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Kalman Filter-based Data Recovery in Wireless Smart Sensor Network for Infrastructure Monitoring
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 Title & Authors
Kalman Filter-based Data Recovery in Wireless Smart Sensor Network for Infrastructure Monitoring
Kim, Eun-Jin; Park, Jong-Woong; Sim, Sung-Han;
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 Abstract
Extensive research effort has been made during the last decade to utilize wireless smart sensors for evaluating and monitoring structural integrity of civil engineering structures. The wireless smart sensor commonly has sensing and embedded computation capabilities as well as wireless communication that provide strong potential to overcome shortcomings of traditional wired sensor systems such as high equipment and installation cost. However, sensor malfunctioning particularly in case of long-term monitoring and unreliable wireless communication in harsh environment are the critical issues that should be properly tackled for a wider adoption of wireless smart sensors in practice. This study presents a wireless smart sensor network(WSSN) that can estimate unmeasured responses for the purpose of data recovery at unresponsive sensor nodes. A software program that runs on WSSN is developed to estimate the unmeasured responses from the measured using the Kalman filter. The performance of the developed network software is experimentally verified by estimating unmeasured acceleration responses using a simply-supported beam.
 Keywords
Data recovery;Kalman filter;Wireless smart sensor;Wireless smart sensor network;
 Language
Korean
 Cited by
 References
1.
Jo, H. (2013), Multi-scale Structural Health Monitoring Using Wireless Smart Sensors, PhD dissertation, University of Illinois at Urbana-Champaign.

2.
Jo, H., and Spencer, B. F. (2014), Multi-Metric Model ased Structure Health Monitoring, Proceedings of SPIE, Sensors and Smart Structures Technologies for Civil, Mechanical, and Aerospace Systems 2014, San Diego, 90611F-90611F.

3.
Lynch, J.P., Sundararajan, A., Law, K.H., Kiremidjian, A.S. and Carryer, E. (2004), Embedding Damage Detection Algorithms in a Wireless Sensing Unit for Operational Power Efficiency, Smart Materials and Structures, 13(4), 800-810. crossref(new window)

4.
Palanisamy, R.P., Cho, S., Kim, H., and Sim, S.-H. (2015), Experimental Validation of Kalman Filter-based Strain Estimation in Structures Subjected to Non-zero Mean Input, Smart Structures and Systems, 15(2), 489-503. crossref(new window)

5.
Papadimitriou, C., Fritzen, C.P., Kraemer, P. and Ntotsios, E. (2010), Fatigue Predictions in Entire body of Metallic Structures from a Limited Number of Vibration Sensors Using Kalman Filtering, Structural Control Health Monitoring, 18(5), 554-573.

6.
Park, J.-W., Sim, S.-H., and Jung, H.J. (2013), Wireless Sensor Network for Decentralized Damage Detection of Building Structures, Smart Structures and Systems, 12(3-4).

7.
Rice, J. A., and Spencer Jr, B. F. (2009), Flexible Smart Sensor Framework for Autonomous Full-scale Structural Health Monitoring, Newmark Structural Engineering Laboratory. University of Illinois at Urbana-Champaign.

8.
Rice, J. A., Mechitov, K. A., Spencer Jr, B. F., and Agha, G. (2008), A Service-oriented Architecture for Structural Health Monitoring Using Smart Sensors, In Proceedings of the 14th World Conference on Earthquake Engineering, Beijing.

9.
Sim, S.-H. and Spencer, Jr., B.F. (2009), Decentralized Strategies for Monitoring Structures using Wireless Smart Sensor Networks. Newmark Structural Laboratory Report Series, University of Illinois at Urbana-Champaign, Report 19.

10.
Sim, S.-H., Li, J., Jo, H., Park, J.-W., Cho, S., Spencer, Jr., B.F., and Jung, H.-J. (2014), A Wireless Smart Sensor Network for Automated Monitoring of Cable Tension, Smart Materials and Structures, 23(2), 025006. crossref(new window)

11.
Sim, S.-H., Spencer, Jr., B. F., Zhang, M., and Xie, H. (2009), Automated Decentralized Modal Analysis using Smart Sensors, Journal of Structural Control and Health Monitoring, 17(8), 872-894.

12.
Smyth, A., and Wu, M. (2007), Multi-rate Kalman Filtering for the Data Fusion of Displacement and Acceleration Response Measurements in Dynamic System Monitoring, Mechanical Systems and Signal Processing, 21(2), 706-723. crossref(new window)

13.
Spencer, B. F., Ruiz-Sandoval, M. E., and Kurata, N. (2004), Smart Sensing Technology: Opportunities and Challenges, Structural Control and Health Monitoring, 11(4), 349-368. crossref(new window)

14.
Straser, E.G. and Kiremidjian, A.S. (1998), A Modular, Wireless Damage Monitoring System for Structures, Report No. 128, John A. Blume Earthquake Engineering Center, Department of Civil and Environmental Engineering, Stanford University, Stanford, CA.

15.
Zimmerman, A. T., Shiraishi, M., Swartz, R. A., and Lynch, J. P. (2008), Automated Modal Parameter Estimation by Parallel Processing within Wireless Monitoring Dystems, Journal of Infrastructure Systems, 14(1), 102-113. crossref(new window)