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A pseudo-modal structural damage index based on orthogonal empirical mode decomposition
Proceedings of the Institution of Mechanical Engineers Part C-Journal of Mechanical Engineering Science ( IF 1.359 ) Pub Date : 2019-11-07 , DOI: 10.1177/0954406219885972
Egidio Lofrano; Francesco Romeo; Achille Paolone

Damage identification attracts wide attention and in-depth research in numerous engineering fields for its paramount importance for systems safety and operational assessment. Among the proposed techniques, structural vibration-based ones are increasingly considered. There are two main reasons behind this progression: a practical motivation, related to the aptitude of dynamic tests in capturing the real behaviour of structural systems,1,2 and a technological reason, related to the reduction of costs and the miniaturisation of the electronic acquisition devices.3 Vibration-based structural health monitoring systems are nowadays widespread, for both new and existing structural systems, and dynamic structural damage identification is a new target of a wide scientific community.4 However, this task is intrinsically more complicated than the ‘mere’ structural identification one, since it calls for extracting damage-sensitive features over time from periodically spaced response measurements. Mathematical models derived from physical basis are used for modelling mechanical systems, often resorting to output-only modal parameter estimation methods5,6; alternatively, data-driven models describing the systems input–output relation are adopted. A trade-off between the two approaches is based on the combination of both, physical insights and experimental data. As reported in the comprehensive reviews published in the last two decades,7–9 the variety of proposed identification strategies are devised to detect, localise, quantify damage and, ultimately, to estimate the remaining service life of the structure. These goals are pursued by relying on different quantities, i.e. physical properties (mass, stiffness, damping), modal properties (natural frequencies, mode shapes, modal damping) and structural response signal features (e.g. Fourier, Wavelet or Hilbert transform). In essence, all the identification strategies aim at extracting reliable signs for early diagnosis of structural damage from the least amount of data. For most real structural systems, direct measurement of global physical properties and their variations, possibly ascribable to damage, is unfeasible; therefore, local, albeit numerous, dynamic response quantities are usually relied upon. Modal property-based approaches seek after dynamic response alteration due to damage, which is usually expected to cause a change in stiffness. Predictive models and physically sound interpretations can be provided by these approaches. However, some difficulties may arise, such as the need to rely on accurate structural modelling and to select proper response signals, not to mention the lack of solution uniqueness of the inverse problem. Differently, signal processing-based techniques seek after signals changes, in time and frequency, between undamaged and damaged states. Direct evidence of signals alteration can be readily detected; however, its physical interpretation is often cumbersome.
更新日期:2020-01-06

 

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