Embedded Networks Laboratory
A Wireless Sensor Network for Structural
Health Monitoring:
Performance and Experience
(Wisden)
Jeongyeup Paek
Krishna Chintalapudi, John Caffrey, Ramesh Govindan, Sami Masri

Embedded Networks Laboratory
• Introduction
• Wisden Overview
• Impact of Application Requirements on Design
• System Performance and Characterization
• Conclusion
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Embedded Networks Laboratory
• Structural Health Monitoring (SHM)
– Assess the integrity of structures.
– Detection and localization of damages in structures.
• Why wireless sensor network (WSN)?
– Ease and flexibility of deployment
– Low maintenance and deployment cost
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Embedded Networks Laboratory
• A wireless multi-hop sensor network based data acquisition system for structural health monitoring.
– Reliable data delivery over multiple hops.
– Time-synchronized data delivery from multiple sensor nodes.
– Data compression at the source node to relieve bandwidth bottleneck.
– Ease and flexibility of deployment.
“A Wireless Sensor Network for Structural Monitoring”
, Ning Xu, Sumit Rangwala, Krishna
Chintalapudi, Deepak Ganesan, Alan Broad, Ramesh Govindan, Deborah Estrin, In Proceedings of the ACM Conference on Embedded Networked Sensor Systems, Nov.2004
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Embedded Networks Laboratory
What you’ve designed in the lab may not work in the real deployment…

Embedded Networks Laboratory
Wisden
Initial
Re-design
Design
Application
Requirements
New
Wisden
In-lab
Experiments
Hardware
Limitations
Realistic
Deployments
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Embedded Networks Laboratory
• Introduction
• Wisden Overview
•
Impact of Application Requirements on
Design
• System Performance and Characterization
• Conclusion
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Embedded Networks Laboratory
Application
Requirements
Platform
Limitations
Fidelity of
Data
Higher
Sampling Rate
Onset Detector
Re-design of
Wisden
System
Engineering
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Embedded Networks Laboratory
High Damping Characteristics and Need for High Sampling Rates
• Real structures are heavily damped.
– Vibration is completely damped within 1 second.
• Need more than Nyquist rate
– 50Hz is not enough although structure’s modal frequencies are ~20Hz.
– Higher sampling rate required in highly damped structures.
Experimental data from our test structure:
50Hz Sampling
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Embedded Networks Laboratory
High Damping Characteristics and Need for High Sampling Rates (cont’)
• How high?
– ‘10 times over sampling’
– At least 200 Hz ~.
• But, hardware artifacts limit the achievable sampling rates.
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Embedded Networks Laboratory
• Bandwidth ≠ real achievable data rate
– The rate at which the Wisden application in a single node can send “data”, excluding any overheads.
Mica2
MicaZ
Expected Packet Rate from nominal bandwidth
36.36 pkts/sec
452.89 pkts/sec
Achievable Packet
Transmission Rate
22.17 pkts/sec
153.37 pkts/sec
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Embedded Networks Laboratory
• Number of nodes and the topology also affects the rate at which each node can transmit, due to contention.
sink
1/N
1/(2N-1) sink
In one-hop topology of 14 nodes:
Achievable
Packet Rate
Achievable
Sampling Rate
Estimation from
‘bandwidth’
Mica2 1.58 pkts/sec
MicaZ 10.95 pkts/sec
28.50 Hz
197.19 Hz
46.74 Hz
582.28 Hz
In one-hop topology of 14 nodes:
Achievable
Packet Rate
Mica2 0.82 pkts/sec
MicaZ 5.68 pkts/sec
Achievable
Sampling Rate
14.78 Hz
102.24 Hz
Estimation from
‘bandwidth’
24.24 Hz
301.92 Hz
Achievable sampling rate without compression 14

Embedded Networks Laboratory
• Wisden uses EEPROM to store packets to ensure reliable delivery of samples.
• EEPROM read/write takes time, and this directly limits the packet processing rate
• Bus conflict between the vibration card and EEPROM made it worse.
EEPROM Access Latency
Worst Case
Average
0 50 time (ms)
100 150
Write/pkt
Read/pkt
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Embedded Networks Laboratory
• Sampling rate is limited by EEPROM access latency.
– And this cannot be relieved by compression.
• “We can go around the transmission rate limitation by compression (iff the duty cycle of seismic activity is low enough). We can just send it later”
• “But if we cannot store it in the EEPROM at any time, we can never guarantee the delivery”
Worst Case
Packet generation rate limit
9.03pkts/s
Limits on sampling rate
162.5Hz
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Embedded Networks Laboratory
• Limit due to transmission rate
– Depends on number of nodes and topology.
– In the worst case topology of 14 nodes, we can only inject 5.6 pkts/sec.
Without compression, this can only achieve 100Hz. (MicaZ)
– Can be relieved by compression.
• Limit due to EEPROM access latency
– Independent of number of nodes or topology.
– But cannot be relieved by compression.
– In the worst case, we can safely achieve around 160Hz only.
• Wisden Re-design
– With careful design of buffering and compression, we were able to achieve 200Hz.
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Embedded Networks Laboratory
Application
Requirements
Platform
Limitations
Fidelity of
Data
Higher
Sampling Rate
Onset Detector
Re-design of
Wisden
System
Engineering
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Embedded Networks Laboratory
Need for Re-designing Wisden
Compression Scheme
• Original Wisden compression scheme
– Allow for variation in noise, and suppress quiescent period.
• low frequency modes are often clipped !!
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Embedded Networks Laboratory
Need for Re-designing Wisden
Compression Scheme (cont’)
• Also, low-energy / faster decaying high frequency modes are eliminated.
 Need to re-design the compression scheme.
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• Motivation
– To preserve the fidelity of the structure’s frequency response.
• Onset Detection
– Track noise mean, noise stdev, and signal envelope.
– If the signal envelope jumps out of the expected noise variation range, onset is detected.
Embedded Networks Laboratory
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Embedded Networks Laboratory
• Data Compression with Onset
Detector
– Detect the start and the end of significant event.
– Transmit data without compression during this period.
• Deployment experience
– Mathematically predicted parameter didn’t work well.
– Noise characteristics are not
Gaussian!
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Embedded Networks Laboratory
• Introduction
• Wisden Overview
• Impact of Application Requirements on Design
•
System Performance and Characterization
• Conclusion
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Embedded Networks Laboratory
• Full-scale realistic imitation of a 28’ X 48’ hospital ceiling
• Instrumented with drop ceiling, electric lights, fire sprinklers, and water pipes carrying water.
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Embedded Networks Laboratory
• 14 MicaZ node network
– 2~4 hop: multi-hop network
– 200Hz, single-axis sampling
• 5 minute experiment with
40 seconds of forced vibration
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Embedded Networks Laboratory
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Embedded Networks Laboratory
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Embedded Networks Laboratory
• Achieved 100% delivery
– With 9.5% of the packets being retransmitted
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Embedded Networks Laboratory
Packet
Generation: R
Packet
Transmission: r
1/R
1/r
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Embedded Networks Laboratory
Comparison of deployments on
Mica2 and MicaZ platforms
• Setup
– 7 Mica2 node, and 7-MicaZ node Wisden network colocated.
– 100 Hz, dual-axis sampling.
– Data collected simultaneously.
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Embedded Networks Laboratory
Results: Mica2 and MicaZ Comparison
• MicaZ outperforms Mica2
– Not surprising!!
– Mica2 had 7 times larger average latency.
– Better link quality. (97.8% vs. 93.4%)
– Less retransmissions. (3.5% vs. 7.2%)
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Embedded Networks Laboratory
•
Wisden
– Data acquisition system for Structural Health Monitoring.
– Re-designed through the experiences learned from the series of realistic deployments and experiments.
– Delivers time synchronized vibration data reliably at a sampling frequency of 200Hz across multiple hops.
• Future Work
– Wisden on hierarchical network for scalability
• Wisden software (ver-0.2) is available at
– http://enl.usc.edu
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Embedded Networks Laboratory