Lynch, J. P., Law, K. H., Kiremidjian, A. S., Carryer, E., Kenny, T. W., Patridge, A., & Sundararajan, A. (2002). “Validation of a wireless modular monitoring system for structures.” Proceedings of SPIE - <strong>Smart</strong> Structures and Materials: <strong>Smart</strong> Systems for Bridges, Structures, and Highways, San Diego, CA, 4696(2), 17-21. Lynch, J. P. & Loh, K. (2006). “A summary review of wireless sensors and sensor networks for structural health monitoring.” Shock and Vibration Digest, in press. Lynch, J. P., Sundararajan, A., Law, K. H., Kiremidjian, A. S., Carryer, E., Sohn, H., & Farrar, C. R. (2003). “Field validation of a wireless structural health monitoring system on the alamosa canyon bridge.” Proceedings of SPIE - <strong>Smart</strong> Structures and Materials: <strong>Smart</strong> Systems and Nondestructive Evaluation for Civil Infrastructures, 5057, 267-278. Lynch, J. P., Wang, Y., Law, K. H., Yi, J.-H., Lee, C. G., & Yun, C. B. (2005). “Validation of a large-scale wireless structural monitoring system on the Geumdang bridge.” Proceedings of the Int. Conference on Safety and <strong>Structural</strong> Reliability, Rome, Italy. Maia, N. M. M., & Silva, J. M. M. (1997). Theoretical and experimental modal analysis. Taunton Somerset, England: Research Studies Press. Maroti, M. Kusy, B., Simon, G., & Ledeczi, A. (2004). “The flooding time synchronization protocol.” Proceedings of 2nd International Conference On Embedded Networked Sensor Systems, Baltimore, MD, 39-49. Mason, A., Yazdi, N., Najafi, K., & Wise, K. (1995). “A low-power wireless microinstrumentation system for environmental monitoring.” Dig. 8th Int. Conference on Solid- State <strong>Sensors</strong> and Actuators, Stockholm, Sweden, 107-110. Maxim Integrated Products, Inc. (2007). “Single/dual/quad, wide-bandwidth, low-power, single-supply, rail-to-rail i/o op amps.” Datasheet, (Mar. 2, 2007). Mechitov, K. A., Kim, W., Agha, G. A., & Nagayama, T. (2004). “High-frequency distributed sensing for structure monitoring.” Proceedings of 1st Int. Workshop on Networked Sensing Systems, Tokyo, Japan, 101–105. MicroStrain, Inc. (Mar. 2, 2007). Millennial Net. (Mar. 2, 2007). Miller, B. (2001). “Bluetooth and other wireless technologies.” Prentice Hall. (Mar. 2, 2007). Moore, M., Phares, B., Graybeal, B., Rolander, D., & Washer, G. (2001). “Reliability of visual inspection of highway bridges.” FHWA Report No. FHWA-RD-01-020, FHWA, U.S. Dept. of Transportation, Washington, DC. Morgan, B. J. & Osterle R. G. (1985). “On-site modal analysis - a new powerful inspection technique.” Proceedings of 2nd International Bridge Conference, Pittsburg, PA, 108-114. 173
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NSEL Report Series Report No. NSEL-
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The Newmark Structural Engineering
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Contents Page CHAPTER 1 INTRODUCTIO
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9.2.3 Power harvesting . . . . . .
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damage/deterioration is intrinsical
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scalability to a large number of sm
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logic circuit. However, FPGAs are m
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easons, smart sensors spatially dis
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Figure 2.1. EYES project sensor pro
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Table 2.1. Smart Sensor Specificati
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While a number of sensor boards for
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need to be within the coordinator's
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eing examined (Moore et al., 2001).
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structural damage, the analysis to
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that sensor installation cost inclu
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(2004) indicated that this accelero
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different type of sensors connected
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Chapter 3 SHM ARCHITECTURE This cha
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Modal operation Several modal opera
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its spatial gradient, which is clai
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Manager node Cluster head node Leaf
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commands; execution timing cannot b
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Table 3.2. Desirable Characteristic
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Table 3.2. Desirable Characteristic
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Figure 4.1. Foil strain gage. strai
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dB A s Figure 4.4. AA filter design
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8.32F 3V 3.45F 3V Input 1K 1K 1K 1K
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Strain ( ) 80 w/o Digital Filter 60
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performance was experimentally vali
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anges from 10 to 20. If 50 percent
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Node 1 x1 i =1,2,…,ns E x 1
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Correlation function estimate (m 2
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Figure 5.5. Effect of data loss and
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Frobenius norm. Because only a limi
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90 80 70 60 50 Node1 Node2 Node3 No
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On reception of a NACK, the sender
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Sender SendLData.send() Pack parame
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If there are missing packets, the r
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Sender SendLData.bcast() Pack param
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Sender Send a packet • Sender sen
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utilized in SHM applications follow
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where R xxref is a vector consistin
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Time (sec) 80 60 40 20 0 -20 -40 -6
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Difficulties encountered in realizi
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1.8715 x10 5 #ofdatablocks 1.871 me
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Before this decimation is applied,
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where xn is the original signal,
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Timer firing every T3 110 data poin
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locks before or after the current b
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Chapter 6 ALGORITHMS In this chapte
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The eigenproblem of the system matr
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where M 0 is the mass matrix of the
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same community, eliminating the nee
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measurement or mass perturbation ca
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these algorithms are implemented on
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10 0 10 -2 10 -4 0 500 1000 1500 20
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Table 7.1. SVD Accuracy Check on Ma
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7.1.4 Complex matrix inverse A comp
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Figure 7.9. Details of the joint (G
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Figure 7.13. Amplifier (Gao, 2005).
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0.08 0.2 Acceleration (g) 0.04 0 -0
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3 Imote2_2/Imote2_1 Imote2_1/Siglab
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200 3 Phase of spectral densities (
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1.5 x10-17 Time (sec) Difference in
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- Page 167 and 168: e scalability, autonomous distribut
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- Page 173 and 174: REFERENCES Actis, R. L. & Dimarogon
- Page 175 and 176: Casciati, F., Faravelli, L, Borghet
- Page 177 and 178: Feldman, M. & Braun, S. (1995). “
- Page 179: Kling, R. (2003). “Intel Mote: an
- Page 183 and 184: Sazonov, E., Janoyan, K., & Jha, R.
- Page 185 and 186: Yi, J.-H. & Yun, C.-B. (2004). “C