Establishment of a hybrid Fuzzy–Krill Herd approach for novelty detection applied to damage classification of offshore jacket-type structures

Mojtahedi, Alireza; Hokmabady, Hamid; Abyaneh, Saeed Shakery Zad; Nassiraei, Hossein

doi:10.1007/s00773-018-0589-4

Cited by 16 publications

(4 citation statements)

References 24 publications

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“…4 Considered boundary conditions and geometries for the numerical model Fig. 5 Flow over the studied model and installed manometer measuring instruments experimental and numerical results are compared to each other, some differences that can produce false alarms are found due to various types of errors [31]. For this reason, in the first step, the acceptability of the numerical model must be assessed.…”

Section: Resultsmentioning

confidence: 99%

Energy dissipation evaluation for stepped spillway using a fuzzy inference system

2020

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In this study, to evaluate the effects of geometry parameters on the dissipation rate in flows over the stepped spillways, a numerical model is provided and validated by using a physical model. A type of Fuzzy Inference System (FIS) is used to study the control of the rates of dissipation. It is used to measure the estimated energy dissipation under different scenarios, and the results are compared with prepared numerical database. An error criterion is used to examine the prediction accuracy of the FIS measurements. The realization of these kinds of considerations may, in turn, lead to a remarkable reduction in the dimensions of stilling basins. The results indicate that proposed FIS can be used as a valuable tool for operational control of dissipater structures with consideration of different geometric parameters. The method is proposed somehow to consider the uncertainty problems with consideration of the benefits, and some shortcomings noted in the literature.

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Section: Resultsmentioning

confidence: 99%

Energy dissipation evaluation for stepped spillway using a fuzzy inference system

2020

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“…Compared with the Fuzzy Logic System, this method uses fewer features in the training process, and the average accuracy rate reaches 97.5%. Mojtahedi et al 36 present a hybrid Fuzzy Krill Herd algorithm to deal with the noise and uncertainty parameters for the jacket SHM. However, this method is not universal for different noise levels; if the data contains series noise, it will greatly affect the convergence speed and reduce the accuracy of damage identification.…”

Section: Structure Health Monitoring Of Offshore Jacket Structuresmentioning

confidence: 99%

Condition-based structural health monitoring of offshore wind jacket structures: Opportunities, challenges, and perspectives

Leng

Gardoni

Wang

et al. 2023

Structural Health Monitoring

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Structural health monitoring (SHM) has been recognized as a useful tool for safety management and risk reduction of offshore wind farms. In complex offshore environment, jacket structures of offshore wind turbines are prone to damages due to corrosion and fatigue. Effective SHM on jacket structures can substantially reduce their operation risk and costs. This work reviews the latest progress on the SHM of offshore wind jacket structures. The achievements in the structural damage identification, location, quantification, and remaining useful life (RUL) estimation are respectively introduced in detail, and existing challenges are discussed. Possible solutions to the challenges using the Digital Twin (DT) technology are put forward. The DT is able to mirror a real jacket structure into a virtual model, and Bayesian updating can refresh the virtual model parameters in real-time to keep consistency between virtual model and physical structure; then, just-in-time SHM can be carried out for jacket structures by performing damage detection, location, quantification, and RUL estimation using the virtual model. As a result, the DT may provide engineers and researchers a practicable tool for safety monitoring and risk reduction of fixed foundation offshore wind structures.

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“…A part of this research includes a FEM updating using the krill herd (KH) algorithm. [ 30 ] Several researchers have attempted to evaluate the impact of the gray wolf optimizer (GWO) on FEM updating problems. Amiri et al implemented an optimization‐based FEM updating strategy for damage tracking in frames.…”

Section: Introductionmentioning

confidence: 99%

Efficiency of the slime mold algorithm for damage detection of large‐scale structures

Ghannadi

Kourehli

2022

Structural Design Tall Build

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Summary Optimization‐based methods are increasingly being implemented for structural damage detection problems through the minimization of the objective functions based on vibration data. The adopted optimization algorithm and objective function play an important role in the accurate detection and quantification of damages. Meanwhile, the challenge of long computational time is another aspect of structural damage identification problems, especially upon addressing large‐scale structures. In this paper, recently developed optimization techniques called slime mold algorithm (SMA) and marine predators algorithm (MPA) are applied to damage assessment of large‐scale structures for the first time. The performance of these algorithms is compared with those obtained using other well‐known optimization techniques such as ant lion optimizer (ALO), whale optimization algorithm (WOA), and grasshopper optimization algorithm (GOA). Furthermore, the sensitivity of three objective functions based on modal assurance criterion (MAC), modified total modal assurance criterion (MTMAC), and natural frequency vector assurance criterion (NFVAC) are examined. Two numerical studies, including the 53‐bar planar truss and the Guangzhou New TV tower, and a full‐scale three‐story frame as an experimental investigation are conducted to present a statistical comparison. The overall results show that the combination of SMA and objective function based on MTMAC provides an accurate tool for damage identification. However, improved SMA (ISMA) has been introduced to enhance the capability of standard SMA for damage detection, and especially finite element model updating in the experimental example. Five benchmark functions are also used to evaluate the global optimization capacity of ISMA and SMA. The results show that the ISMA has many benefits in terms of tackling global optimization problems. MPA‐MTMAC can provide promising results compared with ALO‐MTMAC, WOA‐MTMAC, and GOA‐MTMAC. However, excessive computation time is a big drawback for MPA. The overall results confirm the perfection of the objective function based on MTMAC compared with two others based on MAC and NFVAC.

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Establishment of a hybrid Fuzzy–Krill Herd approach for novelty detection applied to damage classification of offshore jacket-type structures

Cited by 16 publications

References 24 publications

Energy dissipation evaluation for stepped spillway using a fuzzy inference system

Energy dissipation evaluation for stepped spillway using a fuzzy inference system

Condition-based structural health monitoring of offshore wind jacket structures: Opportunities, challenges, and perspectives

Efficiency of the slime mold algorithm for damage detection of large‐scale structures

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