Franklin Open (Mar 2024)
Multi-objective design optimization of an in-pipe inspection robot
Abstract
In addition to inspection, In-Pipe Inspection Robots (IPIRs) could be enabled to perform other tasks, such as object retrieval and blockage clearing. In this study, a new IPIR is proposed with a design aimed at expanding its range of potential applications beyond inspection. The design methodology followed to facilitate the aforementioned application expansion commences with the development of a parametric preliminary design of an IPIR, in which the sizing of the robot parts are determined based on an optimization problem formulated in this work. The multi-objective optimization problem maximizes two contradictory objective functions, namely, its payload capacity, and the range of pipe diameters in which it can fit (radial range). The problem's Pareto front is solved using the NSGA-II implemented by Matlab's gamultiobj(.). The robot's final design is selected based on one of the Pareto-optimal solutions obtained from the Pareto front with a theoretical payload capacity of 11 kg and a radial range of 33 mm. The robot was manufactured and tested to validate such theoretical results.