Abstract:The health status identification of ATM sector can help to comprehensively understand air traffic operation situation, and has certain application value in ATC safety assessment, sector division and air traffic flow management. Based on the temporal and spatial characteristics of traffic flow in ATM sector, a sector control operation health identification method is established with the air traffic operational data. We established five health evaluation indicators for sector control operation, such as saturation degree, instantaneous saturation degree, retention degree, traffic demand of next 15 minutes, and ATC workload level. Then, the subjective and objective combination weighting method was used to determine the weight of each evaluation indicator. And then, the health classification method of the sector control operation was built with gray clustering theory and verified with the operation data of Xiamen No.1 sector. The results show that the health status is the result of the interaction between macroscopic dynamic characteristics and complicated microscopic features; the proposed method is effective and the calculation process is simple and feasible.