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BRIMON: Wireless Sensor Network based Railway Bridge Monitoring

Kameswari Chebrolu Assistant Professor Department of Electrical Engineering IIT Kanpur http://home.iitk.ac.in/~chebrolu. BRIMON: Wireless Sensor Network based Railway Bridge Monitoring. People. Kameswari Chebrolu Bhaskaran Raman Nilesh Mishra Hemanth Haridas Phani Kumar Valiveti

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BRIMON: Wireless Sensor Network based Railway Bridge Monitoring

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  1. Kameswari Chebrolu Assistant Professor Department of Electrical Engineering IIT Kanpur http://home.iitk.ac.in/~chebrolu BRIMON: Wireless Sensor Network based Railway Bridge Monitoring

  2. People • Kameswari Chebrolu • Bhaskaran Raman • Nilesh Mishra • Hemanth Haridas • Phani Kumar Valiveti • Raj Kumar

  3. Motivation • Indian Railways consists of 1,20,000 bridges spread over a large geographical area • Many in weak and distressed conditions • 57% are over 80 years old • An automated system to track bridge's health is of utmost importance. • Short term monitoring • Long term monitoring

  4. Existing Techniques • Mostly wired solutions • Equipment is bulky and very expensive • Large setup time (few days) for short-term monitoring • Few wireless solutions • WISDEN (UCLA) • Continuous monitoring • Golden-gate bridge (UCB) • Short-term monitoring

  5. Problem Statement • Develop an easy to deploy, low maintenance and long-term structural health monitoring system for Railway bridges Easy to deploy: Huge number of bridges to monitor Low maintenance: Technical expertise is difficult to get Long-term: Useful to monitor a structure's health over time

  6. Application Requirements • What to measure? Acceleration in 3-axis of motion • Frequency components of interest 0.25-20Hz • How long to measure? • Forced vibrations: 20sec; Free vibrations: 20sec • Time Synchronization • Necessary only across node in a span • Need accuracy of 5ms 30-125m 3-axis accelerometers

  7. Implications of Requirements • 2km bridge can have as many as 200 sensors • 6 nodes per span; 60m span • Data collection duration: 40sec • Data generated by a node: 3 channels * 12 bits * 40 Hz * 40 sec = 57.6kbits • Maximum data from a data span (12 nodes): 691.2kbits • Maximum data generated by the sensors on the bridge: 1.44 MBytes

  8. Solution Approach • Battery operated wireless sensor motes • Cheap alternative • Easy to deploy and maintain • Eliminates hassle of laying cable to route data/power • No solar panels • Expensive and prone to theft • Sensors maybe placed under deck in shade Key Goal: Minimize energy consumption

  9. Hardware Details • Sensor mote: Tmote-Sky • 8 Mhz MSP430 processor • 250kbps 2.4Ghz radio complaint with 802.15.4 • MEMS based ADXL 203 accelerometer • Dual axis • Range is +/- 1.7g • Sensitivity 1000mv/g • 8dBi Omni Antenna

  10. Challenges • Event Detection • Cannot predict train arrival • To conserve power, sensor nodes have to duty-cycle (sleep + wake cycle) • Remote Access • Bridges may not have network coverage to transfer data to central server • Scalability • Can have as many as 200 sensors per bridge • Protocols and architecture needs to be scalable

  11. Outline • Motivation • Application Requirements • Challenges • Overview of Architecture • Event Detection • Data Transfer • Measurements on a Bridge • Conclusions

  12. Architecture Overview • Data span as an independent network • Each cluster operates on a different • channel Channel 5 Data Transport modules Channel 3 Clusters Channel 5 3 6 Event Signaling module (Channel 1) 1 2 3 Channel 3 4 5 6 1 2 4 5 Span Cluster heads 1 Piers

  13. Topology Formation 3 6 1 2 3 4 5 6 1 2 Channel 3 4 5 Channel 5

  14. Time Synchronization 3 6 1 2 3 4 5 6 1 2 Channel 3 4 5 Channel 5

  15. Sleep-Wakeup 3 6 1 2 3 4 5 6 1 2 Channel 3 4 5 Channel 1 Channel 5

  16. Command Control: Wakeup Train Arrival Detection 3 6 1 2 3 4 5 6 1 2 4 5

  17. VibrationSensing 3 6 1 2 3 4 5 6 1 2 4 5

  18. Data Gathering by individual cluster heads 3 6 1 2 3 4 5 6 1 2 Channel 3 4 5 Channel 5

  19. Sleep-Wakeup 3 6 1 2 3 4 5 6 1 2 Channel 3 4 5 Channel 1 Channel 5

  20. Data Uploading Train Detection 3 6 1 2 3 4 5 6 1 2 4 5

  21. Sleep-Wakeup 3 6 1 2 3 4 5 6 1 2 4 5

  22. Data Analysis Centre Send Data to Repository

  23. BriMon Architecture: Event Detection Span P Head node

  24. BriMon Architecture: Event Detection Span P Head node

  25. BriMon Architecture: Event Detection Span P Head node

  26. BriMon Architecture: Event Detection Span Head node

  27. Event Detection: Analysis • Question: What should be the duration of sleep and wake up? • Tdc = max time available between detection of oncoming train and data collection • Tcc = sleep/wakeup cycle = Tsl + Tw • Tw = Tdet + Tcd + Tpc (at head mote) • Tdet: Time taken to detect the train • Tcd : Maximum clock drift • Tpc : Time taken for command propogation

  28. Event Detection • Tw = 2*Tcd + Tpc (at non-head mote) • Ans: Tdc = Tcc + Tw = Tsl + 2Tw

  29. Radio Range Measurements • Tdc = D/V • D is found to be about 400m with 8dBi omni-antenna for various speeds • At 80kmph, Tdc = 36s • Use of 802.11 extends range to 800m • Frontier Nodes

  30. Time Synchronization • Tw is function of Tdet & Tcd & Tpc • Tsl = Tdc - 2* Tw • Tpc : We use same protocol for synchronization as well as command issue • Flooding with multiple retransmissions (3) • Tpc turns out to be about 72ms • Error in synchronization is 0.18ms

  31. Time Synchronization • Calculating Tcd • Worst case clock drift in 36 sec is 20ppm • Synchronization error is 0.31ms • Tcd = 36s * 20 * 10^-6 (0.72) + 0.18 = 0.9ms • Tcd << Tpc ; Tdet ~ 50ms; • Tw ~ 125ms;Tsl ~ 36–0.25 = 35.75; • Duty Cycling ~ 0.3%

  32. Data Transfer • Long distance wireless links infeasible • 2km bridge with 200 sensors generate 1.5MB data • Transfer to single hop over 10-20 hops presents scalability problems • Data transfer time for 14 node network is 5 min • Reference: “A Wireless Sensor Network for Structural Health Monitoring: Performance and Experience”, EmNetS-II, May 2005

  33. Data Transfer: Our Approach • Use multiple channels; one for each data span • Data across spans independent • At most 12 nodes per span; very scalable • Adjacent channels are 7 spans apart with 16 available channels • Transfer data of the span motes to the head mote • Transfer data from head mote to train

  34. 3 4 5 1 2 6 Data Transfer C3 C5 C7 C9 Head Mote

  35. Data Transfer within Span:Routing Issues • Links are very stable in our setting • Reference: “Implications of Link Range and (In)Stability on Sensor Network Architecture”, WINTECH 2006 • Any simple protocol can be used • Centralized 2 Phase routing • Average duration of routing for 6 nodes : 567ms

  36. Routing Protocol: An Example 4 4 4 4 4 4 1 1 1 1 1 1 2 2 2 2 2 2 3 3 3 3 3 3 5 5 5 5 5 5 6 6 6 6 6 6 (d) Node 6 is a good neighbour to node3, node 5 has no good neighbour (c) Nodes 2,3 & 4 are good neighbours to node 1 (f) Dispatch Tree information (e) Node 5 is a bad neighbour to node 3 (b) Neighbourhood Discovery (a) Cluster of six nodes

  37. FLASH FLASH Data Transfer within Span: Transport Protocol • Transport protocol • Transfers data from the motes to the head mote • NACK based block transfer CMD Data TFR CMD Data TFR CMD Data TFR CMD Data ACK CMD Data ACK CMD Data ACK HEAD Mote NODE-2 NODE-3 NODE-4 Block Data TFR Block Data TFR Block Data TFR Block Data ACK Block Data ACK Block Data ACK

  38. Single Hop Data Transfer

  39. Mobile Data Transfer • Achievable data transfer rate using block transfer transport protocol on hardware is 46kbps (tested on field) • Max data per data span is 693Kbits (12 nodes) • Contact duration required is 15sec • Contact Range required = contact duration * speed of train Contact Range = D Head node

  40. Throughput Considerations • Contact range required for data transfer is • 330m at train speed of 80kmph • 250m at train speed of 60kmph • Our measurements give a contact range of 400m (one-side) • Transfer is possible with enough leeway. • Throughput can be further increased via • Compression • Multiple receivers at head and rear of train • Better Hardware • Simultaneous operation of flash and radio • Bluetooth Radio (1Mbps)

  41. Lifetime Estimate • Can achieve 1.5 year of operation using a 2500mAH battery 36s 15s 131s 33s

  42. Measurements on a Bridge Omni antenna

  43. Measurements on a Bridge Sink Mote

  44. Data Analysis Tool

  45. Conclusions • Application specific design • Extensive measurement study • Novelty of our contributions • Event detection mechanism • Mobile data transfer • Integration with time-synchronization/routing • Estimates indicate network can operate without intervention for 1 1/2 years

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