A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Abstract It is well known that damaged structural members may alter the behavior of the structures considerably. Careful observation of these changes has often been viewed as a means to identify and assess the location and severity of damages in structures. Among the responses of a structure, natural frequencies and natural modes are both relatively easy to obtain and independent from external excitation and, therefore, can be used as a measure of the structural behavior before and after an extreme event which might have led to damage in the structure. This chapter applies charged system search algorithm to the problem of damage detection using vibration data. The objective is to identify the location and extent of multi-damage in a structure. Both natural frequencies and mode shapes are used to form the required objective function. To moderate the effect of noise on measured data, a penalty approach is applied. A variety of numerical examples including beams, frames, and trusses are examined. The results show that the present methodology can reliably identify damage scenarios using noisy measurements and incomplete data [1].
Abstract It is well known that damaged structural members may alter the behavior of the structures considerably. Careful observation of these changes has often been viewed as a means to identify and assess the location and severity of damages in structures. Among the responses of a structure, natural frequencies and natural modes are both relatively easy to obtain and independent from external excitation and, therefore, can be used as a measure of the structural behavior before and after an extreme event which might have led to damage in the structure. This chapter applies charged system search algorithm to the problem of damage detection using vibration data. The objective is to identify the location and extent of multi-damage in a structure. Both natural frequencies and mode shapes are used to form the required objective function. To moderate the effect of noise on measured data, a penalty approach is applied. A variety of numerical examples including beams, frames, and trusses are examined. The results show that the present methodology can reliably identify damage scenarios using noisy measurements and incomplete data [1].
Damage Detection in Skeletal Structures Based on CSS Optimization Using Incomplete Modal Data
Kaveh, A. (author)
2016-12-02
11 pages
Article/Chapter (Book)
Electronic Resource
English
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