Presenter : Steve

BRIMON: Wireless Sensor Network based Railway

Bridge Monitoring

Kameswari Chebrolu , Bhaskaran Raman, Nilesh Mishra, Phani Kumar Valiveti, Raj Kumar

Presenter : Steve

Outline

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

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

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

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

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

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

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

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

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

Architecture Overview

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Piers

Event Signaling module (Channel 1)

Clusters

Data Transport modules

Data span as an independent network Each cluster operates on a different channel

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Topology Formation

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Time Synchronization

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Sleep-Wakeup

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Train Arrival DetectionCommand Control: Wakeup

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Vibration Sensing

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Data Gathering by individual cluster heads

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Train Detection Data Uploading

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Sleep-Wakeup

Send Data to Repository

BriMon Architecture: Event Detection

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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 propagation

Event Detection

• Tw = 2*Tcd + Tpc (at non-head mote)

• Ans: Tdc = Tcc + Tw = Tsl + 2Tw

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


• 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


• 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%

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

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

Data Transfer

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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– 1.Neighbor-discovery Phase– 2.Tree construction phase

– Average duration of routing for 6 nodes : 567ms

Routing Protocol: An Example

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(b) Neighbourhood Discovery

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(c) Nodes 2,3 & 4 are good neighbours to node 1

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(d) Node 6 is a good neighbour to node3, node 5 has no good neighbour

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(e) Node 5 is a bad neighbour to node 3

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(f) Dispatch Tree information

Data Transfer within Span: Transport Protocol

• Transport protocol– Transfers data from the motes to the head mote– NACK based block transfer

HEAD Mote NODE-2

FLASH

NODE-3 NODE-4

FLASHCMD Data TFR

CMD Data ACK

CMD Data TFR

CMD Data ACK

CMD Data TFR

CMD Data ACK

Block Data TFR

Block Data ACK

Block Data TFR

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Single Hop Data Transfer

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

Head node

Contact Range = D

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)

Lifetime Estimate• Can achieve 1.5 year of operation using a

2500mAH battery

131s 33s 15s

36s

Measurements on a Bridge

Omni antenna

Measurements on a BridgeSink Mote

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

Documents

Presenter : Steve