The main cable of suspension bridges is subject to corrosion and requires advanced anti-corrosion technology. Consequently, the internal airflow of the main cable has become a significant research focus. This study employs image processing and machine learning to analyze the cross-sectional images of the main cable and reveals the distribution characteristics of pores and fractures within the main cable cross-section. The numerical simulation model of the main cable is divided into inner and outer parts based on porosity, with porosity levels of 18.16% and 32.11%, respectively. Fractures randomly occurred in the inner part, with a probability of 31.37%. A simulation model based on fractured porous media (FPM) is developed, which innovatively incorporates the fracture flow model into the numerical simulation of the internal airflow of the main cable. The numerical simulation clearly explores the intricate details of the internal flow field of the main cable, revealing that the existence of fractures has a great impact on the internal flow field of the main cable. Additionally, the relative deviation of specific frictional head loss between the field experiment and numerical simulation is about 6.83%, indicating that the numerical simulation results are relatively reliable.