Structural Health Monitoring Using Smart Sensors - ideals ...

More documents

Recommendations

Info

the communication quality, and the atmosphere attenuates the signal power over large distances. Moreover, its slow wave propagation speed becomes a serious problem for timing-critical applications. Laser communication can be classified as either passive or active communication, according to whether the laser signal is generated through a secondary source or not. Passive devices receive signals through a laser, and send back data depending on the received command by modulating mirrors located on the passive device. Without the necessity of generating a laser signal, the passive device consumes a small amount of power. Active laser communication points an on-board laser transmitter toward a receiver and transmits data. Long communication ranges, up to 21.4 km (Hollar, 2000), have been reported. Because of the short wavelength, i.e., 100 to 350 nm for lasers as compared to 0.01 to 30 m for RF, and the resultant small divergence, information can be transmitted at lower power than RF. However, searching for the correct receiver direction can take a significant amount of time, and the point-to-point communication is fixed unless the transmitter is redirected through a time- and power-consuming receiver search. Infrared communication uses infrared light with wave lengths ranging from 700 nm to 1 mm. IrDA, an infrared wireless communication technology, consumes significantly less power than RF transceivers (Miller, 2001). The IrDA, however, uses a relatively narrow focused beam which usually requires that the transmitter and the receiver be carefully aligned with each other. Most of the smart sensors to date employ RF-based wireless communication. As opposed to the laser and infrared communication, RF communication is omni-directional, and does not need direct line-of-sight. In the United States, the Federal Communications Commission (FCC) has allocated the three RF bands around 900 MHz, 2.4 GHz, and 5.0 GHz (0.33 m, 0.125 m, and 0.06 m, respectively, in terms of wavelength) as unlicensed industrial, scientific, and medical (ISM) bands. Many of today's wireless technologies operate on these ISM bands. Small RF chips, which require low power and have few external components, are available from many suppliers. For example, the CC1000 from Chipcon, Inc. (2007) consumes only 8.6-25.4 mA for transmission and 9.6 mA for reception at 868 MHz with a 3 V supply voltage. However, RF chip communication speed is typically limited; the throughput of the CC1000 is only 38.4 kbps. Omni-directional communication with moderate power consumption suits a dense array of smart sensors. RF communication in the ISM band has often been adapted for applications needing small amounts of data transfer such as temperature monitoring. The RF link also has a limited communication range. As the distance between transmitter and receiver gets longer, more data is lost. Communication between two nodes can be achieved by either home runs, where two nodes communicate with each other directly, or hopping, where nodes between two communication endpoints work as relay nodes. For communication in a network of a large number of smart sensors, hopping communication has advantages in terms of power. Power requirements for RF communication are proportional to the distance raised to some power. Depending on interference effects, the power requirement could be proportional to the fifth power of distance (Zhao & Guibas, 2004). Also, maximum transmission power for the ISM bands is restricted to be less than 1 W by FCC, limiting the communication range. For these 7
easons, smart sensors spatially distributed over large areas, as is the case for SHM of bridges and buildings, need to communicate with each other through hopping. However, this simple analysis on power consumption does not include all the communication related tasks affecting the total power consumption in a system. For example, waiting for possible incoming messages in a listening mode also consumes power. Additionally, latency and robustness concerns accompany a large number of relay nodes. Optimal design for communication range is sought with these considerations. Such RF communication links result in the following characteristics of smart sensors: (a) Wireless communication is not as fast as wired communication; (b) Data loss is inherent to exchange of communication packets; and (c) The network route is not physically fixed, which enables self-configuration and self-healing of networks, and dynamic routing with the help of the on-board microprocessor. Several standards have provided RF communication specifications. For example, the Bluetooth standard provides the radio link, baseband link, and the link manager protocol (the Open Systems Interconnection reference model; Zimmermann, 1980) for low-power Wireless Personal-Area Networking (WPAN). The expected application is short-range, low-power voice and data communication, such as Personal Digital Assistant (PDA), mobile phones, and laptops. Bluetooth is based on proximity networking at 2.4 GHz, with an expected communication range of around 100 m at an output power of 100 mW, although 1 and 2.5 mW specifications are also available. Data throughput is 723.1 Kbps. IEEE 802.11 is a Wireless Local Area Networking (WLAN) specification. The specification includes robust, Ethernet-style data networking components, such as a Transmission Control Protocol/Internet Protocol (TCP/IP) stack. At the expense of power consumption, this technology possesses communication ranges larger than 100 m and a throughput of up to 54 Mbps. For example, an 802.11b compatible transceiver chip, MAX2820 from Maxim Integrated Products, Inc. (2007), consumes more than 200 mW, while other external components also draw current. IEEE 802.11 technology is well-suited for devices with stable power supplies and high data rate requirements. The IEEE 802.15.4 standard defines the physical and Media Access Control (MAC) layer protocols for WPAN with low data rates but needing a very long battery life. The data rate is 250 Kbps. ZigBee is an industry consortium to promote this standard. The CC2420 from Chipcon, Inc. implements the IEEE 802.15.4 communication standard, consuming only 8.5-17.4 mA for transmission and 19.7 mA for reception. These RF communication standards bring significant benefit to smart sensor applications, though some applications may need customization. By using the standards, users can avoid the necessity to design all the layers of the OSI reference model (Zimmermann, 1980) from scratch. Users can choose a standard which best fits each application. Also the standards allow independently developed systems to communicate with each other easily. The available standards, however, do not necessarily offer the best RF solution to a specific smart sensor application. Users may want to customize the standards if available standards do not offer a suitable solution at the expense of losing compatibility with other systems. 8
Page 1 and 2: NSEL Report Series Report No. NSEL-
Page 3 and 4: The Newmark Structural Engineering
Page 5 and 6: Contents Page CHAPTER 1 INTRODUCTIO
Page 7 and 8: 9.2.3 Power harvesting . . . . . .
Page 9 and 10: damage/deterioration is intrinsical
Page 11 and 12: scalability to a large number of sm
Page 13: logic circuit. However, FPGAs are m
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
show all

Structural Health Monitoring Using Smart Sensors - ideals ...

You also want an ePaper? Increase the reach of your titles

Delete template?

Save as template?