Probability-based damage detection using model updating with efficient uncertainty propagation

Xu, Yang; Yu, Qin; Chen, Jianjun; Song, Gangbing

doi:10.1016/j.ymssp.2014.11.008

Cited by 16 publications

(8 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…En esta simulación se han considerado 100000 iteraciones donde los resultados se obtuvieron al subdividir la región de muestreo en 2000 regiones espaciadas uniformemente en las que se calcula el número de ocurrencias (fallas) para cada región. El comportamiento aleatorio de las variables de la Tabla 1 fueron asumidos con una distribución LogNormal considerando que es usada frecuentemente en estudios de ingeniería civil cuando las variables tienen una distribución desconocida [32]. Sin embargo, para establecer la distribución más adecuada para cada variable conllevaría un análisis exhaustivo basado en datos reales, lo cual va frontera que agrupa los resultados según sean eficientes o no.…”

Section: Resultsunclassified

Estrategias para la inspección óptima de estructuras de hormigón armado sujetas a corrosión

2021

View full text Add to dashboard Cite

Gran parte de las estructuras de hormigón armado se han construido en la primera mitad del Siglo XX,por lo que su vida útil se encuentra actualmente en una etapa crítica desde la perspectiva del mantenimiento. Uno de los mecanismos de degradación más frecuentes y costosos en este tipo de infraestructura está asociado con la corrosión del refuerzo inducida por el fenómeno de carbonatación. Bajo este contexto,el objetivo de este artículo fue la formulación de un modelo de toma de decisiones para la planificación de la inspección óptima. Los tiempos de inspección fueron optimizados considerando la incertidumbre inherente al proceso de degradación y una compensación entre los costos de inspección y la capacidad de servicio de la estructura. Se ha elaborado un análisis de eficiencia a través de dos enfoques: el Análisis de Frontera Estocástica y el Análisis de Envolvente Multidireccional. Este análisis proporciona una evaluación que reduce el número de inspección necesarias y el intervalo de tiempo entre inspecciones para proporcionar no solo una solución óptima, sino también más eficiente. Así, el resultado de esta investigación comprende un modelo numérico para la obtención de los tiempos de inspección más adecuados durante la vida útil de la estructura.

show abstract

Section: Resultsunclassified

Estrategias para la inspección óptima de estructuras de hormigón armado sujetas a corrosión

2021

View full text Add to dashboard Cite

show abstract

“…In addition to processing the monitoring data, computational modeling of the building also plays an important role. A finite element (FE) model can serve as a basis for optimal sensor placement analysis,() model updating against sensor measurement (alternatively with condensed model),() structural change (e.g., damage) quantification and localization,() reliability assessment, response prediction under various simulated loading conditions, and so forth. Ni et al presented both full‐scale and reduced‐order FE models of the Canton Tower (610 m), which served as a benchmark model for monitoring tall buildings in the SHM community.…”

Section: Introductionmentioning

confidence: 99%

Computational modeling of a unique tower in Kuwait for structural health monitoring: Numerical investigations

Sun

Al-Qazweeni

Parol

et al. 2019

Struct Control Health Monit

View full text Add to dashboard Cite

Summary Computational modeling, in addition to data analytics, plays an important role in structural health monitoring (SHM). The high‐fidelity computational model based on the design and construction information provide important dynamics information of the structure and, more importantly, can be updated against field measurements for SHM purposes such as damage detection, response prediction, and reliability assessment. In this paper, we present a unique skyscraper (Al‐Hamra Tower) located in Kuwait City and its high‐fidelity computational model using ETABS for structural health monitoring applications. The tower is made of cast‐in‐place reinforced concrete with a core of shear walls and two curved shear walls running the height of the building (approximately 413 m with 86 floors in total). Interesting static and dynamic characteristics of the tower are described. System identification, interferometry‐based wave propagation analysis, and wave‐based damage detection are performed using synthetic data. This work mainly presents the phase of numerical investigations, which serves as a basis for correlating the field monitoring data to the model of the building in future work.

show abstract

“…The feasibility of vibration-based damage detection is that the damage usually changes the structural characteristics, such as stiffness, which are reflected in the measured vibration characteristics of the structure [2]. The vibration characteristics include measured frequency, mode shape and strain energy, which are often used in damage detection [3][4][5]. One category of vibration-based damage detection methods is the application of time domain analysis by constructing a time series model, which has been widely used in feature exaction to realize structural damage diagnosis and detection.…”

Section: Introductionmentioning

confidence: 99%

Structural nonlinear damage detection using improved Dempster-Shafer theory and time domain model

Guo¹,

Zhou²,

Zhang³

2019

J. vibroeng.

View full text Add to dashboard Cite

In the service period, a crack may appear in some engineering structures. The development of accurate and effective methods for crack damage detection has become a topic of great importance. In this paper, a nonlinear damage detection method based on the improved Dempster-Shafer (D-S) theory and time domain model is presented. First, acceleration responses in the undamaged and damaged states are measured by using accelerometers. Then, acceleration responses are utilized to establish an autoregressive (AR) model, and residual time series of acceleration responses are used to establish an autoregressive conditional heteroskedasticity (ARCH) model. A cepstral metric conversion (CMC) method based on the AR model is employed to obtain local damage solution and an autoregressive conditional heteroskedasticity conversion (ARCHC) method based on ARCH model is presented to acquire another local damage solution. Finally, the D-S theory is applied to detect damages by integrating these local damage solutions, and an improved D-S theory is further presented to enhance the detection accuracy. The numerical and experimental examples show that the improved D-S theory has high detection accuracy and good performance.

show abstract

Probability-based damage detection using model updating with efficient uncertainty propagation

Cited by 16 publications

References 30 publications

Estrategias para la inspección óptima de estructuras de hormigón armado sujetas a corrosión

Estrategias para la inspección óptima de estructuras de hormigón armado sujetas a corrosión

Computational modeling of a unique tower in Kuwait for structural health monitoring: Numerical investigations

Structural nonlinear damage detection using improved Dempster-Shafer theory and time domain model

Contact Info

Product

Resources

About