To address the challenge of automated detection of void of the steel-concrete structures interfaces, this paper designs a magnetic wall-climbing robot incorporating image and acoustic feature recognition. First, we introduce the robot’s chassis, magnetic suction device, power system, drive system, and mapping and sound modules. Next, we discuss the robot’s hardware control system and detemine the feasibility of using Neodymium-iron-boron permanent magnet for adsorption force through force analysis and experimental testing. Finally, the composition and functions of the image and acoustic feature recognition software part are detailed. Among them, the image capturing part adopts the image transmission solution based on the Orange Pie platform. The acoustic pattern recognition module consists of front-end, middle-end and back-end architecture: the front-end carries percussion and recording devices for excitation and collection of acoustic patterns; the middle-end of the acoustic pattern recognition WeChat mini program is developed to achieve acoustic pattern noise removal and effective feature extraction; the back-end, through the cooperation of Tencent Cloud and the WeChat mini program, recognizes acoustic pattern data and returns the results to the WeChat mini program. The magnetic wall-climbing robot incorporating image and acoustic feature recognition designed in this paper can achieve the collaborative acquisition and analysis of image and acoustic patterns, providing an effective solution for the automated inspection of steel-concrete and other structural interfaces for debonding.