Study On Damage Detection Of The Concrete-filled Steel Tube Arch Bridge

The concrete-filled steel tube arch bridge inevitably suffers from the different damages such as craking and aging etc. during the service life, which may result in disastrous consequences. In order to insure safety of the people's health and wealth, the effective damage identification and safety evaluation is important for bridge operation. Therefore, these considerations have motivated research for the damage identification and health diagnosis of the concrete-fileed steel tube arch bridge.The dynamic characteristic of structures has a direct relationship with structural parameters, and structural damage can cause dynamic characteristics shifts correspondently. Therefore, if the mapping relationship between structural damage and dynamic characteristic shifts can be established, the damage can be diagnosed by using dynamic measurements of the structures. According to the measured date and identification principle, the identification methods can be divided into the method based on frequency, mode shape, and modal flexibility and so on. But all of those mainly focus on simple structures, it lacks the effective methods of damage identification for the concrete-filled steel tube arch bridgeThe concrete-filled steel tube arch bridge, Chang-qing Bridge in Shen Yang, is studied in this dissertation. Some methods of structural damage identification and neural network are respectively introduced, and the numerical simulation for the damage identification of Chang-qing Bridge is carried out.The article summarizes the research overview and the method of the dynamic diagnose firstly, then two new damage identification methods are proposed based on dynamic characteristic: fourth derivative of displacement mode and slope of flexibility difference. A zonal approach damage identification method is proposed for global identification of the concrete-filled steel tube arch bridge. The article discusses the basic principle and method of the damage diagnose on the basis of artificial neural network structure, then establishes a BP neural network to command the health status of bridge in commonly using state. The method consists of three-stage: â‘  damage alarming; â‘¡ damage localization; â‘¢ damage quantification. In the second stage, the structure is divided into two parts, and then the damage severity is identified respectively.The numerical results demonstrate that the proposed method can localize the structural damages for the Chang-qing Bridge. It is concluded that the proposed method is feasible for damage identification and safety evaluation of the concrete-filled steel tube arch bridge.