A multiresolution approach for damage detection in fiber-reinforced polymer pipe systems

El-Gebeily, M. A.; Khulief, Y. A.; Ghneim, Ahmed

doi:10.1177/1687814016668707

Cited by 4 publications

(4 citation statements)

References 30 publications

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“…The load case matrix for the SCR is summarized in Table 2. The damage to the SCR will cause a change in stiffness, referring to existing structural damage detection research [7][8][9]. Thus, in the SCR model, the damage is simulated by reducing the elastic modulus of the damaged part.…”

Section: Simulation Scr Modelmentioning

confidence: 99%

“…The main purpose of this study is to locate and quantify the fatigue damage at the touchdown zone of SCRs. The simulation of damage refers to other damage studies of steel pipe or steel plate structures [7][8][9]. The traditional vibrationbased damage identification methods have been widely used and can be divided into two categories: parametric approaches and non-parametric approaches [10][11][12].…”

Section: Introductionmentioning

confidence: 99%

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A Novel Damage Identification Method for Steel Catenary Risers Based on a Novel CNN-GRU Model Optimized by PSO

Liu

Mei

Wang

et al. 2023

JMSE

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As a new type of riser connecting offshore platforms and submarine pipelines, steel catenary risers (SCRs) are generally subject to waves and currents for a long time, thus it is significant to fully evaluate the SCR structure’s safety. Aiming at the damage identification of the SCR, the acceleration time series signals at multiple locations are taken as the damage characteristics. The damage characteristics include spatial information of the measurement point location and time information of the acquisition signal. Therefore, a convolutional neural network (CNN) is employed to obtain spatial information. Considering the variable period characteristics of the acceleration time series of the SCR, a gated recurrent unit (GRU) neural network is utilized to study these characteristics. However, neither a single CNN nor GRU model can simultaneously obtain temporal and spatial data information. Therefore, by combining a CNN with a GRU, the CNN-GRU model is established. Moreover, the hyperparameters of deep learning models have a significant influence on their performance. Therefore, particle swarm optimization (PSO) is applied to solve the hyperparameter optimization problem of the CNN-GRU. Thus, the PSO-CNN-GRU (PCG) model is established. Subsequently, an SCR damage identification method based on the PCG model is presented to predict the damage location and degree by SCR acceleration time series. By analyzing the SCR acceleration data, the prediction performances of the PCG model and the PSO optimization capacity are verified. The experimental results indicate that the identification result of the proposed PCG model is better than that of several existing models (CNN, GRU, and CNN-GRU).

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Section: Simulation Scr Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Novel Damage Identification Method for Steel Catenary Risers Based on a Novel CNN-GRU Model Optimized by PSO

Liu

Mei

Wang

et al. 2023

JMSE

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“…Using the Euler-Bernoulli pipe element, equation (7) has been discretized in order to solve it, wherein the B-spline wavelet on the interval was used as it was in Oke and Khulief. 28 As a result, equation ( 7) can be stated in a condensed form as Besides, equation ( 8) can be stated in state space using the state vectors fzg and f _ z g as…”

Section: The Finite Element Formulation Of Composite Pipe Conveying Fluidmentioning

confidence: 99%

“…In their investigation, dynamic analysis, first mode shape, and others were considered. El-Gebeily et al 7 developed a method for detecting pipe internal damage in which vibration modal characteristics were employed and B-spline scaling function was used to formulate the model. Other investigations that have been carried out on pipes failure analysis can be found in Ying et al, 8 Rezaei et al 9 It can be observed in the above review that pipe mode shapes have not been given much attention in the failure analysis.…”

Section: Introductionmentioning

confidence: 99%

Investigation of approximate mode shape and transition velocity of pipe conveying fluid in failure analysis

Oke

Adeyemi

Salau

2022

Advances in Mechanical Engineering

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Structures dynamic characteristics and their responses can change due to variations in system parameters. With modal characteristics of the structures, their dynamic responses can be identified. Mode shape remains vital in dynamic analysis of the structures. It can be utilized in failure analysis, and the dynamic interaction between structures and their supports to circumvent abrupt failure. Conversely, unlike empty pipes, the mode shapes for pipes conveying fluid are tough to obtain due to the intricacy of the eigenvectors. Unfortunately, fluid pipes can be found in practice in various engineering applications. Thus, due to their global functions, their dynamic and failure analyses are necessary for monitoring their reliability to avert catastrophic failures. In this work, three techniques for obtaining approximate mode shapes (AMSs) of composite pipes conveying fluid, their transition velocity and relevance in failure analysis were investigated. Hamilton’s principle was employed to model the pipe and discretized using the wavelet-based finite element method. The complex modal characteristics of the composite pipe conveying fluid were obtained by solving the generalized eigenvalue problem and the mode shapes needed for failure analysis were computed. The proposed methods were validated, applied to failure analysis, and some vital results were presented to highlight their effectiveness.

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Viscoelastic response of steel wire and particulate-reinforced polymer under dynamic and creep loading

Noma,

Dauda,

Dan-asabe

et al. 2024

J Mater Sci

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A multiresolution approach for damage detection in fiber-reinforced polymer pipe systems

Cited by 4 publications

References 30 publications

A Novel Damage Identification Method for Steel Catenary Risers Based on a Novel CNN-GRU Model Optimized by PSO

A Novel Damage Identification Method for Steel Catenary Risers Based on a Novel CNN-GRU Model Optimized by PSO

Investigation of approximate mode shape and transition velocity of pipe conveying fluid in failure analysis

Viscoelastic response of steel wire and particulate-reinforced polymer under dynamic and creep loading

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