a wireless sensor network for structural health monitoring: performance and experience (wisden)

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

2


Overview

• Introduction

• Wisden Overview

• Impact of Application Requirements on Design

• System Performance and Characterization

• Conclusion

3


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

4


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


What you’ve designed in the lab may not work in the real deployment…

8


Deployment and Re-design

New Wisden

Initial Design

In-lab Experiments

Wisden

Realistic Deployments

Re-design

Application Requirements

Hardware Limitations

9


Overview

• Introduction

• Wisden Overview



• Conclusion

10


Roadmap


Platform Limitations

Fidelity of Data

Onset Detector

Higher Sampling Rate

Re-design of Wisden

System Engineering

11


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

12


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.

13


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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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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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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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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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.

19


Roadmap


Platform Limitations

Fidelity of Data

Onset Detector

Higher Sampling Rate

Re-design of Wisden

System Engineering

20


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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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.

22


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.

23


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!

24


Overview

• Introduction

• Wisden Overview



• Conclusion

25


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.

26


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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Data validation

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Onset Detector Performance

29


System Evaluation

• Achieved 100% delivery– With 9.5% of the packets being retransmitted

30


Latency Calculation

Packet Generation: R

Packet Transmission: r

1/R

1/r

31


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.

32


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%)

33


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


Thank you

a wireless sensor network for structural health monitoring: performance and experience (wisden)

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