Safety assessment of scaffolding support systems under construction loads: Experimental and numerical investigation

• Safety factor formula considering corrosion-load-vibration synergies was proposed. • A novel finite element models incorporating non-uniform corrosion geometry were developed. • A convolutional neural network (CNN) for corrosion damage identification was established. In order to explore the safety and reliability of the scaffolding support system under construction load, the static and dynamic performance of the scaffolding support system during construction is studied by means of experimental research and theoretical analysis. The static and dynamic data of scaffolding support system are measured by installing axial force meter, strain meter, displacement meter, dip meter, and acceleration sensor. ABAQUS software is used to simulate the displacement and stress of the scaffolding support system with different corrosion degrees. The test results show that the stress distribution of the support system tends to be uneven with the increasing corrosion levels, and the anti-overturning ability of the structure is greatly reduced and the collapse risk is increased. When the corrosion level is 8%, the ultimate bearing capacity of scaffolding support system is reduced by about 28.1%, and the overall deformation capacity and stiffness of the structure are reduced by 9.5%. The frequency of the scaffolding support system increases with the increase of load, and the vibration velocity and acceleration velocity of the scaffold increase with the increase of load. Based on the test data, the formula for calculating the safety factor of the support system was obtained. When the overall deflection increases to 11.5mm, the safety factor of the support system decreases by 23.8%. Finally, the collapse resistance analysis and rust damage identification method of scaffolding support system were obtained, and the research can provide a reliable calculation method for the construction safety of the scaffolding support system.