Optimization of Magnetic Adsorption Units for Wall‐Climbing Robots via Integrated Response Surface Methodology and Genetic Algorithm

ABSTRACT To address the requirement for stable adsorption of climbing robots in confined spaces during ship hull cleaning operations, this study proposes a multi‐objective optimization design method for arc‐shaped magnetic adsorption units based on the response surface method‐genetic algorithm. By analyzing the influence relationships among magnetic circuit topology, hull plate thickness, and air gap dimensions, the study reveals the superior performance of a five‐loop Hallbarth array within specific air gap ranges and identifies the nonlinear impact of arc angle on magnetic adsorption units. A multi‐parameter coupling optimization framework linking arc angle to permanent magnet geometric parameters has been established to determine the optimal configuration of permanent magnet structural parameters and arc angle. Experimental validation demonstrates a 15.37% increase in magnetic adsorption force per unit mass after optimization, with robotic stability confirmed through motion testing. This research holds significant value for achieving stable adsorption and engineering applications of wall‐climbing robots on ship hull surfaces.