Damage identification of structures with uncertain frequency and mode shape data

Xia, Yong; Hao, Hong; Brownjohn, James; Xia, Pinqi

doi:10.1002/eqe.137

Cited by 140 publications

(74 citation statements)

References 18 publications

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“…Finally, damage identification is not in fact a deterministic exercise, but considers variability of parameters and probabilities of identification (Xia et al, 2002;Naeim et al, 2005).…”

Section: Several Reviews Of Vbdd Are Available Including Comprehensimentioning

confidence: 99%

Vibration-based monitoring of civil infrastructure: challenges and successes

Brownjohn

Stefano

et al. 2011

J Civil Struct Health Monit

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264

132

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Structural health monitoring (SHM) is a relatively new paradigm for civil infrastructure stakeholders including operators, consultants and contractors which has in the last two decades witnessed an acceleration of academic and applied research in related areas such as sensing technology, system identification, data mining and condition assessment.SHM has a wide range of applications including, but not limited to, diagnostic and prognostic capabilities.However when it comes to practical applications, stakeholders usually need answers to basic and pragmatic questions about in-service performance, maintenance and management of a structure which the technological advances are slow to address.

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“…Finally, damage identification is not in fact a deterministic exercise, but considers variability of parameters and probabilities of identification (Xia et al, 2002;Naeim et al, 2005).…”

Section: Several Reviews Of Vbdd Are Available Including Comprehensimentioning

confidence: 99%

Vibration-based monitoring of civil infrastructure: challenges and successes

Brownjohn

Stefano

et al. 2011

J Civil Struct Health Monit

Self Cite

264

132

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“…Xia and Hao [13] developed a statistical damage identification algorithm accounting for the effects of measurement noise in the natural frequencies and variations in the finite element (FE) model, and derived the probability of damage existence. They further extended the statistical approach to the case with combined frequency and mode shape data for structural damage identification [14]. Based on acceleration responses, Li and Law [15] analyzed the influence of the uncertainty of system parameters and the measurement data on damage identification.…”

Section: Introductionmentioning

confidence: 99%

Structural damage measure index based on non-probabilistic reliability model

Wang

Xia

Zhou

et al. 2014

Journal of Sound and Vibration

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Uncertainties in the structural model and measurement data affect structural condition assessment in practice. As the probabilistic information of these uncertainties lacks, the non-probabilistic interval analysis framework is developed to quantify the interval of the structural element stiffness parameters. According to the interval intersection of the element stiffness parameters in the undamaged and damaged states, the possibility of damage existence is defined based on the reliability theory. A damage measure index is then proposed as the product of the nominal stiffness reduction and the defined possibility of damage existence. This new index simultaneously reflects the damage severity and possibility of damage at each structural component.Numerical and experimental examples are presented to illustrate the validity and applicability of the method. The results show that the proposed method can improve the accuracy of damage diagnosis compared with the deterministic damage identification method.

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“…Uncertainties in finite element (FE) models and measurements may result in false damage identification (Farrar and Doebling 1998;Xia et al 2002). Moreover, the maximum number of measurement locations is limited due to technological and economical reasons.…”

Section: Introductionmentioning

confidence: 99%

Sensor Placement for Structural Damage Detection considering Measurement Uncertainties

Zhou

Xia

Hao

2013

Advances in Structural Engineering

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Structural damage detection methods using vibration measurements have been developed for decades. Measurement selections may affect damage detection results, because inevitable uncertainties are involved in vibration testing. A new sensor placement index is defined as the ratio of two parameters, namely, the contribution of measurement points to a Fisher information matrix, and the damage sensitivity to the measurement noise. A large value of the contribution vector represents that the corresponding measurement points are sensitive to the damage and measurements at these points are more prominent for structural damage identification, whereas a small noise sensitivity value indicates measurement points that are less influenced by noises. Consequently, the points with large index values are chosen as the measurement subset. The effectiveness of the proposed technique is verified using a laboratory-tested steel frame. The damage detection using different measurement selection schemes shows that the present technique can identify multiple damages of the structure more accurately. The effect of the measurement number is also investigated.

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Damage identification of structures with uncertain frequency and mode shape data

Cited by 140 publications

References 18 publications

Vibration-based monitoring of civil infrastructure: challenges and successes

Vibration-based monitoring of civil infrastructure: challenges and successes

Structural damage measure index based on non-probabilistic reliability model

Sensor Placement for Structural Damage Detection considering Measurement Uncertainties

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