Structural Health Monitoring Using Smart Sensors - ideals ...

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The estimated correlation functions are reported back to the cluster heads and base station. While cluster heads need correlation function estimates from their leaf nodes, the base station does not need the estimates except for the debugging purposes. Reporting to the base station can be omitted once the system is fully developed. Cluster heads then apply ERA to the correlation function estimates. Natural frequencies and mode shapes are calculated. Based on these modal parameters, mass normalization constants are estimated, or damage localization is performed. During monitoring in the local sensor communities, the DCS logic is applied to the outcome of the DLV procedure. The results are then sent back to the base station. Some of these results are injected to cluster heads at the beginning of the next set of measurement. For example, the estimated mass normalization constants are injected to the cluster heads at the beginning of the monitoring process by the local sensor communities. This reporting is also not necessary, once the system is fully developed. The outcome of one set of measurements can be kept on RAM or nonvolatile memory for the next set of measurements, eliminating the need for the parameter injection. In the implementation of DCS for SHM, the frequency scalable feature of the Imote2 is utilized. The microprocessor on the Imote2 can operate at multiple frequencies. Because the driver on TinyOS supports only the 13 and 100 MHz modes at the time, the operational frequency is switched between only these two values. Numerical calculations in NExT, ERA, and DLV, as well as sensing, are all performed at 100 MHz. Other tasks such as communication are performed at 13 MHz. All of the tasks in DCS for SHM need to be performed in the proper order by relevant nodes. A 1-Byte variable containing instruction for the next task is utilized in organizing all of the tasks. All of the communication packets have 1-byte variable to describe the instructions. At the end of transmission and reception, this instruction is processed in a task named “ProcessInstruction”. “ProcessInstruction” then looks for the block of codes following the “switch” statement corresponding to the instruction value. Operations described in the block of codes are executed. At the end of the block, new values can be assigned to the instruction byte to execute the next task, or a communication packet carrying new values for the instruction byte can be sent out. Components of DCS for SHM explained in this chapter are synthesized in this manner. Table 7.7 summarizes the instructions, associated operations, and information accompanying the communication packet. The implementation on the Imote2 is summarized from Figures 7.26 to 7.30. 7.3 Summary This chapter described the implementation of DCS for SHM on a network of Imote2s. The validity of the system is numerically examined in a component-by-component manner. In the next chapter, the Imote2s are installed on a three-dimensional truss and the algorithms are experimentally verified. 129
PC Base station Manager sensor Cluster heads Leaf nodes 1 1 example 1 10 ProcessInstruction(1) Store -NodeIDs of leaf nodes -Measurement channels of leaf nodes 1 10 1 1 NEXT Send a message PC ->BS Receive a message PC->BS Send a message BS -> PC ProcessInstruction(10) NEXT NEXT 1 Receive a message BS->PC Send long data NEXT NEXT 2a 2a 1 Receive long data 2a 2a 10 Send short message ProcessInstruction(2a) Store -Measurement direction. Inform leaf nodes -Measurement direction 10 Receive short message 2b 2b ProcessInstruction(2b) Store -Measurement direction. 10 10 ProcessInstruction(10) NEXT NEXT NEXT 4 4 4 4 ProcessInstruction(4) Store -NExT parameters (e.g., nfft) 10 10 ProcessInstruction(10) NEXT NEXT NEXT 3c 3c 3c 3c ProcessInstruction(3c) Store -Number of samples 10 10 ProcessInstruction(10) NEXT NEXT 2x NEXT 2x 2x 2x Figure 7.26. The implementation block diagram of monitoring in a sensor community (1). 130
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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
Page 85 and 86: Time (sec) 80 60 40 20 0 -20 -40 -6
Page 87 and 88: Difficulties encountered in realizi
Page 89 and 90: 1.8715 x10 5 #ofdatablocks 1.871 me
Page 91 and 92: Before this decimation is applied,
Page 93 and 94: where xn is the original signal,
Page 95 and 96: Timer firing every T3 110 data poin
Page 97 and 98: locks before or after the current b
Page 99 and 100: Chapter 6 ALGORITHMS In this chapte
Page 101 and 102: The eigenproblem of the system matr
Page 103 and 104: where M 0 is the mass matrix of the
Page 105 and 106: same community, eliminating the nee
Page 107 and 108: measurement or mass perturbation ca
Page 109 and 110: these algorithms are implemented on
Page 111 and 112: 10 0 10 -2 10 -4 0 500 1000 1500 20
Page 113 and 114: Table 7.1. SVD Accuracy Check on Ma
Page 115 and 116: 7.1.4 Complex matrix inverse A comp
Page 117 and 118: Figure 7.9. Details of the joint (G
Page 119 and 120: Figure 7.13. Amplifier (Gao, 2005).
Page 121 and 122: 0.08 0.2 Acceleration (g) 0.04 0 -0
Page 123 and 124: 3 Imote2_2/Imote2_1 Imote2_1/Siglab
Page 125 and 126: 200 3 Phase of spectral densities (
Page 127 and 128: 1.5 x10-17 Time (sec) Difference in
Page 129 and 130: input forces applied at nodes in th
Page 131 and 132: CH1 CH2 CH3 …. CHn-1 CHn Initiali
Page 133 and 134: 1 2 Node ID 102 RETAKE 1 3 4 INCONS
Page 135: Initialization: within local sensor
Page 139 and 140: PC Base station Manager sensor Clus
Page 141 and 142: PC Base station Manager sensor Clus
Page 143 and 144: Table 7.7. Instructions in DCS Code
Page 145 and 146: EXPERIMENTAL VERIFICATION Chapter 8
Page 147 and 148: 8 x10-3 Time (sec) Correlation func
Page 149 and 150: Table 8.2. Mass Normalization Const
Page 151 and 152: 1 2 Node ID 67 RETAKE 0 3 4 ID 67 #
Page 153 and 154: for a SHM strategy does not necessa
Page 155 and 156: are saved. The 420 seconds listed a
Page 157 and 158: 1 1 Normalized accumulated stress m
Page 163 and 164: Table 8.5. Summary of False Damage
Page 165 and 166: Table 8.7. Summary of False Damage
Page 167 and 168: e scalability, autonomous distribut
Page 169 and 170: The lowest frequencies of interest
Page 171 and 172: structural vibration is considered
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 and 180: Kling, R. (2003). “Intel Mote: an
Page 181 and 182: Mufti, A. A. (2003). “Integration
Page 183 and 184: Sazonov, E., Janoyan, K., & Jha, R.
Page 185 and 186: Yi, J.-H. & Yun, C.-B. (2004). “C
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