Damage detection in offshore structures using neural networks

Elshafey, Ahmed A.; Haddara, Moutaz; Marzouk, H.

doi:10.1016/j.marstruc.2010.01.005

Cited by 62 publications

(23 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Usually, the functional relationship is better than that obtained using regression methods. Usually, a neural network consists of an input layer, one or more hidden layers and an output layer [51]. The number of the neurons in the input layer is equal to the number of the independent variables in the experiment plus one.…”

Section: Neural Networkmentioning

confidence: 99%

Prediction of punching shear strength of two-way slabs

Elshafey

Rizk

Marzouk

et al. 2011

Engineering Structures

Self Cite

View full text Add to dashboard Cite

Section: Neural Networkmentioning

confidence: 99%

Prediction of punching shear strength of two-way slabs

Elshafey

Rizk

Marzouk

et al. 2011

Engineering Structures

Self Cite

View full text Add to dashboard Cite

“…The classification and the identification of cracks were reasonable using this technique. Elshafey [12] proposed a random decrement technique which is used to extract the free decay of the structure which outlines the use of the NN technique in the identification of a damage index for an offshore structure using its free decay response. The method presented can be used routinely to discover any shape change of the damage index.…”

Section: Neural Network Analysis For Detection Of Cracksmentioning

confidence: 99%

Application of Artificial Intelligence Techniques for Detection of Cracks-A Review

Thatoi¹

2013

IJET

View full text Add to dashboard Cite

Abstract-Detection of cracks using vibration analysis employs different algorithms out of which artificial intelligence (AI) techniques is drawing a lot of attention of the engineers and scientists. This paper presents a comprehensive review of various AI techniques for determining the location, size and depth of cracks in different structures. The techniques mainly consist of fuzzy interference technique, neural network (NN), genetic algorithm (GA), hybrid models and other optimization algorithms.

show abstract

“…Nichols (2003) discusses passive SHM for offshore structures using a phase-space approach, similar to the approach presented in this paper. Elshafey et al (2010) also discuss SHM for offshore structures, though from a physics-based approach rather than a phase-space based approach. Lam et al (2011) investigates damage detection for electrical transmission towers.…”

Section: Applications Of Shmmentioning

confidence: 99%