Wireless Structural Health Monitoring Using MEMS

Abstract:

So far, the inspection of building structures and especially of bridges is mainly done visually. Therefore, the condition of the structure is examined from the surface and the interpretation and assessment is based on the experience of the expert. However, the main purpose of monitoring civil structures is not to substitute visual inspection. Continuous structural health monitoring should provide data from the inside of a structure to better understand its structural performance and to predict its durability and remaining life time. Monitoring should render objective data and observable alterations in the structure continuously, which cannot be done by visual inspection. More detailed information is needed with respect to different exposure due to dynamic and static loads and also temperature and moisture. Today mainly wired monitoring systems are used to monitor structures, which are relatively expensive and time consuming to install. In this paper the basic principle of a wireless monitoring system equipped with MEMS sensors is presented, which can be easily installed at different structures. Microelectromechanical systems (MEMS) are small integrated devices or systems that combine electrical and mechanical components. A wireless monitoring sensor network equipped with such MEMS could be produced with a very low budget and becomes very efficient. This permits a wide area of applications not only in civil engineering. With respect to different applications relevant properties of a wireless monitoring system are described. In detail network configuration, power consumption, data acquisition and data aggregation, signal analysis and data reduction as well as reliability and robustness are discussed.

• Periodical: Key Engineering Materials (Volumes 293-294)
• Pages: 625-634
• DOI: https://doi.org/10.4028/www.scientific.net/KEM.293-294.625
• Online since: September 2005
• Authors: Markus Krüger, Christian U. Grosse, Pedro José Marrón
• Keywords: Micro-Electromechanical System (MEMS), Structural Health Monitoring (SHM), Telemetry, Wireless Sensor Network (WSN)

References

[1] Sustainable Bridges: Assessment for Future Traffic Demands and Longer Lives: Integrated Project in the Sixth Framework Programme on Research, Technological Development and Demonstration, FP6-PLT-001653, http: /www. sustainablebridges. net.

[2] C.U. Grosse, F. Finck, J. Kurz and H. -W. Reinhardt: Monitoring techniques based on wireless AE sensors for large structures in civil engineering (Proc. EWGAE 2004 symposium in Berlin, Berlin 2004).

[3] B.A. Warneke and K.S. J Pister: MEMS for Distributed Wireless Sensor Networks (International Conference on Electronics, Circuits and Systems, 2002).

DOI: 10.1109/icecs.2002.1045391

[4] L. Doherty, B.A. Warneke, B. Boser and K.S.J. Pister: Energy and Performance Considerations for Smart Dust (International Journal of Parallel and Distributed Sensor Networks, 2001).

[5] E. Mackensen, W. Kuntz and C. Müller: Smart Wireless Autonomous Microsystems (SWAMs) (Proceeding of the Sensors For Industry Conference, New Orleans, USA 2004).

DOI: 10.1109/sficon.2004.1287133

[6] C.U. Grosse: Monitoring of large structures using acoustic emission techniques (Symposium Niet-destructief onderzoek in de bouwsector, Proceedings, Antwerpen 2003).

[7] E. Mackensen and W. Kuntz: Intelligente, autarke Mikrosysteme für drahtlose Sensor-AktorNetzwerke (VDI/VDE-Gesellschaft (Hrsg. ): Sensoren und Messsysteme 2004, VDI-Berichte 1829, Düsseldorf 2004).

[8] D. Roundy, D. Steingart, L. Frechette, P. Wright and J. Rabaey: Power Sources for Wireless Sensor Networks (In: H. Karl, A. Willig, A. Wolisz (Eds. ): EWSN 2004, LCNS 2004).

DOI: 10.1007/978-3-540-24606-0_1

[9] N. Zhou, B. Zhu, K.S.J. Pister and A.M. Agogino: Evolutionary Synthesis of MEMS (Microelectronic Mechanical Systems) Design (IEEE Neural Networks Council and Smart Engineering Systems Laboratory, 2001).

[10] K. Römer, C. Frank, P.J. Marrón and C. Becker: Generic role assignment for wireless sensor networks (In Proc. of the 11th ACM SIGOPS European Workshop, 2004).

DOI: 10.1145/1133572.1133588

[11] D. Minder, J. Hähner, R. Sauter, K. Rothermel, P.J. Marrón and A. Lachenmann: Tinycubus - A Flexible and Adaptive Framework for Sensor Networks (Proceedings of the Second European Workshop on Sensor Networks EWSN2005, 2005).

DOI: 10.1109/ewsn.2005.1462020

[12] D. Culler, A. Woo and T. Tong: Taming the Underlying Challenges of Reliable Multihop Routing in Sensor Networks (Proceedings of the First International Conference on Embedded Networked Sensor Systems, 2003).

DOI: 10.1145/958491.958494

[13] J. Heidemann, D. Son and B. Krishnamachari: Experimental study of the effects of Transmission Power Control and Blacklisting in Wireless Sensor Networks. (Proceedings of the First IEEE Communications Society Conference on Sensor and Ad Hoc Communications and Networks SECON, 2004).

DOI: 10.1109/sahcn.2004.1381929

[14] B.M. Baas: IEEE J. Solid-State Circuits Vol. 34(3) (1999), p.380.

[15] A. Woo, S. Madden and R. Govindan: Communications of the ACM Vol. 47(6) (2004), p.47.

[16] P. Seshadri, P. Bonnet and J.E. Gehrke: Towards Sensor Database Systems (Proceedings of the Second International Conference on Mobile Data Management, 2001).

[17] J. Liu, Y. Chen and A. Liestman: Clustering Algorithms for Ad Hoc Wireless Networks (Ad Hoc and Sensor Networks, 2004).

DOI: 10.1016/j.adhoc.2004.08.009

[18] K. Römer: Tracking Real-World Phenomena with Smart Dust (Proceedings of the European Workshop on Sensor Networks, 2004).

[19] D. Estrin, J. Elson and L. Girod: File-Grained Network Time Synchronization using Reference Broadcasts (Proceedings of the 5th symposium on Operating systems design and implementation, 2002).

DOI: 10.1145/1060289.1060304

[20] K. Römer and J. Elson: SIGCOMM Comput. Commun. Vol. 33(1) (2003), p.149.