Static Damage Identification Of Long-Span Cable-Stayed Bridge Based On Support Vector Machines

Due to a wide variety of unforeseen conditions and circumstance, it will never be possible or practical to design and build a structure that has a zero percent probability of failure during the bridge operation. Structural aging, environmental conditions, and frequent load action are examples of circumstances that could affect the reliability and the life of a structure. The significance of developing a long-term monitoring system for a large-scale bridge is that it is really able to provide information for evaluating structural integrity, durability and reliability throughout the bridge life cycle and ensuring optimal maintenance planning. As the core of bridge health monitoring system, the damage identification theory is active area of research in recent years.The state of arts and purposes of bridge damage identification are introduced firstly, and the support vector machines theory is discussed systematically. Then the support vector machines method is adopted in the damage identification of long-span cable-stayed bridge and the good identification effect is obtained. The specific studies are listed as follows:1. The basic characteristics and research status of static damage identification are briefly introduced, and the solution is also proposed for static damage identification of cable-stayed bridge.2. The long-span cable-stayed bridge is taken as the example, according to the analysis of vulnerability and the comparision of damage indexs, the vulnerable parts of the structure and the reasonable damage indexs are determined.3. The support vector classification and support vector regression are adopted respectively to locate and quantify the damage. The damage identification result which under the different conditions is compared with each other and the influence of different noise level is also considered.4. The static damage identification results are verified on the basis of the measured data. The main works and the research results are summarized, and some improved testing methods for the bridge damage identification are put forward at last.