仿生主动式曲面真空吸附桥梁爬壁裂缝检测机器人设计

Design of Wall-climbing Bridge Crack Detection Robot with Bionic Active Curved Surface Vacuum Adsorption Mechanism

摘要:

针对桥梁检测中人工效率低、机器人环境适应性差的问题，提出一种具有仿生主动式曲面真空吸附机构的爬壁机器人。通过融合改进YOLO算法模型，实现了裂缝长度（±1 mm）、宽度（±0.2 mm）的高精度检测。机器人采用模块化设计，集成三自由度机械臂与真空吸附系统，负载能力达9 kg，可在复杂曲面桥墩稳定作业。实验表明：该机器人在曲面桥墩的吸附成功率为95%，裂缝检出率超过90%，显著提升了桥梁检测的智能化水平与安全性。

Abstract:

To address the low manual efficiency and poor environmental adaptability of robots in bridge inspection, a wall?climbing robot equipped with a bionic active curved?surface vacuum?adsorption mechanism is proposed. By integrating a modified YOLO algorithm model, the high?precision detection of crack length (±1 mm) and width (±0.2 mm) is realized. The robot adopts a modular design, integrating a three-degree-of-freedom mechanical arm and a vacuum adsorption system. With a load capacity of up to 9 kg, it can operate stably on complex curved surface bridge piers. The experimental results show that the adsorption success rate of this robot on curved bridge piers is 95%, and the crack detection rate exceeds 90%, which significantly enhance the intelligent level and safety of bridge inspection.