Modeling for Detection of Degraded Zones in Metallic and Composite Structures

Ostachowicz, Wiesław; Krawczuk, Marek

doi:10.1002/9780470061626.shm066

Cited by 3 publications

(2 citation statements)

References 79 publications

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“…The deviation from 1 can be interpreted as a damage indicator in structures. This index is based on comparisons between the changes in the mode shapes obtained both from tests and from calculations, the MAC is defined by W. M. Ostachowicz et al 1996: (17) = Test mode shape vector. = calculate mode shape vector.…”

Section: Modal Assurance Criterionmentioning

confidence: 99%

Damage Detection and Assessment of Stiffness and Mass Matrices in Curved Simply Supported Beam Using Genetic Algorithm

Hadi¹,

Abdulkareem²

2023

jcoeng

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In this study, a genetic algorithm (GA) is used to detect damage in curved beam model, stiffness as well as mass matrices of the curved beam elements is formulated using Hamilton's principle. Each node of the curved beam element possesses seven degrees of freedom including the warping degree of freedom. The curved beam element had been derived based on the Kang and Yoo’s thin-walled curved beam theory. The identification of damage is formulated as an optimization problem, binary and continuous genetic algorithms(BGA, CGA) are used to detect and locate the damage using two objective functions (change in natural frequencies, Modal Assurance Criterion MAC). The results show the objective function based on change in natural frequency is the best objective and no error was recorded in prediction of location and small error in detecting damage value. Also the result show that the genetic algorithm method are efficient indicating and quantifying single and multiple damage with high precision, and the prediction error for the CGA are less than corresponding value for the BGA.

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Section: Modal Assurance Criterionmentioning

confidence: 99%

Damage Detection and Assessment of Stiffness and Mass Matrices in Curved Simply Supported Beam Using Genetic Algorithm

Hadi¹,

Abdulkareem²

2023

jcoeng

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“…The GA arithmetic is often used in determining collocation of sensors. Ostachawicz [1] et al demonstrated the use of GA in damage detection using a damage index as the fitness function. Staszweski [2] et al used GA to place sensors on a grid for damage detection.…”

Section: Introductionmentioning

confidence: 99%

Optimal Placement of Sensors for Damage Characterization Using Genetic Algorithms

Yan

Chen

Jiang

2007

KEM

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Sensor data are the basis for health assessment of complex structural systems. Careful selection and logical layout of sensors is critical to enable the high reliability of system health assessment. This paper presents a methodology how to use a minimum number of sensors, and what locations of them should be placed, so that the voltage signals received from the sensor can be used to detect both presence and extent of damage. In this study, an optimization procedure is developed using Genetic Algorithm (GA) to determine the location of piezoelectric sensor for damage detection in a composite wingbox. A new damage index using all differences in voltage signals decomposed by wavelet transform is proposed. Results show that the proposed method is available at determining number and location of sensors for structural damage detection using piezoelectric patch sensors.

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Spline-Based FEM Approach

Żak

2024

Lecture Notes on Numerical Methods in Engineering and Sciences

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Modeling for Detection of Degraded Zones in Metallic and Composite Structures

Cited by 3 publications

References 79 publications

Damage Detection and Assessment of Stiffness and Mass Matrices in Curved Simply Supported Beam Using Genetic Algorithm

Damage Detection and Assessment of Stiffness and Mass Matrices in Curved Simply Supported Beam Using Genetic Algorithm

Optimal Placement of Sensors for Damage Characterization Using Genetic Algorithms

Spline-Based FEM Approach

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