Optimal Sensor Placement for Modal Identification of Bridge Systems Considering Number of Sensing Nodes
Publication: Journal of Bridge Engineering
Volume 19, Issue 6
Abstract
A series of optimal sensor placement (OSP) techniques is discussed in this paper. A framework for deciding the optimum number and location of sensors is proposed, to establish an effective structural health monitoring (SHM) system. The vibration response from an optimized sensor network reduces the installation and operational cost, simplifies the computational processes for a SHM system, and ensures an accurate estimation of monitoring parameters. In particular, the proposed framework focuses on the determination of the number of sensors and their proper locations to estimate modal properties of bridge systems. The relative importance of sensing locations in terms of signal strength was obtained by applying several OSP techniques, which include effective influence (EI), EI-driving point residue (EI-DPR), and kinetic energy (KE) methods. Additionally, the modified variance (MV) method, based on the principal component analysis (PCA), was developed with the assumption of independence in modal ordinates at each sensing location. Modal assurance criterion (MAC) between the target and interpolated mode shapes from an optimal sensor set was utilized as an effective measure to determine the number of sensors. The proposed framework is verified by three examples: (1) a numerically simulated simply supported beam, (2) finite-element (FE) model of the Northampton Street Bridge (NSB), and (3) modal information identified using a set of wireless sensor data from the Golden Gate Bridge (GGB). These three examples demonstrate the application and efficiency of the proposed framework to optimize the number of sensors and verify the performance of the MV method compared to the EI, EI-DPR, and KE methods.
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Acknowledgments
This research was partially supported by National Science Foundation under grant CMMI-0926898 by the Sensors and Sensing Systems program, and by a grant from the Commonwealth of Pennsylvania, Department of Community and Economic Development, through the Pennsylvania Infrastructure Technology Alliance (PITA).
References
Ahlberg, J. H., Nilson, E. N., and Walsh, J. L. (1967). The theory of splines and their applications, Academic Press, New York.
Belytschko, T., Lu, Y. Y., and Gu, L. (1994). “Element-free Galerkin methods.” Int. J. Numer. Methods Eng., 37(2), 229–256.
Carne, T. G., and Dohrmann, C. R. (1995). “A modal test design strategy for model correlation.” Proc., 13th Int. Modal Analysis Conf., Society for Experimental Mechanics (SEM), Bethel, CT.
Cha, Y. J., Agrawal, A. K., Kim, Y., and Raich, A. M. (2012). “Multi-objective genetic algorithms for cost-effective distributions of actuators and sensors in large structures.” Expert Syst. Appl., 39(9), 7822–7833.
Chang, M., and Pakzad, S. N. (2013). “Observer Kalman filter identification for output-only systems using interactive structural modal identification toolsuite.” J. Bridge Eng., 04014002.
Ewins, D. J. (1984). Modal testing: Theory and practice. Research Studies Press, Letchworth, Hertfordshire, U.K.
Fedorov, V. V., and Hackl, P. (1994). “Optimal experimental design: Spatial sampling.” Calcutta Statistical Assoc. Bull., 44(173–174), 57–81.
Gu, L. (2003). “Moving kriging interpolation and element-free Galerkin method.” Int. J. Numer. Methods Eng., 56(1), 1–11.
Heo, G., Wang, M. L., and Satpathi, D. (1997). “Optimal transducer placement for health monitoring of long span bridge.” Soil. Dyn. Earthquake Eng., 16(7–8), 495–502.
Huston, D. R., Fuhr, P. L., Ambrose, T. P., and Barker, D. A. (1994). “Intelligent civil structures-activities in Vermont.” Smart Mater. Struct., 3(2), 129–139.
Kammer, D. C. (1990). “Sensor placement for on-orbit modal identification and correlation of large space structures.” Proc., American Control Conf., IEEE, New York, 2984–2990.
Laory, I., Hadj Ali, N. B., Trinh, T. N., and Smith, I. F. C. (2012). “Measurement system configuration for damage identification of continuously monitored structures.” J. Bridge Eng., 857–866.
Li, B., Ou, J., Zhao, X., and Li, D. (2011). “Optimal sensor placement in health monitoring system of Xinghai bay bridge.” Int. Workshop on Advanced Smart Materials and Smart Structures Technology, DEStech Publications, Lancaster, PA.
Li, D. S., Li, H. N., and Fritzen, C. P. (2007). “The connection between effective independence and modal kinetic energy methods for sensor placement.” J. Sound Vib., 305(4–5), 945–955.
Lynch, J. P., and Loh, K. J. (2006). “A summary review of wireless sensors and sensor networks for structural health monitoring.” Shock Vib. Digest, 38(2), 91–128.
Meo, M., and Zumpano, G. (2005). “On the optimal sensor placement techniques for a bridge structure.” Eng. Struct., 27(10), 1488–1497.
Middleton, D. (1960). An introduction to statistical communication theory, McGraw Hill, New York.
Morassi, A., and Tonon, S. (2008). “Dynamic testing for structural identification of a bridge.” J. Bridge Eng., 573–585.
Pakzad, S. N., and Fenves, G. L. (2009). “Statistical analysis of vibration modes of a suspension bridge using spatially dense wireless sensor network.” J. Struct. Eng., 863–872.
Pandit, S. M. (1991). Modal and spectrum analysis, Wiley, New York.
Papadimitriou, C. (2004). “Optimal sensor placement methodology for parametric identification of structural systems.” J. Sound Vibrat., 278(4–5), 923–947.
Papadopoulos, M., and Garcia, E. (1998). “Sensor placement methodologies for dynamic testing.” AIAA J., 36(2), 256–263.
Sacks, J., Welch, W. J., Mitchell, T. J., and Wynn, H. P. (1989). “Design and analysis of computer experiments.” Stat. Sci., 4(4), 409–423.
Saitta, S., Kripakaran, P., Raphael, B., and Smith, I. F. (2008). “Improving system identification using clustering.” J. Comput. Civ. Eng., 292–302.
SAP2000 [Computer software]. Walnut Creek, CA, Computers and Structures (CSI).
SMIT 1.0 [Computer software]. Bethlehem, PA, Lehigh Univ., ATLSS Engineering Center.
Spencer, B. F., Jr., Ruiz-Sandoval, M. E., and Kurata, N. (2004). “Smart sensing technology: Opportunities and challenges.” J. Struct. Control Health Monit., 11(4), 349–368.
Worden, K., and Burrows, A. P. (2001). “Optimal sensor placement for fault detection.” Eng. Struct., 23(8), 885–901.
Yao, L., Sethares, W. A., and Kammer, D. C. (1992). “Sensor placement for on-orbit modal identification of large space structure via a genetic algorithm.” IEEE Int. Conf. on Systems Engineering, IEEE, New York, 332–335.
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Published In
Journal of Bridge Engineering
Volume 19 • Issue 6 • June 2014
Copyright
© 2014 American Society of Civil Engineers.
History
Received: Jun 24, 2013
Accepted: Dec 18, 2013
Published online: Jan 27, 2014
Published in print: Jun 1, 2014
Discussion open until: Jun 27, 2014
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