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A Wireless Sensor Network for Structural Health Monitoring: Performance and Experience (Wisden)

A Wireless Sensor Network for Structural Health Monitoring: Performance and Experience (Wisden). Jeongyeup Paek. Krishna Chintalapudi, John Caffrey, Ramesh Govindan, Sami Masri. Overview. Introduction Wisden Overview Impact of Application Requirements on Design

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A Wireless Sensor Network for Structural Health Monitoring: Performance and Experience (Wisden)

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  1. 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

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

  6. Deployment and Re-design Application Requirements Wisden Initial Design Re-design New Wisden In-lab Experiments Realistic Deployments Hardware Limitations

  7. Overview • Introduction • Wisden Overview • Impact of Application Requirements on Design • System Performance and Characterization • Conclusion

  8. Application Requirements Platform Limitations Fidelity of Data Higher Sampling Rate System Engineering Re-design of Wisden Onset Detector Roadmap

  9. 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

  10. 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.

  11. 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.

  12. … sink 1/N … sink 1/(2N-1) Transmission Rate Limits (cont’) • Number of nodes and the topology also affects the rate at which each node can transmit, due to contention. Achievable sampling rate without compression

  13. 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.

  14. 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”

  15. 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.

  16. Fidelity of Data Re-design of Wisden Onset Detector Roadmap Application Requirements Platform Limitations Higher Sampling Rate System Engineering

  17. 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 !!

  18. 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.

  19. 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.

  20. 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!

  21. Overview • Introduction • Wisden Overview • Impact of Application Requirements on Design • System Performance and Characterization • Conclusion

  22. 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.

  23. 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

  24. Data validation

  25. Onset Detector Performance

  26. System Evaluation • Achieved 100% delivery • With 9.5% of the packets being retransmitted

  27. 1/R 1/r Latency Calculation Packet Generation: R Packet Transmission: r

  28. 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.

  29. 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%)

  30. 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

  31. Thank you

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