چكيده به لاتين
In the civil engineering community, the need for effective monitoring of the health of structures during their useful life has been accepted. Accidents such as earthquakes, storms and explosions can severely damage the infrastructure of the building. These cases have caused the identification of damage to the structure (severity, type, time and place of damage) and structural health monitoring as one of the most important issues in engineering sciences, including civil engineering.
One of the methods that has been considered today is the methods of damage detection based on the vibration of the structure. These methods, using the modal properties, are trying to identify the failure of the structures. In these methods, damage can be defined as a reduction of Stiffness, which affects the modal properties of the structure. Therefore, causing damage to the structure results in changes in the dynamic characteristics, including the natural frequencies, the felexibility matrix, and the mode shape.
As stated above, structural damage are mainly interpreted as local stiffness reduction at the site of damage, many researchers have tried to use the felexibility matrix of the structure, which, in terms of measuring accuracy, has better conditions than the Stiffness matrix, as A method for troubleshooting structures. The felexibility matrix advantage of the hard matrix is that since the matrix of inverse softness is a Stiffness matrix, it contributes less to the higher frequency Stiffness matrix and low frequencies. In the real world, the frequencies of lower modes can be more accurately calculated, so using a felexibility matrix instead of a Stiffness matrix for specifying systems, detecting damage, and finding the location of damage is a better choice. The location of the damage can be detected using the estimate of felexibility matrix change before and after injury.
In structural engineering, optimization in a wide range of topics including design and optimization of structures, location detection and severity of member failure, and many other areas are applicable. The optimization topic involves a wide range of methods that mathematical optimization, component optimization, and optimization of the meta-analysis are among the most important ones. Fractional methods include a wide range, mostly inspired by nature. Gray wolf algorithm is one of the most effective methods used in this study. Fractional algorithms are able to find the right answer, not necessarily the best answer, at a relatively small time for large and complex issues. One of these methods is to identify damage in structures.
In this thesis, we introduce a method for determining the location and calculating the amount of damage in structures based on the softness matrix and angular velocity of the damaged structure using the model update. The proposed method determines the position and amount of structural failure using optimization of the cost function with the gray wolf algorithm.
Three examples of varying degrees of damage, different scenarios of damage and the effect of noise on modal data are investigated. The results show the successful and effective performance of the proposed method in determining the severity and location of the failure.
Keywords: damage detection, model updating , optimization algorithms, cost function.
