Work place: Department of Civil Engineering, Islamic Azad University, Central Tehran Branch, Tehran, Iran
E-mail: h.rouhollahpour@gmail.com
Website:
Research Interests: Engineering, Computational Engineering
Biography
H. Rouhollah Pour, received the M.Sc. degree in civil engineering from the Department of Civil Engineering, College of Technical and Engineering, Islamic Azad University Central Tehran Branch, Iran, in 2017. The current researches include steel construction design, fault detection for applications to Structures Health Monitoring (SHM), earthquake estimation.
By H. Rouhollah Pour J. Asgari Marnani A. A. Tabatabei
DOI: https://doi.org/10.5815/ijigsp.2018.04.01, Pub. Date: 8 Apr. 2018
The first step in Structures Health Monitoring (SHM), are determining the location, intensity and type of damage in structures. Crack is a damage that often occurs in structural elements and may cause serious ruptures in the structure. One of the important approaches is the wavelet analysis of vibration modes structures. In this study, it has been performed the crack detection method in steel cantilever beam structure, using an optimized wavelet-based model. The wavelet analysis has been performed based on the higher orders of the structure’s mode shapes. The results show that the proposed method is able to accurately detect all kinds of cracks, in which the cracks location are variable. In this study also, cracks with length of 20%, 10%, 5% and 2% of the beam’s depth have been considered and one of the most prominent results is introducing a method for detecting robust and environmental noisy cracks. The proposed method is capable of accurately detecting crack in the cantilever beams in noisy conditions about 20 dB of SNR.
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