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Deploying Wireless Sensor Networks with Fault Tolerance for Structural Health Monitoring

Deploying Wireless Sensor Networks with Fault Tolerance for Structural Health Monitoring. Md Zakirul Alam Bhuiyan. (Joint work with Jiannong Cao and Guojun Wang). The 8th IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS '12), Hangzhou, China, May 16-18, 2012. .

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Deploying Wireless Sensor Networks with Fault Tolerance for Structural Health Monitoring

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  1. Deploying Wireless Sensor Networks with Fault Tolerance for Structural Health Monitoring Md Zakirul Alam Bhuiyan (Joint work with Jiannong Cao and Guojun Wang) The 8th IEEE International Conference on Distributed Computing in Sensor Systems (DCOSS '12), Hangzhou, China, May 16-18, 2012. • Email: zakirulalam@gmail.com

  2. Outline • Structural Health Monitoring (SHM) • SHM and other WSN Applications • Fault-Tolerant WSN deployment • Sensor Placement • Backup Sensor Placement • Simulation and Implementation • Conclusions and Limitations

  3. What is a SHM System? A type of system that provides information about any damage occurring in the structure. - e. g. buildings, bridges, aircrafts, nuclear plants Damage- is a significant changes in the structure

  4. Why SHM System? USAF F-16 aircraft at an airshow at Mountain Home Air Force Base, Idaho, on Sept. 14, 2003 A road bridge in Fenghuang, China collapsed at 2007, killing 64 people and injuring 22 A road bridge in Zhuzhou, China, collapsed at 2009, killing 9 people and injuring 16 I-35 Bridge in MN, USA collapsed at 2007, killing 13 people and injuring 145 American Airlines 587, Airbus A300-600, Nov. 12, 2001. 1Structural Failure (damage) is about 25% 1http://www.planecrashinfo.com/cause.htm

  5. Designing a SHM System • In designing a SHM system, we need to know: • The structural phenomena to be monitored • Sensors • Time strategies • Damage detection algorithms • Data transfer and storage mechanism

  6. WSN-Based SHMA New Paradigm of SHM Systems • Smart sensor nodes • Sensors • CPU • Wireless transceivers • Wireless sensor networks

  7. SHM vs. Other WSN Applications

  8. Sensor Placement on Civil Structure SHM vs. Other WSN Applications The first and fundamental problem in SHM

  9. SHM vs. Other WSN Applications • Placement in general WSN application • Random, uniform, grids/trees, rectangular, circular • Are they practically meaningful to the respective application demands? e.g., SHM • Anywhere/Anytime? • Constraint: • Energy, communication, connectivity, data delivery, fault-tolerance Difficulty: Monitoring @ some specific locations where the damage sensitivity is high

  10. Sensor Placement on Civil Structures • Engineering-driven optimal deployment: • Sensor are placed at optimal locations in order to achieve the best estimates of physical properties of a civil structure. • EFI (EFfective Independence) method • Genetic algorithm, etc. 2,3 2. B. Li, D. Wang, F. Wang, and Y. Q. Ni, “High quality sensor placement for SHM systems: Refocusing on application demands,” INFOCOM, 2010. 3. D. Kammer, “Sensor Placement for on-orbit Modal Identification and Correlation of Large Space Structures,” Journal of Guidance, 14: 251-259, 1991.

  11. Sensor Placement on Civil Structures • EFI Method: • It is used to maximize both the spatial independence and sensor signal strength of the N targeted location by maximizing the determinant of the associated Fisher information matrix (FIM)3,4 • EFI gives EFI values as the location quality • Sensors are placed at locations with high EFI values. 3. D. Kammer, “Sensor Placement for on-orbit Modal Identification and Correlation of Large Space Structures,” Journal of Guidance, 14: 251-259, 1991. 4. M. Meo and G. Zumpano, “On the Optimal Sensor Placement Techniques for a Bridge Structure,” Engineering Structures, 27 (2005): 1488- 1497, 2005.

  12. Sensor Placement on Civil Structures • There are Mlocations e.g., 100 candidate locations • Given Nsensors e.g., 20 sensors • We need to find the optimal locations which are with high EFI values

  13. Problem Definition (i) • Our problem is to get N sensors that are placed by finding candidate locations out of M using EFI values. • Constraints • Connectivity • Data delivery • Heavy communication load • Objectives: Maximize network lifetime → long-term SHM

  14. Challenges • Our problem is to get N sensors that are placed by finding candidate locations out of M using EFI values. • Constraints • Connectivity • Data delivery • Heavy communication load • Objectives: Maximize network lifetime → long-term SHM Can we guarantee that this deployed WSN is able to monitor a civil infrastructure smoothly? ? Energy constraint! Faults/Failure (data packet-losses) (weak/strong?) (high rate data collection) (congestion)

  15. 2 3 1 1 3 2 the points, where the sensors or communication link failures are highly possible Challenges Repairing Points (RPs) Fault/ Failure Points Separable Points A connecting point of other several sensors, whose removal results in a disconnected network Critical Middle points A longest transmission distance (duv) and the link between sensor u and v is vulnerable Isolated Points u doesn't have a path or communication to v, or may receive broken messages

  16. Challenges • When one or more sensors fail that placed at the optimal locations • How to continue obtaining adequate information of structural behavior or changes in the structure? • How to guarantee fault tolerance? Backup Sensor Placement

  17. Backup Sensor Placement (BSP) (1/2) • Idea: Placing a small set of backup sensors by finding remaining/unused near optimal locations using EFI • Objectives • Mitigating communication failure • Mitigating single-point failure: • Backup sensor can take the role when a primary sensor fails • Mitigating Packet losses • Prolonging network lifetime

  18. Backup Sensor Placement (BSP) (2/2) • Where to place? • @ Remaining /unused locations • There may have a lot of unused locations available in a structure. M-N • How many backup sensors are there available? R (<N), N-R? N+R? • How to find the locations for the backup sensors? at near/the RPs

  19. Problem Definition (ii) • The problem is to place a set B of Rbackup sensors into a network with N sensors by optimally finding locations out of M-Nremaining/unused locations near the RPs such that: • (i) the network is guaranteed to be fault tolerant to the presence of up to k-1 sensors fault and data packet-loss • (ii) T is prolonged under constraints of long distance communication, k -1 connectivity, data delivery.

  20. Repairing the Network through BSP • Repairing points: • BSP1-Separable Points (RPi) • BSP1-Critical Middle Points (RPi) • BSP1- Isolated Points (RPi)

  21. Algorithm: BSP

  22. Algorithm: Search-and-Place

  23. A total of 100 ((N=80)+ (R=20)) sensor nodes First place the primary sensors and then backup sensors fr → the percentage of faults/ failures, k-connectivity, Metric: Communication cost 5,6, T→ Network lifetime Performance Evaluation (1/4) Simulations Fault/Failure Injection • Communication failure (invalidating communication module at different points of time • Providing limited power 5. S. Olariu and I. Stojmenovic, “Design Guidelines for Maximizing Lifetime and Avoiding Energy Holes in Sensor Networks with Uniform Distribution and Uniform Reporting,” in IEEE INFOCOM, 2006. 6. W. Heinzelman, A. Chandrakasan, and H. Balakrishnan, “Energy-efficient Communication Protocol for Wireless Micro-sensor Networks,” in IEEE HICSS, 2000.

  24. FTSHM SPEM5 RELAY6 Performance Evaluation (2/4) The communication cost in the network under sensor faults The network lifetime (T) vs. the number of sensors (m) 7. Structural Health Monitoring for Guangzhou New TV Tower Using Sensor Networks. [online]: http://www.cse.polyu.edu.hk/benchmark/. 8. K. Xu et al. “Relay Node Deployment Strategies in Heterogeneous Wireless Sensor Networks, ”IEEE Trans. on Mobile Computing,9(2): 145-159, 2010 [online]: http://www.cse.polyu.edu.hk/benchmark/

  25. Sensor deployment on LSK building 15 floors At least 220 locations (M) 22 sensors (m) [N=16, R=6] Ambient vibration Sensor fault injection: Sensors attached on the 5rd and 7th floors are given minimum power at around 2nd hour, we remove one sensor from the 11th floor, Observation: Impact of monitoring performance Communication cost Network lifetime Performance Evaluation (3/4) Real Implementation

  26. Performance Evaluation (4/4) Results The total communication cost in the network achieved in different days of deployment The identified affected mode shape under sensor fault (on day 2)

  27. Conclusions and Limitations • A new way to incorporate both WSN and SHM requirements and make use of traditional method used by civil, structural, or mechanical engineering domains for resource-constrained WSNs. • Besides SHM, the idea of backup sensor placement can also be used in generic WSN applications ← repairing points. • Limitations: • Detailed theoretical analysis and the cost of backup sensor placement algorithms. • Network performance analysis and fault tolerance under physical damage injection.

  28. Q&A Contact Info: • Alam, Email: zakirulalam@gmail.com

  29. Works @ HK PolyU • Xuefeng Liu, Jiannong Cao, MdZakirul Alam Bhuiyan, Steven Lai, Hejun Wu, and Guojun Wang, “Fault Tolerant WSN-Based Structural Health Monitoring," DSN 2011 • X. Liu, J. Cao, S. Lai, C. Yang, H. Wu, and Y. Xu, “Energy Efficient Clustering for WSN-based Structural Health Monitoring”, in IEEE INFOCOM, 2011. • B. Li, D. Wang, F. Wang, and Y. Q. Ni, “High quality Sensor Placement for SHM Systems: Refocusing on Application Demands,” in IEEE INFOCOM, 2010.

  30. Related WorksGeumdang Bridge (Icheon, Korea) • Length: 122m • U Michigan & Stanford (2005): • Specially designed wireless sensor node prototypes • 14 sensor nodes, sampling at 200 Hz, constitute a centralized single-hop network 2 Lynch, J., et al. Validation of a large-scale wireless structural monitoring system on the Geumdang Bridge. 2005: Citesee 3 Lynch, J., et al., Performance monitoring of the Geumdang Bridge using a dense network of high-resolution wireless sensors. Smart Materials and Structures, 2006. 15: p. 1561.

  31. Wired vs. WSN based SHM Systems

  32. Golden Gate Bridge (San Francisco, USA) • Length: 1280m • UC Berkeley (2007): • 64 MicaZ motes, with addition sensor board and antenna, sampling at 1kHz rate • Sampled data is collected over a 46-hop network 4 Kim, S., et al. Health monitoring of civil infrastructures using wireless sensor networks. 2007 IPSN’07

  33. Guangzhou New TV Tower, China (GNTVT) • A height of 610m, with a 156m antenna • The main tower reached to a full height of 454m. • Wired sensor networks are currently running on the tower • A WSN is also varied on the tower5 5. B. Li, D. Wang, F. Wang, and Y. Q. Ni, “High quality sensor placement for SHM systems: Refocusing on application demands,” INFOCOM, 2010.

  34. Test Structure: 12 floors, vibrating under hammer strike Faulty nodes: Sensors attached on the 3rd and 7th floors are released Structural damage: Releasing a support ring on the 9th floor Performance Evaluation (2/3) Implementation

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