embedded networks laboratory a wireless sensor network for structural health monitoring: performance...
TRANSCRIPT
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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
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Embedded Networks Laboratory
Overview
• Introduction
• Wisden Overview
• Impact of Application Requirements on Design
• System Performance and Characterization
• Conclusion
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Embedded Networks Laboratory
Introduction
• 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
Wisden
• 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…
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Embedded Networks Laboratory
Deployment and Re-design
New Wisden
Initial Design
In-lab Experiments
Wisden
Realistic Deployments
Re-design
Application Requirements
Hardware Limitations
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Embedded Networks Laboratory
Overview
• Introduction
• Wisden Overview
• Impact of Application Requirements on Design
• System Performance and Characterization
• Conclusion
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Embedded Networks Laboratory
Roadmap
Application Requirements
Platform Limitations
Fidelity of Data
Onset Detector
Higher Sampling Rate
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
Transmission Rate Limits
• Bandwidth ≠ real achievable data rate
– The rate at which the Wisden application in a single node can send “data”, excluding any overheads.
Expected Packet Rate from nominal bandwidth
Achievable Packet Transmission Rate
Mica2 36.36 pkts/sec 22.17 pkts/sec
MicaZ 452.89 pkts/sec 153.37 pkts/sec
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Embedded Networks Laboratory
Transmission Rate Limits (cont’)
In one-hop topology of 14 nodes:
Achievable Packet Rate
Achievable Sampling Rate
Estimation from ‘bandwidth’
Mica2 1.58 pkts/sec 28.50 Hz 46.74 Hz
MicaZ 10.95 pkts/sec 197.19 Hz 582.28 Hz
…
1/(2N-1)
sink
…
1/N
sink
Achievable sampling rate without compression
• Number of nodes and the topology also affects the rate at which each node can transmit, due to contention.
In one-hop topology of 14 nodes:
Achievable Packet Rate
Achievable Sampling Rate
Estimation from ‘bandwidth’
Mica2 0.82 pkts/sec 14.78 Hz 24.24 Hz
MicaZ 5.68 pkts/sec 102.24 Hz 301.92 Hz
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Embedded Networks Laboratory
EEPROM Access Latency
• 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.
0 50 100 150
time (ms)
Average
Worst Case
EEPROM Access Latency
Write/pkt
Read/pkt
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Embedded Networks Laboratory
EEPROM Access Latency (cont’)
• 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”
Packet generation rate limit Limits on sampling rate
Worst Case 9.03pkts/s 162.5Hz
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Embedded Networks Laboratory
Sampling Rate Limits (Summary)
• 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
Roadmap
Application Requirements
Platform Limitations
Fidelity of Data
Onset Detector
Higher Sampling Rate
Re-design of Wisden
System Engineering
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Embedded Networks Laboratory
Need for Re-designing Wisden Compression Scheme
• low frequency modes are often clipped !!
• Original Wisden compression scheme– Allow for variation in noise, and suppress quiescent period.
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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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Embedded Networks Laboratory
Onset Detector
• 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.
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Embedded Networks Laboratory
Onset Detector (cont’)
• 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
Overview
• Introduction
• Wisden Overview
• Impact of Application Requirements on Design
• System Performance and Characterization
• Conclusion
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Embedded Networks Laboratory
Seismic Test Structure
• 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
Deployment Setup
• 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
Data validation
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Embedded Networks Laboratory
Onset Detector Performance
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Embedded Networks Laboratory
System Evaluation
• Achieved 100% delivery– With 9.5% of the packets being retransmitted
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Embedded Networks Laboratory
Latency Calculation
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 co-located.
– 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
Conclusion and Future Work
• 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
Thank you