Detecting cracks on the surface of bridge piers is critical to the health condition of bridges. Aiming at the limitations of existing unmanned aerial vehicles (UAVs) and climbing robots, this research proposes a ring-climbing visual scanning operation robotic disease acquisition system, which achieves entire region, high-definition, and fast acquisition of cracks on bridge piers surfaces. In addition, a crack segmentation network based on an efficient self-attention mechanism and a refined segmentation algorithm are proposed to achieve accurate detection and quantification of cracks on bridge piers. Finally, an experimental prototype was built, and experiments were conducted. The results show that the maximum error of crack quantification is within 0.1 mm. The designed ring-climbing visual scanning operation robotic disease acquisition system can be applied to the surface of any pier with a 1.2 to 1.5 m diameter, which is of great significance for the automatic detection of the health condition of bridge piers.