Structural system identification by measurement error‐minimizing observability method

Lei, Jun; Galant, José Antonio Lozano; Xu, Dianguo; Coderque, José Turmo

doi:10.1002/stc.2425

Cited by 14 publications

(17 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…One of the most known and commonly adopted approaches for optimal sensor placement was developed by Kammer [ 14 ]. Since then, several variants of this approach have been suggested to resolve the positioning of SSI sensors [ 13 , 15 , 16 , 17 ]. However, no research works have noticed that the choice in the best position of the sensors might change when different sources of uncertainty are considered in the uncertainty analysis.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Role of Sensors in Error Propagation with the Dynamic Constrained Observability Method

Tian

Nogal

Casas

et al. 2021

Sensors

Self Cite

View full text Add to dashboard Cite

The inverse problem of structural system identification is prone to ill-conditioning issues; thus, uniqueness and stability cannot be guaranteed. This issue tends to amplify the error propagation of both the epistemic and aleatory uncertainties, where aleatory uncertainty is related to the accuracy and the quality of sensors. The analysis of uncertainty quantification (UQ) is necessary to assess the effect of uncertainties on the estimated parameters. A literature review is conducted in this paper to check the state of existing approaches for efficient UQ in the parameter identification field. It is identified that the proposed dynamic constrained observability method (COM) can make up for some of the shortcomings of existing methods. After that, the COM is used to analyze a real bridge. The result is compared with the existing method, demonstrating its applicability and correct performance by a reinforced concrete beam. In addition, during the bridge system identification by COM, it is found that the best measurement set in terms of the range will depend on whether the epistemic uncertainty involved or not. It is concluded that, because the epistemic uncertainty will be removed as the knowledge of the structure increases, the optimum sensor placement should be achieved considering not only the accuracy of sensors, but also the unknown structural part.

show abstract

Section: Introductionmentioning

confidence: 99%

“…Figure16. Uncertainty distribution of Young's modulus E 2 and E 8 , prior and posterior PDF (grey line) of element Young's modulus according to[4], the red PDF by COM UQ analysis.…”

mentioning

confidence: 99%

Role of Sensors in Error Propagation with the Dynamic Constrained Observability Method

Tian

Nogal

Casas

et al. 2021

Sensors

Self Cite

View full text Add to dashboard Cite

show abstract

“…Unfortunately, because of these simplifications, actual structures on site rarely correspond to the numerical models. In this case, to get a representative behavior of the structure, the calibration of the model parameters on site might be advised [4,5]. This calibration can use structural system identification (SSI) techniques to measure the actual response of the structure on site by Despite the many works published about this topic, many researchers agree that this procedure is still under development, and it is expected that huge technological progress will be made in the coming years.…”

Section: Introductionmentioning

confidence: 99%

New Image Recognition Technique for Intuitive Understanding in Class of the Dynamic Response of High-Rise Buildings

et al. 2021

View full text Add to dashboard Cite

In the last years, more and more studies have highlighted the advantages of complementing traditional master classes with additional activities that improve students’ learning experience. This combination of teaching techniques is specially advised in the field of structural engineering, where intuition of the structural response it is of vital importance to understand the studied concepts. This paper deals with the introduction of a new (and more encouraging) educational tool to introduce students intuitively to the dynamic response of structures excited with an educational shaking table. Most of the educational structural health monitoring systems use sensors to determine the dynamic response of the structure. The proposed tool is based on a radically different approach, as it is based on low-cost image-recognition techniques. In fact, it only requires the use of an amateur camera, a black background, and a computer. In this study, the effects of both the camera location and the image quality are also evaluated. Finally, to validate the applicability of the proposed methodology, the dynamic response of small-scale buildings with different typologies is analyzed. In addition, a series of surveys were conducted in order to evaluate the activity based on student´s satisfaction and the actual acquisition and strengthening of knowledge.

show abstract

“…Unfortunately, because of these simplifications actual structures on site rarely correspond to the numerical models. In this case, to get a representative behavior of the structure, the calibration of the model parameters on site might be advised (Lei et al 2019). This calibration can use Structural System Identification (SSI) techniques to measure the actual response of the structure onsite by health monitoring systems (such as accelerometers, glass fiber wires or strain gauges).…”

Section: Introductionmentioning

confidence: 99%

New Image Recognition Technique for Intuitive Understanding in Class of the Dynamic Response of High-Rise Buildings

Soriano¹,

Mobaraki²,

Galant³

et al. 2021

Preprint

View full text Add to dashboard Cite

In the last years, more and more studies highlight the advantages of complementing traditional master classes with additional activities that improve students´ learning experience. This combination of teaching techniques is specially advised in the field of structural engineering, where intuition of the structural response it is of vital importance to understand the studied concepts. This paper deals with the introduction of a new (and more encouraging) educational tool to introduce intuitively students in the dynamic response of structures excited with an educational shaking table. Most of the educational structural health monitoring systems use sensors to determine the dynamic response of the structure. The proposed tool is based on a radically different approach, as it is based on low-cost image-recognition techniques. In fact, it only requires the use an amateur camera, a black background and a computer. In this study, the effects of both the camera location and the image quality are also evaluated. Finally, to validate the applicability of the proposed methodology, the dynamic response of small-scale buildings with different typologies is analyzed. In addition, a series of surveys were conducted in order to evaluate the activity based on student´s satisfaction and the actual acquisition and strengthening of knowledge.

show abstract

Structural system identification by measurement error‐minimizing observability method

Cited by 14 publications

References 36 publications

Role of Sensors in Error Propagation with the Dynamic Constrained Observability Method

Role of Sensors in Error Propagation with the Dynamic Constrained Observability Method

New Image Recognition Technique for Intuitive Understanding in Class of the Dynamic Response of High-Rise Buildings

New Image Recognition Technique for Intuitive Understanding in Class of the Dynamic Response of High-Rise Buildings

Contact Info

Product

Resources

About