Sensors for structural health monitoring

Sergiyenko, Oleg; Rivas-López, Moisés; Miranda-Vega, Jesús E.; Flores-Fuentes, Wendy; Rodríguez-Quiñonez, Julio C.; Линднер, Ларс; Hernández-Balbuena, Daniel; González-Navarro, Félix F.; Tyrsa, Vera

doi:10.1016/b978-0-12-819870-4.00013-x

Cited by 3 publications

(2 citation statements)

References 37 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The decision was taken considering that nowadays the tendency of modern cities that contain bridges in their transportation systems is adopting smart city concepts. 19 That involves the installation of video surveillance on bridges for vehicle detection and tracking for several purposes. Since surveillance video is an undervalued source of traffic information, already installed and available in most of the bridges, image processing has been selected to extract a bridge load indicator to correlate with displacement measurements, 20 which gives place to the proposed novel method described in this work, because never before bridges displacement measurements by OSSs have been correlated with bridge occupancy estimated from surveillance video.…”

Section: Introductionmentioning

confidence: 99%

A structural health monitoring method proposal based on optical scanning and computational models

Flores-Fuentes

Alba-Corpus

Sergiyenko

et al. 2022

International Journal of Distributed Sensor Networks

Self Cite

View full text Add to dashboard Cite

This article proposes a method for continuous bridge displacement monitoring combining the dynamic triangulation scanning and load estimation by vehicle image recognition. The vehicle–bridge interaction is a non-stationary dynamic process parameter of high relevance to understanding the static instability behavior of bridges. The knowledge of the load on a bridge in the specific time when its structural spatial coordinates are measured allows correlating the bridge displacement with the effect of vehicle–bridge interaction. The evaluation of such correlation is mandatory in order to verify if the observed bridge displacement is due to the nature of its operation or due to it is presenting structural damage. The proposed method is continuous structural health monitoring method, based on the combination of three approaches evaluated at laboratory environment: (1) a three-dimensional optical scanning system for displacement measurement, (2) a load measurement system for vehicle–bridge interaction assessment, and (3) a two-measurement systems data correlation; to be implemented in bridges at a real environment to collect their historical behavior. Overall, for each approach, the measurement systems’ principles, the laboratory experimental methodology followed, and results obtained are presented.

show abstract

Section: Introductionmentioning

confidence: 99%

A structural health monitoring method proposal based on optical scanning and computational models

Flores-Fuentes

Alba-Corpus

Sergiyenko

et al. 2022

International Journal of Distributed Sensor Networks

Self Cite

View full text Add to dashboard Cite

show abstract

“…Besides, different models have been proposed to predict the behavior of nonstructural elements [16][17][18]. The technological advances have permitted monitoring buildings entailing the development of new fields such as structural health monitoring [19,20].…”

Section: Introductionmentioning

confidence: 99%

Influence of Earthquake Mechanisms to the Seismic Response of Steel Moment Frames

Campos¹,

Torres‐Rodas²,

Quinde³

et al. 2021

Proceedings of the 8th International Conference on Computational Methods in Structural Dynamics and Earthquake Engineering (COM

View full text Add to dashboard Cite

Recent studies conducted on Steel Moment Frames (SMFs) highlight the importance of considering the effect of certain characteristics of earthquake ground motions (GMs) such as duration and spectral shape in their seismic response. Although their acceleration response spectra have mainly characterized ground motions in seismic standards, these studies indicate that the probability of collapse is sensitive to the GMs' duration. This represents a concern in areas with a different tectonic mechanism, such as South-America, and Pacific Northwest U.S., where subduction processes mainly generate GMs. It is well-known that the duration and spectral shape of subductions earthquakes are quite different from crustal earthquakes. Motivated by these issues, this research presents a parametric study to assess building height sensitivity to metrics such as inter-story drift ratios and floor accelerations, considering GMs records from subduction and crustal earthquakes carefully selected and scaled. The scientific basis of this research is a series of nonlinear dynamic analyses conducted on SMFs (varying in height) at different seismic hazard levels. Two hazard levels are considered in this study: a) Life safety and b) Collapse prevention. The paper intends to understand the sensitivity of engineering demand parameters (i.e., drifts and floor accelerations) of SMFs to different earthquake mechanisms (i.e., crustal earthquakes vs. subduction earthquakes). The GMs records of subduction earthquakes consist of a set of GMs representative of South America and Japan's seismicity. The GMs records set of crustal earthquakes collects large magnitude-long distance events representative of Southern California.

show abstract

k-Nearest Neighbor Classification for Pattern Recognition of a Reference Source Light for Machine Vision System

2021

View full text Add to dashboard Cite

Sensors for structural health monitoring

Cited by 3 publications

References 37 publications

A structural health monitoring method proposal based on optical scanning and computational models

A structural health monitoring method proposal based on optical scanning and computational models

Influence of Earthquake Mechanisms to the Seismic Response of Steel Moment Frames

k-Nearest Neighbor Classification for Pattern Recognition of a Reference Source Light for Machine Vision System

Contact Info

Product

Resources

About