Structural Health Monitoring Using Smart Sensors - ideals ...

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5.3 Synchronized sensing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 5.3.1 Time synchronization effect on SHM applications . . . . . . . . . . . . 74 5.3.2 Estimation on time synchronization error . . . . . . . . . . . . . . . . . . . . 77 5.3.3 Issues toward synchronized sensing . . . . . . . . . . . . . . . . . . . . . . . . 79 5.3.4 Realization of synchronized sensing . . . . . . . . . . . . . . . . . . . . . . . . 82 5.4 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 91 CHAPTER 6 ALGORITHMS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 6.1 Natural Excitation Technique . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 6.2 Eigensystem Realization Algorithm . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 6.3 Damage Locating Vector method . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 6.4 Distributed Computing Strategy for SHM . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 6.5 Stochastic Damage Locating Vector method . . . . . . . . . . . . . . . . . . . . . . . . . 98 6.6 Extension of DCS for SHM with the SDLV method . . . . . . . . . . . . . . . . . . 101 6.7 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 101 CHAPTER 7 REALIZATION OF DCS FOR SHM . . . . . . . . . . . . . . . . . . . . . . . 103 7.1 Functions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 7.1.1 Fast Fourier Transform . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 103 7.1.2 Singular value decomposition . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104 7.1.3 Eigensolver . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 106 7.1.4 Complex matrix inverse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 7.1.5 Sort . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 7.2 DCS implementation . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 7.2.1 Sensing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 108 7.2.2 NExT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 118 7.2.3 ERA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 120 7.2.4 DLV methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 121 7.2.5 DCS logic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 122 7.2.6 Final implementation on the Imote2 . . . . . . . . . . . . . . . . . . . . . . . 126 7.3 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 129 CHAPTER 8 EXPERIMENTAL VERIFICATION . . . . . . . . . . . . . . . . . . . . . . . 138 8.1 Experimental setup . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 138 8.2 NExT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140 8.3 ERA . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141 8.4 DLV methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141 8.5 DCS logic . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143 8.6 Calculation and communication time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 8.7 Battery life . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148 8.8 Damage detection results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149 8.9 Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 CHAPTER 9 CONCLUSIONS AND FUTURE STUDIES . . . . . . . . . . . . . . . . . . 159 9.1 Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159 9.2 Future studies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161 9.2.1 Sensing capability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 161 9.2.2 Damage detection capability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 162
9.2.3 Power harvesting . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163 9.2.4 Power management and scheduling . . . . . . . . . . . . . . . . . . . . . . . 164 9.2.5 <strong>Monitoring</strong> of occasional events such as earthquakes . . . . . . . . . 164 9.2.6 Multihop . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164 9.2.7 Communication range adjustment . . . . . . . . . . . . . . . . . . . . . . . . 165 9.2.8 Reliability of the system . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165 9.2.9 Environmental hardening . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 165 9.2.10 Multiple purpose usage of smart sensors . . . . . . . . . . . . . . . . . . 165 REFERENCES . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166
Page 1 and 2: NSEL Report Series Report No. NSEL-
Page 3 and 4: The Newmark Structural Engineering
Page 5: Contents Page CHAPTER 1 INTRODUCTIO
Page 9 and 10: damage/deterioration is intrinsical
Page 11 and 12: scalability to a large number of sm
Page 13 and 14: logic circuit. However, FPGAs are m
Page 15 and 16: easons, smart sensors spatially dis
Page 17 and 18: Figure 2.1. EYES project sensor pro
Page 19 and 20: Table 2.1. Smart Sensor Specificati
Page 21 and 22: While a number of sensor boards for
Page 23 and 24: need to be within the coordinator's
Page 25 and 26: eing examined (Moore et al., 2001).
Page 27 and 28: structural damage, the analysis to
Page 29 and 30: that sensor installation cost inclu
Page 31 and 32: (2004) indicated that this accelero
Page 33 and 34: different type of sensors connected
Page 35 and 36: Chapter 3 SHM ARCHITECTURE This cha
Page 37 and 38: Modal operation Several modal opera
Page 39 and 40: its spatial gradient, which is clai
Page 41 and 42: Manager node Cluster head node Leaf
Page 43 and 44: commands; execution timing cannot b
Page 45 and 46: Table 3.2. Desirable Characteristic
Page 47 and 48: Table 3.2. Desirable Characteristic
Page 49 and 50: Figure 4.1. Foil strain gage. strai
Page 51 and 52: dB A s Figure 4.4. AA filter design
Page 53 and 54: 8.32F 3V 3.45F 3V Input 1K 1K 1K 1K
Page 55 and 56: Strain ( ) 80 w/o Digital Filter 60
Page 57 and 58:
performance was experimentally vali
Page 59 and 60:
anges from 10 to 20. If 50 percent
Page 61 and 62:
Node 1 x1 i =1,2,…,ns E x 1
Page 63 and 64:
Correlation function estimate (m 2
Page 65 and 66:
Figure 5.5. Effect of data loss and
Page 67 and 68:
Frobenius norm. Because only a limi
Page 69 and 70:
90 80 70 60 50 Node1 Node2 Node3 No
Page 71 and 72:
On reception of a NACK, the sender
Page 73 and 74:
Sender SendLData.send() Pack parame
Page 75 and 76:
If there are missing packets, the r
Page 77 and 78:
Sender SendLData.bcast() Pack param
Page 79 and 80:
Sender Send a packet • Sender sen
Page 81 and 82:
utilized in SHM applications follow
Page 83 and 84:
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 and 136:
Initialization: within local sensor
Page 137 and 138:
PC Base station Manager sensor Clus
Page 139 and 140:
Page 141 and 142:
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 159 and 160:
Page 161 and 162:
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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