Issue 52

J. Akbari et alii, Frattura ed Integrità Strutturale, 52 (2020) 269-280; DOI: 10.3221/IGF-ESIS.52.21 270 I NTRODUCTION n recent years, structural damage detection is an interesting field for the researchers. From a practical point of view, proposing an effective non-destructive technique is a crucial task to maintain the safety and integrity of the structures. The previous studies [1] have reported that most of the non-destructive techniques could be categorized as local or global damage identification methods. Furthermore, with increasing the size and dimensions of the buildings or structural elements, the capabilities of traditional damage detection methods such as ultra-Sonic and X-ray tests or Schmidt's hammer are not practically possible. Because such methods require easy accessibility for testing and knowing the vicinity of the damage, which cannot be guaranteed in most cases in civil or mechanical engineering. As well, the health monitoring of large-scale structures is a time-consuming and costly process. The vibration-based damage identification method as a global technique is developed to overcome these difficulties. The main idea for vibration-based damage identification is that the damage-induced changes in the physical properties such as mass, damping, and stiffness will lead to detectable changes in natural frequencies, modal damping, and mode shapes. Therefore, with the appearance of modern computer facilities and digital signal processing techniques, new research on SHM has seriously been started. Ratcliffe [2] presented a structural health monitoring method that could identify the damage without requiring the modal data of the intact structure. He utilized the curve-fitting technique of mode shape's curvature in one-dimensional beams. In this discipline, Weng and Deng [3] used the wavelet transforms for the detection of small transverse cracks in static and dynamic loadings for pinned-pinned and clamped-free beams. Hou et. al. [4] examined wavelet capabilities for damage detection for a system with the mass and spring as a single degree of freedom model. They claimed that the wavelet has enough capability to identify the time of yielding of spring. Chang and Chen [5] conducted research on the Timoshenko beam based on wavelet distance. The proposed wavelet successfully recognized the damage on beams using the first and second mode shapes. Ovanesova and Suarez [6] utilized stationary discrete wavelet for detecting damages in beam and frame type structures. Loutridis et al. [7] carried- out the research for the detection of a crack in double beams using continuous wavelet transforms. Chang and Chen [8] studied a cantilever-type beam that the crack was an open crack that has been modeled using torsional spring. In their research, Gabor wavelet has been applied to the mode shapes, in order to find the crack location. Gökda ğ , H., & Kopmaz, O [9] conducted the research for identifying crack on beams by a combination of the continuous and discrete wavelet. In their research, the combination of the mode shapes of an intact and damaged beam has been taken into account under the errors of measurement and local damage. Ruka [10] studied the effects of higher modes in system identification utilizing discrete wavelet and showed that applying higher modes will result in better performance. Zhong and Oyadiji [11] considered the modal responses of damaged beams using the finite-element method and experimental data. The results showed that the discrete wavelet when the sampling rate is high could not obviously detect the details of the synthesized signal. In addition, in further research, Zhang and Oyadji [12] considered the reconstructed mode shapes for damaged beams using a discrete wavelet method. They could identify the damage with a 4% intensity for hinged support beams. Algaba et al. [13] defined a new damage index composed of natural frequency and mode shape for damage detection using continuous wavelet. The proposed method could not be able to identify low damages. Therefore, Solís et.al [14] developed a new damage index for low damages with 5% and 10% intensities. However, both indexes were not able to identify the damages for noisy conditions. Khorram et.al [15] implemented continuous wavelet and factorial texting techniques for the detection of multiple damages on beams. Cao.M, et.al [16-17] studied the damage detection for noisy data. In their research, the mode shape curvature polluted by noise with a given signal to noise ratio. When the wavelet transforms are not able to identify the damage, a combination of wavelet and Teager energy of signal could identify the damages with the intensity of 5 %. Akbari and Ahmadifarid [18] applied the discrete wavelet transform and energy operator for damage detection of the two-dimensional frames. There are two main reasons for the study on damage detection of simple structures like beams: (1) most of the structures or their major components in civil and mechanical engineering could be simplified as a beam or plate. (2) the problem of identifying specific damage in a beam/plate provides an important benchmark for the effectiveness and accuracy of the identification techniques. Therefore, in this paper, the damage identification of beam structures in different support conditions and also various damage scenarios have been carefully investigated. To the knowledge of the authors, multiple cracks usually cause damages with low intensity, which are difficult to be detected. This could be much more difficult when the damage is close to the supports. The authors believe that damage identification in such cases has not received enough attention and comprehensive studies in this regard is required. Therefore, this paper focuses on the evaluation of multiple cracks detection near the supports of the beams. I