Damage detection by mixed measurements using accelerometers and strain gages

Lee, Eun-Taik; Rahmatalla, Salam; Eun, Hee-Chang

doi:10.1088/0964-1726/22/7/075014

Cited by 18 publications

(17 citation statements)

References 19 publications

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“…Esfandiari [28] used a decomposed form of Strain FRF to attribute the strain variations to the changes of the structural parameters. Lee and Rahmattalla [29] proposed a method for damage detection using the data collected from both accelerometers and strain gauges. They indicated that dynamic strain data are more sensitive to structural damages as compared with the displacement data.…”

Section: Introductionmentioning

confidence: 99%

Finite element model updating using strain-based power spectral density for damage detection

Pedram

Esfandiari

Khedmati

2016

Struct. Control Health Monit.

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In this paper a new sensitivity-based finite element (FE) model updating method using spectral density of strain as metric is introduced, which is applicable for damage detection and structural health monitoring purposes. Derivation of the sensitivity equation is exact without any need for approximation. A set of incompletely measured natural frequencies and damping loss factors of the damaged structure is used to deal with incomplete measurement without implementation of the FE model reduction or data expansion algorithms. The insights provided from the distribution of the spectral strain energy among the elements in the intact model are used for selection of excitation location. The solution to the developed sensitivity equation is achieved by linear least square and imposing unprejudiced side constraints on the design variables. The proposed method is successfully examined on the FE model of a 3D truss and frame structure and is capable of localization and quantification of damage. The method is robust against measurement, natural frequency, and mass modeling error.

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Section: Introductionmentioning

confidence: 99%

Finite element model updating using strain-based power spectral density for damage detection

Pedram

Esfandiari

Khedmati

2016

Struct. Control Health Monit.

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“…Thus, to ensure the long‐term stability of structures, damage diagnosis technology that can accurately detect the occurrence of cracks in real time is urgently required. [ 1 ] Two types of diagnostic methods are often employed: contact diagnostics, in which an electrical signal is detected by a n attached strain gauge [ 2 ] or piezoelectric sensor, [ 3 ] and noncontact diagnostics, in which a camera [ 4 ] or LiDAR detector [ 4b,5 ] is employed. Recently, research on self‐reporting materials, which can produce visible signs of deformation or damage via the incorporation of force‐responsive molecules called mechanophores, began to be conducted.…”

Section: Introductionmentioning

confidence: 99%

Mechano‐Responsive Spiropyran Microbeads: A Facile Fabrication Strategy for Self‐Reporting Materials

Jang

Park

et al. 2022

Adv Materials Technologies

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irreversible catastrophic disasters. Thus, to ensure the long-term stability of structures, damage diagnosis technology that can accurately detect the occurrence of cracks in real time is urgently required. [1] Two types of diagnostic methods are often employed: contact diagnostics, in which an electrical signal is detected by a n attached strain gauge [2] or piezoelectric sensor, [3] and noncontact diagnostics, in which a camera [4] or LiDAR detector [4b,5] is employed. Recently, research on selfreporting materials, which can produce visible signs of deformation or damage via the incorporation of force-responsive molecules called mechanophores, began to be conducted. [6] These materials are now attracting increasing levels of attention because of their ability to monitor nonuniform stress/strain distributions in real time, without the need for expensive power sources and data-processing devices.Spiropyran (SP) is a type of mechanophore that exhibits a specific reaction in response to force. [6e,7] As shown in Scheme 1, when a force is applied, the SP molecule undergoes selective C-O bond cleavage and is converted into merocyanine (MC), which is accompanied by color and fluorescence changes. SP is pale yellow and does not fluoresce, but MC is blue (or purple) and exhibits strong fluorescence in the 550-700 nm wavelength region. The advantages of stress visualization, high sensitivity, and reversible response have resulted in SP being very actively studied recently. Since 2009, when Moore and co-workers [7b] reported the discovery of the self-reporting of external forces by chemically bonding SP to a polymethacrylate polymer structure, SP has been introduced into various polymers such as polyurethane (PU), [8] polydimethylsiloxane (PDMS), [9] polyamide (PA), [10] polyester (PET), [11] polyacrylates, [6a,12] and polystyrene. [13] For example, Braun and co-workers [8a] successfully used SP as a molecular probe of force and orientation by incorporating it into the hard and soft phase of a segmented PU, respectively. Ko and co-workers [14] dramatically improved the mechano-sensitivity of SP-linked PDMS by adopting a hierarchical nanoparticle-inmicropore architecture and applied it as a mechano-chromic electronic skin. The nonuniform stress states of a SP-linked polyethylacrylate were experimentally monitored by Creton and co-workers, [15] and their observations were in accord with finite element simulation results. Spiropyran (SP) mechanophores are attracting attention as next-generationsmart materials that can self-diagnose stress or strain thanks to their capacity for stress visualization with superior sensitivity. However, at present, to achieve the self-reporting functionality, it is considered essential that SP is chemically bonded to a host matrix, which has greatly limited its application. In this paper, mechano-responsive SP beads that can render a material selfreporting by means of simple physical mixing are presented. The synthesis of SP beads is achieved in a microemulsifying needle via dispersio...

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“…As the function of second derivatives of the classical displacement mode shapes (DMSs), strain mode shapes [9] have been applied in structural dynamic modelling, damage detection and dynamic design due to having high sensitivity [10][11][12][13][14]. In recent years, strain measurement based methods have been successfully developed to improve the local outperformance of model updating [15][16][17].…”

Section: Introductionmentioning

confidence: 99%

A revisit to normalization methods for purpose of stress mode shapes

Zhou¹

2020

FME Transactions

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In order to accurately interpret the results of modal analysis for the purpose of stress mode shapes (SMSs), this work revisits the normalization methods in computational structural dynamics. Firstly, the fundamental principle of structural dynamics analysis and mode of normalization were concisely introduced, and the critical parameters affecting SMSs were discussed. Secondly, the displacement and mass normalizations were applied to the case study of a beam structure. Detailed comparisons were considered between the SMSs and the conventional displacement mode shapes (DMSs) with different normalization methods. Lastly, some important characteristics were obtained. Present study can serve as an ongoing research effort aimed at evaluating both the SMSs and DMSs for future dynamic damage/failure analysis.

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Damage detection by mixed measurements using accelerometers and strain gages

Cited by 18 publications

References 19 publications

Finite element model updating using strain-based power spectral density for damage detection

Finite element model updating using strain-based power spectral density for damage detection

Mechano‐Responsive Spiropyran Microbeads: A Facile Fabrication Strategy for Self‐Reporting Materials

A revisit to normalization methods for purpose of stress mode shapes

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