Applying neural networks, genetic algorithms and fuzzy logic for the identification of cracks in shafts by using coupled response measurements

Saridakis, Kostas M.; Chasalevris, Athanasios; Papadopoulos, Chris; Dentsoras, A.J.

doi:10.1016/j.compstruc.2007.08.004

Cited by 61 publications

(28 citation statements)

References 11 publications

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“…Consolazio [23], Inel [20]), damage detection (e.g. Suresh et al [24], Saridakis et al [25]), structural dynamics and control (e.g. Chen et al [26]), and non-destructive testing methods of material (e.g.…”

Section: Introductionmentioning

confidence: 99%

Comparison of ANFIS and NN models—With a study in critical buckling load estimation

Bilgehan

2011

Applied Soft Computing

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Section: Introductionmentioning

confidence: 99%

Comparison of ANFIS and NN models—With a study in critical buckling load estimation

Bilgehan

2011

Applied Soft Computing

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“…Cavalini Jr et al put forward a crack identification approach using external diagnostic forces at certain frequencies to obtain the nonlinear combinational resonances which were used as the objective function of a differential evolution optimization code to determine the crack location and depth by minimizing the difference between the measured and modelled rotor systems. Model‐based methods were adopted by Saridakis et al , Xiang et al and He et al to minimize the difference between real outputs and model outputs to determine the location and depth of a crack in a rotor‐bearing system with genetic algorithm. Model‐based methods perform well in theory, especially for crack localization and quantification, but they are largely dependent on the accuracy of the established model.…”

Section: Introductionmentioning

confidence: 99%

Localization of breathing cracks in stepped rotors using super‐harmonic characteristic deflection shapes based on singular value decomposition in frequency domain

Dong

Ouyang

et al. 2017

Fatigue Fract Eng Mat Struct

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An output‐only multiple‐crack localization method is proposed in this paper to detect and localize breathing cracks in a stepped rotor, which utilizes the crack‐induced local shape distortions in super‐harmonic characteristic deflection shapes (SCDSs). To minimize the noise effects on SCDSs and improve the accuracy of SCDS‐based crack localization, singular value decomposition is adopted to estimate the SCDS as the dominant singular vector of output power spectral density matrix at a super‐harmonic frequency. Then, in order to better reveal shape distortions in the SCDSs, an after‐treatment technique called gapped smoothing method is applied to derive a damage index. Numerical experiments are carried out to investigate the performance of the proposed method based on a two‐disc stepped rotor‐bearing system with breathing cracks established by the finite element method. Results show that the method is effective for single and multiple crack localization in stepped rotors and interference of steps can be excluded. Furthermore, the method is robust to noise. Influences of crack depths and rotating speeds are also investigated, and how to choose the rotating speed for better crack localization is discussed.

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“…"Ref. [8]" has first introduced a model for the coupling effect of bending vibrations on the cracked shaft and then used to identify the rotational angle of the crack. "Ref.…”

Section: Introductionmentioning

confidence: 99%

Vibration Analysis of Cracked Beam Using Genetic Controller

Choudhury

Sahu

Parhi

2011

2011 International Conference on Process Automation, Control and Computing

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Damage to structures may occur as a result of normal operations, accidents, deterioration or severe natural events such as earthquakes and storms. Most often the extent and location of damage may be determined through visual inspection. However, in some cases this may not be feasible. The basic strategy applied in this study is to train the first three natural frequencies of the cracked cantilever beam in a genetic algorithm controller which works on the principle of evolution. Here Finite Element Analysis is used to model the crack. The result from the Genetic Controller has been compared with the Finite Element Analysis result. It has been found out that the results are in close agreement with each other.Index terms -vibration, natural frequency, genetic algorithm, fitness function, binary encoding, and genetic operator.

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Applying neural networks, genetic algorithms and fuzzy logic for the identification of cracks in shafts by using coupled response measurements

Cited by 61 publications

References 11 publications

Comparison of ANFIS and NN models—With a study in critical buckling load estimation

Comparison of ANFIS and NN models—With a study in critical buckling load estimation

Localization of breathing cracks in stepped rotors using super‐harmonic characteristic deflection shapes based on singular value decomposition in frequency domain

Vibration Analysis of Cracked Beam Using Genetic Controller

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