Review on Vibration-Based Structural Health Monitoring Techniques and Technical Codes

Yang, Yang; Zhang, Yao; Tan, Xiaokun

doi:10.3390/sym13111998

Cited by 95 publications

(50 citation statements)

References 111 publications

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“…δx (a) [mm] for a=0. 4 1, it is easy to observe that the deflection caused by a crack located at the fixed end is smaller than that when the crack is located at x=20 mm and even x=200 mm for all analyzed crack depths.…”

Section: Crack Position [M]mentioning

confidence: 89%

Determining the Severity of Open and Closed Cracks Using the Strain Energy Loss and the Hill-Climbing Method

Tufiși¹,

Rusu²,

Gillich³

et al. 2022

Preprint

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Evaluating the integrity of structures is an important issue in engineering applications. The use of vibration-based techniques has become a common approach to assessing cracks, which are the most often occurring damage in structural elements. When involving an inverse method, it is necessary to know the influence of the position and the geometry of the crack on the modal parameter changes. The geometry of the crack, both in size and shape, defines the damage severity (DS). In this study, we present a method (DS-SHC) used for estimating the DS for closed and open transverse cracks in beam-like structures by using the intact and damaged beam deflections under its weight and a Stochastic Hill Climbing (SHC) algorithm. After describing the procedure of applying DS-SHC, we calculate for a prismatic cantilever beam the severities for different crack types and depths. The results are tested by comparing the DS obtained with DS-SHC with those acquired from dynamic tests made using professional simulation software. We obtained a good fit between the severities determined in these two ways. Afterward, we performed laboratory experiments and find out that the severities obtained with the DS-SHC method can accurately predict the frequency changes due to the crack. Hence, these severities are a valuable tool for damage detection.

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Section: Crack Position [M]mentioning

confidence: 89%

Determining the Severity of Open and Closed Cracks Using the Strain Energy Loss and the Hill-Climbing Method

Tufiși¹,

Rusu²,

Gillich³

et al. 2022

Preprint

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“…In structural health monitoring [16][17][18], it is very important to carry out structural parameter identification. The frequency-domain description of aerodynamic loads is a suitable framework for studying flutter.…”

Section: Identification Methods Of Flutter Derivativesmentioning

confidence: 99%

Computational Fluid Dynamics Based Kriging Prediction on Flutter Derivatives of Flat Steel Box Girders

Zhan

Zhang

et al. 2022

Symmetry

Self Cite

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An investigation on the flutter derivative prediction of flat steel box girders is carried out based on CFD simulations. Firstly, by taking the flat steel girder section of Qingshan Yangtze River Bridge as the basic section and considering its width and height as the design variables of cross-section shape, the design domain of cross-section shape is defined by controlling the possible variation range of cross-section design variables. A small number of cross-sections are selected for the calculation of aerodynamic forces by CFD simulations. Secondly, according to the aerodynamic lift and moment time-histories of these steel box girders, of which the flutter derivatives are identified by the least square method. Next, these selected cross-section shape design parameters are used as the inputs, and the flutter derivatives obtained from CFD simulations are used as the outputs to train Kriging models. To improve the prediction accuracy of Kriging models, a modified method of model training is presented. Finally, the flutter derivatives of other cross-sections in the design domain are predicted by using the trained Kriging models, and the predicted flutter derivatives are verified by CFD simulations. It is feasible to directly predict the flutter derivatives of steel box girders by Kriging models.

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“…Among the modal parameters, the natural frequencies are the easiest to determine and require the involvement of relatively cheap and very robust instrumentation. Moreover, estimating the natural frequencies requires a limited number of sensors compared to methods based on mode shapes [ 6 ]. For this reason, in this paper, we focus on the analysis of natural frequencies to detect damage.…”

Section: Introductionmentioning

confidence: 99%

Beam Damage Assessment Using Natural Frequency Shift and Machine Learning

Gillich

Tufiși

Săcărea

et al. 2022

Sensors

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Damage detection based on modal parameter changes has become popular in the last few decades. Nowadays, there are robust and reliable mathematical relations available to predict natural frequency changes if damage parameters are known. Using these relations, it is possible to create databases containing a large variety of damage scenarios. Damage can be thus assessed by applying an inverse method. The problem is the complexity of the database, especially for structures with more cracks. In this paper, we propose two machine learning methods, namely the random forest (RF), and the artificial neural network (ANN), as search tools. The databases we developed contain damage scenarios for a prismatic cantilever beam with one crack and ideal and non-ideal boundary conditions. The crack assessment was made in two steps. First, a coarse damage location was found from the networks trained for scenarios comprising the whole beam. Afterwards, the assessment was made involving a particular network trained for the segment of the beam on which the crack was previously found. Using the two machine learning methods, we succeeded in estimating the crack location and severity with high accuracy for both simulation and laboratory experiments. Regarding the location of the crack, which was the main goal of the practitioners, the errors were less than 0.6%. Based on these achievements, we concluded that the damage assessment we propose, in conjunction with the machine learning methods, is robust and reliable.

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Review on Vibration-Based Structural Health Monitoring Techniques and Technical Codes

Cited by 95 publications

References 111 publications

Determining the Severity of Open and Closed Cracks Using the Strain Energy Loss and the Hill-Climbing Method

Determining the Severity of Open and Closed Cracks Using the Strain Energy Loss and the Hill-Climbing Method

Computational Fluid Dynamics Based Kriging Prediction on Flutter Derivatives of Flat Steel Box Girders

Beam Damage Assessment Using Natural Frequency Shift and Machine Learning

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