Identification of a crack in a beam by the boundary element method

Lee, Jin‐Hee

doi:10.1007/s12206-010-0119-8

Cited by 13 publications

(4 citation statements)

References 20 publications

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“…Many authors have determined natural frequencies of mode shapes of bending vibration for the cracked beam to identify the crack. [8][9][10][11][12] A crack is represented by rotational spring in the beam to model the jump in slope caused by the local flexibility at the crack location, and in case of no crack, the local flexibility is zero or rotational spring stiffness is infinity. 13 Sayyad and Kumar 14 carried out theoretical and experimental vibration analysis for cracked simply supported beam.…”

Section: Introductionmentioning

confidence: 99%

Behavior of cracked Euler–Bernoulli beam and inverse problem for assessing crack severity

Soliman

2021

Noise & Vibration Worldwide

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In this present study, natural frequencies of the first two modes of bending vibration for the cracked simply supported Euler–Bernoulli beam is determined using finite element analysis (FEA). FEA natural frequencies for the cracked beam are used to investigate the behavior of the cracked beam and also used in the inverse problem of crack depth detection. Dynamic behavior of the cracked simply supported beam is observed, and it is found that normalized mode shape at crack location has great effect on amount of decreasing of natural frequencies. When normalized mode shape at crack location is increased, then natural frequencies decrease. In this study, pattern of mode shape played a vital role in decreasing or increasing natural frequencies. At the midpoint of the beam, there is largest bending moment in first bending mode and there is nodal point in second bending mode. Harmonic analysis for the cracked simply supported beam is carried out to find von Mises stress responses and appearance of peaks at frequency of first bending mode is noticed in graphs of von Mises stress response, expressing high values of von Mises stress at crack tip. Inverse problem of assessing the crack depth is performed using results of FEA first mode frequency ratio and published experimental results and the method showed good results in case of high crack depth ratios.

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Section: Introductionmentioning

confidence: 99%

Behavior of cracked Euler–Bernoulli beam and inverse problem for assessing crack severity

Soliman

2021

Noise & Vibration Worldwide

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“…There are two main fields in damage detection. One field is applying the dynamic wave to the structures to compare the differences between healthy and nonhealthy structures [4][5][6][7][8][9][10][11][12][13]. The other field is the identification of defects by using static response [14][15][16][17][18][19][20][21][22], that is applying directional loading to the structures.…”

Section: Introductionmentioning

confidence: 99%

Hardware-In-The-Loop Simulations of Hole/Crack Identification in a Composite Plate

Liang

Sun

2020

Materials

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The technology of hardware-in-the-loop simulations (HILS) plays an important role in the design of complex systems, for example, the structural health monitoring (SHM) of aircrafts. Due to the high performance of personal computers, HILS can provide practical solutions to many problems in engineering and sciences, especially in the huge systems, giant dams for civil engineering, and aircraft system. This study addresses the HILS in hole/crack identification in composite laminates. The multiple loading modes method is used for hole/crack identification. The signals of strains measured from the data-acquisition (DAQ) devices are accomplished by the graphical software LabVIEW. The results represent the actual responses of multiple loading mode tests of real specimens. A personal computer is employed to execute the identification work according to the strain data from DAQ devices by using a nonlinear optimization approach. When all the criteria are satisfied, the final identification results will be obtained. HILS will achieve real time identification of hole/crack in the composite plate by using the actual response measured from the sensors. Not only the size, but also the location and orientation of the crack/hole in a composite plate are successfully identified herein.

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“…beforehand, at that point, a structure is harmed, or complexities in the harm levels or ranges [7].The crack detection technique depends on the way that an enclosed crack in an empty area brings mutual vibration amongst bending and longitudinal vibrations [8], and in this way, an additional resonant peak appears in the FRF (frequency response function) of the beam with a crack. This strategy is able to detect the presence of cracks, however, it is hard to anticipate the location parameters and depth of the crack particularly while numerous cracks exist [9]. All together for identifying the parameters of the crack precisely through this methodology, initially a cracked-beam component is created for the cracked beams with express portrayals of the crack parameters, including the seriousness of the crack and its relative area inside a component [10,11].…”

Section: Introductionmentioning

confidence: 99%

Optimal Method for Identification of Cracks in Different Beams using Fuzzy with Elephant Based Neural Network

Pitchaiah*,

Rao

2019

IJITEE

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Failure of Structures i.e., beams can be avoided by identifying the damage in the structure at its beginning and proper retrofitting. Recently, the researchers created a structure to recognize crack damage using a cracked beam component model that originates from the fracture mechanics and local flexibility rules. The present work exhibits the analysis of cracked beam with a machine learning model to assess the stiffness of the structure. Here Fuzzy Optimal Neural Network (FONN) is considered, in addition, the stiffness reduction technique, especially concerning thick beams, is featured with a survey of other crack models. The extricated model data are utilized to conversely recognize the cracks with the cracked beam component model through a model updating technique. The optimal Neural Network based stiffness computation utilizes a global searching procedure using Adaptive Elephant Herding Optimization (AEHO) to identify the number of cracks in various beams. From the proposed model, the attained results are compared with the existing research work, and other optimization and machine learning models.

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Identification of a crack in a beam by the boundary element method

Cited by 13 publications

References 20 publications

Behavior of cracked Euler–Bernoulli beam and inverse problem for assessing crack severity

Behavior of cracked Euler–Bernoulli beam and inverse problem for assessing crack severity

Hardware-In-The-Loop Simulations of Hole/Crack Identification in a Composite Plate

Optimal Method for Identification of Cracks in Different Beams using Fuzzy with Elephant Based Neural Network

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