Structural Health Monitoring Using Smart Sensors - ideals ...

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Sufficient RAM, flash memory and RF bandwidth Because SHM for civil infrastructure measures dynamic vibrations of large structures at high sampling frequencies, the amount of data to be saved, processed, and transmitted is large even after local data processing. The sampling frequency of dynamic vibration measurements is often higher than 100 Hz. RAM size, flash memory size, and radio throughput are desirably large, though power consumption still needs to remain moderate. Environmentally hardened Because smart sensors placed on structures are often subjected to severe environmental conditions (e.g., wind, rain, sunshine, extreme temperature, and vibration), the sensors need to be rugged. Packaging is one solution. Without ruggedness, severe environmental conditions may result in faulty data or node loss. Open source OS and interface The operating system (OS) and the interface should be open to the public. Tasks are ideally optimized to make efficient use of the limited resources. Services offered by the OS may not give the best solution for a specific task. Algorithms and middleware services to be implemented may work more efficiently if the OS is customized. Certain algorithms or middleware services may be implementable only if the OS is customized. In such cases, users should have access to the source of the OS. Also, open source OS and interfaces allow user communities to participate in improving OS and software. In particular, at this early stage of smart sensor network research, contributions from broad communities are important to improve the technology. Open source OS and interfaces will advance smart sensor network technology and its application to SHM. 3.2 SHM system architecture An SHM system architecture to address many of the difficulties explained in the previous chapter and the desirable characteristics is proposed herein. Network system architecture, smart sensor platform, middleware services, and algorithms to be employed in this report are described. 3.2.1 Network system architecture A homogeneous configuration with a single type of node is employed instead of the tiered system approaches employing powerful upper-level nodes and less powerful lowerlevel nodes. Note that even though only one type of node is deployed over a structure, a PC may be needed in this architecture as an interface to users. Usage of only one type of node allows for development of a simple and robust sensor network system, as explained later in this section. 33
Manager node Cluster head node Leaf node Base station Manager node Cluster head node Leaf node Base station (a) (b) Figure 3.1. SHM system architecture: Different roles are assigned to nodes in (a) and (b). In terms of functionality, smart sensor nodes in the proposed system are differentiated as follows: the base station, the manager node, cluster heads, and leaf nodes. All of the sensors deployed on a structure, in principle, work as leaf nodes. Leaf nodes receive commands from the other nodes and perform preprogrammed tasks such as sensing, data processing, and acknowledgment. A node in a local sensor community is assigned as a cluster head and coordinates most of the communication and data processing in the community. In addition to tasks inside the community, the cluster head communicates with the cluster heads of the neighboring communities to exchange information. One of the cluster heads also functions as the manager node. When intracluster RF communication spans multiple clusters, the manager deals with time sharing among clusters to avoid RF interference. The manager also exchanges packets with the leaf nodes to manage operations in which all of the leaf nodes participate; sensing that is triggered by the manager sensor is an example. The base station node is the gateway between smart sensor networks and the PC. The PC with a user interface sends commands and parameters to smart sensor networks via the base station. The PC also receives data and calculation results from the base station. While the base station can communicate with any node in direct communication range, most communication involving the base station is routed through the manager or cluster heads with the exception being transmission of a large amount of data or calculation results from leaf nodes to the PC for debugging purposes. Thus, smart sensors nodes are functionally differentiated into four categories (see Figure 3.1). This system architecture can be compared with tiered networks to clarify its characteristics. A tiered network assumes ample hardware resources at the upper level nodes. By reducing the constraints on hardware (i.e., power source, RAM space, flash memory space, radio bandwidth, etc.), a tiered network aims to implement more functionality on the network easily. However, such an assumption is not necessarily the case. When smart sensors are installed on a long suspension bridge, there needs to be 34
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 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: its spatial gradient, which is clai
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
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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
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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
Page 115 and 116:
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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input forces applied at nodes in th
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CH1 CH2 CH3 …. CHn-1 CHn Initiali
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1 2 Node ID 102 RETAKE 1 3 4 INCONS
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Initialization: within local sensor
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PC Base station Manager sensor Clus
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Page 141 and 142:
Page 143 and 144:
Table 7.7. Instructions in DCS Code
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EXPERIMENTAL VERIFICATION Chapter 8
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8 x10-3 Time (sec) Correlation func
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Table 8.2. Mass Normalization Const
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1 2 Node ID 67 RETAKE 0 3 4 ID 67 #
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for a SHM strategy does not necessa
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are saved. The 420 seconds listed a
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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
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Table 8.7. Summary of False Damage
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e scalability, autonomous distribut
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The lowest frequencies of interest
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structural vibration is considered
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REFERENCES Actis, R. L. & Dimarogon
Page 175 and 176:
Casciati, F., Faravelli, L, Borghet
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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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