hence, the test features the versatility, adaptability, and robustness of the robot. As for the leg expansion of the robot, it is inspired by the scissors mechanism that is achieved by using of linked, folding supports in a crisscross pattern. In this paper, the traversing of the robot was supported in both simulation and actual testing, wherein it yield a 97.2167% success rate on the site. Likewise, Rust Detection proved to be successful with its high percentage accuracy of 95%. Given the obtained data and results, the researchers were able to go beyond their target objective of 70%. © 2018 IEEE.