Vibration-Based Delamination Detection in Composite Structures Employing Mixed Unified Particle Swarm Optimization

Barman, Swarup K.; Maiti, Dipak Kumar; Maity, Damodar

doi:10.2514/1.j059176

Cited by 21 publications

(6 citation statements)

References 36 publications

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“…However, where GMDHN is used, the computational time is significantly less than that of CFNN. Barman et al [131] 2020 To improve UPSO in terms of accuracy and convergence rate, a new version of the combination of the standard continuous UPSO and binary UPSO (mixed UPSO) is introduced to be employed in a two-stage method for the delamination assessment in composite structures.…”

Section: Plane Portal Framementioning

confidence: 99%

The Application of PSO in Structural Damage Detection: An Analysis of the Previously Released Publications (2005–2020)

Ghannadi

Kourehli

Mirjalili

2022

Frattura Ed Integrità Strutturale

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The structural health monitoring (SHM) approach plays a key role not only in structural engineering but also in other various engineering disciplines by evaluating the safety and performance monitoring of the structures. The structural damage detection methods could be regarded as the core of SHM strategies. That is because the early detection of the damages and measures to be taken to repair and replace the damaged members with healthy ones could lead to economic advantages and would prevent human disasters. The optimization-based methods are one of the most popular techniques for damage detection. Using these methods, an objective function is minimized by an optimization algorithm during an iterative procedure. The performance of optimization algorithms has a significant impact on the accuracy of damage identification methodology. Hence, a wide variety of algorithms are employed to address optimization-based damage detection problems. Among different algorithms, the particle swarm optimization (PSO) approach has been of the most popular ones. PSO was initially proposed by Kennedy and Eberhart in 1995, and different variants were developed to improve its performance. This work investigates the objectives, methodologies, and results obtained by over 50 studies (2005-2020) in the context of the structural damage detection using PSO and its variants. Then, several important open research questions are highlighted. The paper also provides insights on the frequently used methodologies based on PSO, the computational time, and the accuracy of the existing methodologies.

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Section: Plane Portal Framementioning

confidence: 99%

The Application of PSO in Structural Damage Detection: An Analysis of the Previously Released Publications (2005–2020)

Ghannadi

Kourehli

Mirjalili

2022

Frattura Ed Integrità Strutturale

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“…Further, recently the work about delamination modeling and with PSO & ANN techniques are presented in the works of D. Chakraborty, [ 4 ] Arumugam and Vasudevan, [ 20 ] Khatir et al, [ 21 ] Thobiani et al, [ 22 ] and Barman. [ 23 ] The literature presents the outline of the existing works. It has been concluded that the optimization and prediction of the delaminated composite plate has not yet been performed with the PSO and ANN.…”

Section: Introductionmentioning

confidence: 99%

Prediction of influences of size and locations of delamination on dynamic characteristics of laminated composite plate using particle swarm optimization and artificial neural network

Arumugam

Reddy

et al. 2022

Polymer Composites

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In laminated composite structures, delamination is one of the most common defects. The delamination affects the vibration characteristics of laminates, and thus these indicators can be used to detect the potentially catastrophic failures and measures the health characteristics of laminates. In this study, particle swarm optimization (PSO) and artificial neural network (ANN) are used to optimize and predict the influences of location and size of delamination on the dynamic behavior of composite plates. The classical laminated plate theory

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“…In the last decades, numerous SHM methods have been proposed and were successfully tested on simple specimens relevant to aircraft design in laboratory environments [13][14][15][16][17][18]. Recently, scaled demonstrators equipped with multiple sensors have also been built to develop and test the applicability of promising SHM methodologies [19][20][21].…”

Section: Introductionmentioning

confidence: 99%

Development of Aircraft Spoiler Demonstrators for Cost-Efficient Investigations of SHM Technologies under Quasi-Realistic Loading Conditions

2021

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An idealized 1:2 scale demonstrator and a numerical parameter optimization algorithm are proposed to closely reproduce the deformation shape and, thus, spatial strain directions of a real aerodynamically loaded civil aircraft spoiler using only four concentrated loads. Cost-efficient experimental studies on demonstrators of increasing complexity are required to transfer knowledge from coupons to full-scale structures and to build up confidence in novel structural health monitoring (SHM) technologies. Especially for testing novel sensor systems that depend on or are affected by mechanical strains, e.g., strain-based SHM methods, it is essential that the considered lab-scale structures reflect the strain states of the real structure at operational loading conditions. Finite element simulations with detailed models were performed for static strength analysis and for comparison to experimental measurements. The simulated and measured deformations and spatial strain directions of the idealized demonstrator correlated well with the numerical results of the real aircraft spoiler. Thus, using the developed idealized demonstrator, strain-based SHM systems can be tested under conditions that reflect operational aerodynamic pressure loads, while the test effort and costs are significantly reduced. Furthermore, the presented loading optimization algorithm can be easily adapted to mimic other pressure loads in plate-like structures to reproduce specific structural conditions.

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Vibration-Based Delamination Detection in Composite Structures Employing Mixed Unified Particle Swarm Optimization

Cited by 21 publications

References 36 publications

The Application of PSO in Structural Damage Detection: An Analysis of the Previously Released Publications (2005–2020)

The Application of PSO in Structural Damage Detection: An Analysis of the Previously Released Publications (2005–2020)

Prediction of influences of size and locations of delamination on dynamic characteristics of laminated composite plate using particle swarm optimization and artificial neural network

Development of Aircraft Spoiler Demonstrators for Cost-Efficient Investigations of SHM Technologies under Quasi-Realistic Loading Conditions

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