An estimate of the location of multiple delaminations on aeronautical CFRP plates using modal data inverse problem

Gomes, Guilherme Ferreira; Almeida, Fabrício Alves de; Cunha, Sebastião Simões da; Ancelotti, Antônio Carlos

doi:10.1007/s00170-018-2502-z

Cited by 28 publications

(7 citation statements)

References 59 publications

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“…An inverse problem is a general strategy or methodology that is used to convert observed measurements into information about a physical object or system in which we are interested (Jorge et al [2022]). There are several advantages to using modal data in inverse problems, since modal data usually reflect both global and local structural conditions with relevance (Gomes et al [2018a], Magacho et al [2021]).…”

Section: Inverse Modal Problemsmentioning

confidence: 99%

On the use of Modal Test Data in Inverse Problems: Fundamentals and Applications

Gomes¹,

Carneiro²,

S.³

et al. 2022

Fundamental Concepts and Models for the Direct Problem

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In the past few decades, modal testing has become a major technology for determining, improving and optimizing dynamic characteristics of engineering structures in different fields, with emphasys (but not limited to) mechanical, civil, and aeronautical/aerospace engineering. One of the great advantages of using modal tests is related to their experimental practicality. This practical advantage leads to its strong use in inverse methods, or commonly known as inverse modal-based problems. An inverse problem based on modal parameters can be formulated basically using i) natural frequency, ii) damping factor or loss factor and iii) mode shapes. Other metrics can also be used from the composition of these 3 main responses, such as modal strain energy, inverse FRF and many others. Inverse modal-based identification through optimization algorithms are particularly emphasized. The methods discussed here are mainly elaborated by the evaluation of modal data due to the great potential of application. This chapter discusses the use of computational and intelligent techniques for parameter identification using modal responses. The content in this paper aims to help engineers and researchers find a starting point in developing a better solution to their specific structural problems, either by inverse methods, pattern recognition, or intelligent signal processing.

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Section: Inverse Modal Problemsmentioning

confidence: 99%

On the use of Modal Test Data in Inverse Problems: Fundamentals and Applications

Gomes¹,

Carneiro²,

S.³

et al. 2022

Fundamental Concepts and Models for the Direct Problem

View full text Add to dashboard Cite

show abstract

“…If these responses are correlated, the principal component analysis should be applied. Some authors have already demonstrated the importance of the application of PCA [45][46][47].…”

Section: Stage Ii-sub-stage IImentioning

confidence: 99%

Optimization of the Resistance Spot Welding Process of 22MnB5-Galvannealed Steel Using Response Surface Methodology and Global Criterion Method Based on Principal Components Analysis

Ribeiro

Romão

Luz

et al. 2020

Metals

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The 22MnB5-galvannealed steel is extensively used in the hot stamping process to produce car anti-collision structure parts. Furthermore, the resistance spot welding (RSW) is an important process in the automobile industry, especially in body construction, and the 22MnB5-galvannealed steels are a big challenge for the joining methods because their microstructure and mechanical properties are different from those of the conventional steels. In view of this, the present paper aims to optimize the parameters of the RSW process of the 22MnB5-galvannealed steel. Initially, the goal was to remove the galvannealed coating and in the next stage, the following responses were maximized: the nugget width, the nugget cross-sectional area, the penetration, the strength, the joint efficiency, and the energy absorption, whereas the indentation, heat affected zone and separation were used as constraints. The process parameters selected were the effective welding time, the effective welding current, the quenching time, and the upslope time. Response surface methodology (RSM) was applied jointly with the global criterion method based on principal components. The results of the multiobjective optimization are close to the individual targets for each response, highlighting the importance of considering the correlation structure presented in the responses.

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“…Te inverse problem governing structural damage detection has been evaluated with diferent optimization strategies [3][4][5]. With the increasing dissimilarity and complexity of data acquired from various sensors, for the assessment of structural condition and the diagnosis of structural damage, an extremely large amount of computational time is required for the use of optimization-based algorithms [6].…”

Section: Introductionmentioning

confidence: 99%

Time-Domain Structural Damage Identification Using Ensemble Bagged Trees and Evolutionary Optimization Algorithms

Mahdavi

2023

Structural Control and Health Monitoring

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This paper presents a two-step vibration-based strategy for damage identification of framed structures using ensemble bagged trees known as a well-known supervised machine learning (ML) paradigm in conjunction with evolutionary optimization algorithms. The proposed model incorporates the actual response, wavelet coefficients, and wavelet energy to extract damage-sensitive features from the time-domain of the measured and simulated signals. Unlike available studies in this scope, the key objective of this research is to identify damage with a localization precision down to a single structural member, rather than limiting the evaluation to the group of elements. In order to increase the training performance in contributing to extremely large datasets with numerous class labels, the proposed strategy involves the artificial generation of features. Additionally, a modified genetic algorithm is proposed for fast damage localization. It is deduced that the damage locations are confidently detected within a fast computational time. Subsequently, damage identification is followed by the application of evolutionary optimization algorithms. For comparison purpose, the employment of the water cycle optimization algorithm (WCA) is comparatively investigated with the other three state-of-the-art optimizers, i.e., particle swarm optimization (PSO), imperialist competitive algorithm (ICA), and differential evolution algorithm (DE). The numerical and experimental validation studies evidence satisfactorily reliable identification results with no false detection in dealing with multiple damage scenarios in large-scale and real-world applications. It is concluded that developing the most damage-sensitive features and using the proposed data fusion strategy lead to informative features with a reasonably small size and significantly improve the ML performance.

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An estimate of the location of multiple delaminations on aeronautical CFRP plates using modal data inverse problem

Cited by 28 publications

References 59 publications

On the use of Modal Test Data in Inverse Problems: Fundamentals and Applications

On the use of Modal Test Data in Inverse Problems: Fundamentals and Applications

Optimization of the Resistance Spot Welding Process of 22MnB5-Galvannealed Steel Using Response Surface Methodology and Global Criterion Method Based on Principal Components Analysis

Time-Domain Structural Damage Identification Using Ensemble Bagged Trees and Evolutionary Optimization Algorithms

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