Optimal Sensor Placement of a Box Girder Bridge Using Mode Shapes Obtained from Numerical Analysis and Field Testing

Óptima Localización de Sensores en un Puente de Viga Cajón Utilizando Modos de Vibración Obtenidos de Análisis Numérico y Pruebas de Medición en Campo

Contenido principal del artículo

Álvaro Viviescas
Gustavo Chio Cho
Oscar Begambre
Wilson Hernandez
Carlos Alberto Riveros-Jerez

Resumen

This paper presents a comparative study of an Optimal Sensor Placement (OSP) implementation conducted in a box girder bridge using experimental and numerical mode shapes obtained at different construction stages. It is widely recognized that monitoring the dynamic response of bridges during different construction stages provides valuable information to adjust design considerations. Therefore, there is a need for the development of OSP implementations in order to find the optimal number of sensors needed for real applications. In the present study, an OPS method based on the maximization of the Fisher Information Matrix (FIM) is used. The use of experimentally derived and numerical based mode shapes is considered in the determination of the optimal sensor locations. Field testing results previously conducted before connecting the central segment of the main span are also included in this study. The asphalt pavement weight effect in OSP determination is also analyzed by considering field testing.

Descargas

Los datos de descargas todavía no están disponibles.

Detalles del artículo

Biografía del autor/a (VER)

Álvaro Viviescas, Universidad Industrial de Santander

Profesor Asociado

Escuela de Ingeniería Civil

Gustavo Chio Cho, Universidad Industrial de Santander

Profesor Asociado

Escuela de Ingeniería Civil

Oscar Begambre, Universidad Industrial de Santander

Profesor Asociado

Escuela de Ingeniería Civil

Wilson Hernandez, Universidad Industrial de Santander

Estudiante de Maestría en Ingeniería Civil

Escuela de Ingeniería Civil

Carlos Alberto Riveros-Jerez, Universidad de Antioquia

Profesor Asociado

Escuela Ambiental

Universidad de Antioquia

Referencias (VER)

Bagheri, A., Alipour, M., Ozbulut, O., Harris, D. (2018). A nondestructive method for load rating of bridges without structural properties and plans. Engineering Structures, 171, pp. 545-556.

Chang, M., Pakzad, S. (2014). Optimal sensor placement for modal identification of bridge systems considering number of sensing nodes. Journal of Bridge Engineering ASCE, 9(6):04014019.

Chen, G-W., Omenzetter, P., Beskhyroun, S. (2017). Operational modal analysis of an eleven-span concrete bridge subjected to weak ambient excitations. Engineering Structures, 151, pp. 839-860.

Costa, C., Ribeiro D., Jorge, P., Silva, R., Arêde, A., Calçada, R. (2016). Calibration of the numerical model of a stone masonry railway bridge based on experimentally identified modal parameters. Engineering Structures, 123, pp. 354-371.

Hernandez, W., Viviescas, A., Riveros, C.A. Dynamic response assessment during the construction of a segmental bridge using finite element modeling and ambient vibration testing. Dyna, in Review.

Kammer, D., Brillhart, R. (1996). Optimal sensor placement for modal identification using system-realization methods. Journal of Guidance, Control and Dynamics, 19, pp. 729-731.

Kim, T., Youn, B., Oh, H. (2018). Development of a stochastic effective independence (SEFI) method for optimal sensor placement under uncertainty. Mechanical Systems and Signal Processing, 111, pp. 615-627.

Kinemetrics Inc. (2016). [On line]. [Last access: 19 April 2016].

Liu, K., Yang, R., Soares, C. (2018). Optimal sensor placement and assessment for modal identification. Ocean Engineering, 165, pp. 209-220.

Meo, M., Zumpano, G. (2005). On the optimal sensor placement techniques for a bridge structure. Engineering Structures, 27, pp. 1488-1497.

MIDAS Information Technology Co. Ltd. (2016). Midas User Manual, MIDAS Information Technology, Seongnam, South Korea.

Prabhu, S., Atamturktur, S. (2013) Selection of Optimal Sensor Locations Based on Modified Effective Independence Method: Case Study on a Gothic Revival Cathedral. Journal of Architectural Engineering ASCE, 19(4), pp. 288-301.

Riveros, C., García, E., Rivero, J. (2013). A comparative study of sensor placement techniques for structural damage detection. Revista EIA, 10, pp. 23-37.

LANL/UCSD Engineering Institute. (2010). Structural Health Monitoring Tools (SHM Tools). Los Alamos national laboratory, US.

Vicenzi, L., Simonini, L. (2017). Influence of model errors in optimal sensor placement. Journal of Sound and Vibration, 389, pp. 119-133.