Most structural failures are due to break in consisting materials. These breaks begin with a crack, the extension of which is a serious threat to the behaviour of structure. Thus the methods of distinguishing and showing cracks are the most important subjects being investigated. In this article, a new smart portable mechanical system to detect damage in beam structures via using fuzzy-genetic algorithm is introduced. Acceleration-time history of the three points of beam is obtained. The signals are then decomposed into smaller components using new EMD (Empirical Mode Decomposition) method with every IMF containing a specific range of frequency. The dominant frequencies of the structure are obtained from these IMFs using Short-term Fourier transform. Subsequently, a new method of damage detection in simply supported beams is introduced based on fuzzy-genetic algorithm. The new method is capable of identifying the location and intensity of the damage. This algorithm is developed to detect the location and intensity of the damage along the beam, which can detect the damage location and intensity based on the pattern of beam frequency variations between undamaged and damaged states.
Wavelet Transform (WT) and Wavelet Packet Transform (WPT) approaches have shown great promise in the field of signal analysis in recent decades. The main merit of these methods is their capability in localization of each signal in distinct time or space interval. However, the frequency resolution of such transformation is relatively poor in high frequency regions. The WPT, which is an extended form of the WT, provides a complete level-by-level signal decomposition. Therefore, a frequency analysis creates an arbitrary time. In this study, dynamic transient analysis is performed employing a finite element software (ANSYS) on a beam and acceleration time history of various points is investigated. Then, the captured signals are decomposed to the wavelet packet components using MATLAB and energy rate index is calculated for each component utilizing a wavelet packet rate index (WPERI). The results indicate that not only are the obtained index values sensitive, but they also are precise for the crack identification.
In this paper, a new intelligent portable mechanical system is introduced experimentally and theoretically to detect damage employing the fuzzy-genetic algorithm and EMD. For this purpose, the acceleration-time history is obtained from three points of a simply-supported beam utilizing accelerometer sensors. The gained signal is decomposed into small components by using an EMD method. Each decomposed component contains a specific frequency range. Finally, the proposed algorithm is designed to find the location and severity of damage through the frequency variation pattern among the safe and the damaged beam.
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