A Wireless Sensor Network For Structural Monitoring Wisden

1
A Wireless Sensor Network For Structural
Monitoring(Wisden)
Sumit Rangwala

• Collaborators Ning Xu, Krishna Kant
  Chintalapudi, Deepak Ganesan, Alan Broad, Ramesh
  Govindan, Deborah Estrin, Jeongyeup Paek, Nupur
  Kothari

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Background

• Structural health monitoring (SHM)
• Detection and localization of damages in
  structures
• Structural response
• Ambient vibration (earthquake, wind etc)
• Forced vibration (large shaker)
• Current SHM systems
• Sensors (accelerometers) placed at different
  structure location
• Connected to the centralized location
• Wires (cables)
• Single hop wireless links
• Wired or single hop wireless data acquisition
  system

3
Motivation

• Are wireless sensor networks an alternative?
• Why WSN?
• Scalable
• Finer spatial sampling
• Rapid deployment
• Wisden
• Wireless multi-hop data acquisition system

4
Challenges

• Reliable data delivery
• SHM intolerant to data losses
• High aggregate data rate
• Each node sampling at 100 Hz or above
• About 48Kb/sec (10 node,16-bit sample, 100Hz, 3
  axes)
• Data synchronization
• Synchronizing samples from different sources at
  the base station
• Resource constraints
• Limited bandwidth and memory
• Energy efficiency
• Future work

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Wisden Architecture
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Reliable Data Transport

• Routing
• Nodes self-organize in a routing tree rooted at
  the base station
• Used Woo et al.s work on routing tree
  construction
• Reliability
• Hop-by-hop recovery
• How ?
• NACK based
• Piggybacking and overhearing
• Why hop by hop?
• High packet loss

Retransmission
NACK
Retransmission
Retransmission
NACK
NACK
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Reliable Data Transport (cont.)

• End to End packet recovery
• How ?
• Initiated by the base station (PC)
• Same mechanism as hop-by-hop NACK
• Why ?
• Topology changes leads to loss of missing packet
  information
• Missing packet information may exceed the
  available memory
• Data Transmission rate
• Rate at which a node inject data
• Currently pre-configured for each node at R/N
• R nominal radio bandwidth
• N total number of nodes
• Adaptive rate allocation part of future work.

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Compression

• Sampled data significant fraction of radio
  bandwidth
• Event based compression
• Detect Event
• Based on maximum difference in sample value over
  a variable window size
• Quiescent period
• Run length encoding
• Non-quiescent period
• No compression
• Saving proportional to duty-cycle of vibration
• Drawback
• High latency

Compression
No Compression
Compression
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Compression For Low Latency

• Progressive storage and transmission
• Event detection
• Wavelet decomposition and local storage
• Compression
• Low resolution components are transmitted
• Raw data, if required available from local
  storage
• Current Status
• Evaluated on standalone implementation
• To be integrated into Wisden

Flash Storage
Wavelet Decomposition
To sink on demand
Quantization, Thresholding, Run length coding
Reliable Data Transport
Sink
Low resolution components
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Data Synchronization

• Synchronize data samples at the base station
• Generation time of each sample in terms of base
  station clock
• Network wide clock synchronization not necessary
• Light-weight approach
• As each packet travels through the network
• Time spent at each node calculated using local
  clock and added to the field residence time
• Base station subtracts residence time from
  current time to get sample generation time.
• Time spent in the network defines the level of
  accuracy

TAT-(qA qB)
TCT-(qC qD)
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Implementation

• Hardware
• Mica2 motes
• Vibration card (MDA400CA from Crossbow)
• High frequency sampling (up to 20KHz)
• 16 bit samples
• Programmable anti-aliasing filter
• Software
• TinyOS
• Additional software
• 64-bit clock component
• Modified vibration card firmware

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Deployment Scenario1

• Seismic test structure
• Full scale model of an actual hospital ceiling
  structure
• Four Seasons building
• Damaged four-storey office building subjected to
  forced-vibration

1Not presented in the paper
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Seismic Test Structure Setup

• Setup
• 10 node deployment
• Sampling at 50 Hz along three axes
• Transmission rate at 0.5 packets/sec
• Impulse excitation using hydraulic actuators
• For validation
• A node sending data to PC over serial port (Wired
  node)
• A co-located node sending data to the PC over the
  wireless multihop network (Wisden node)

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Results Frequency Response
Power spectral density Wisden node
Power spectral density Wired node

• Low frequency modes captured
• High frequency modes lost
• Artifact of compression scheme we used

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Results Packet Reception and Latency

• Packet reception
• 99.87 (cumulative over all nodes)
• 100 , if we had waited longer
• Latency
• 7 minutes to collect data for 1 minute of
  vibration

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Four Seasons Building

• Setup
• 10 node deployment
• Sampling at 50 Hz along three axes
• Transmission rate at 0.5 packets/sec
• Excitation using eccentric mass shakers
• For validation
• Wisden nodes places alongside floor mounted
  force-balance accelerometer (Wired node)

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Results Frequency Response
Power spectral density Wisden Node
Power spectral density Wired Node

• Dominant frequency captured
• Noise
• Sampling differences, force balanced
  accelerometer much more sophisticated, packet
  losses

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Results Packet Reception

• Packet reception
• High data loss
• Due to a bug

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Conclusions and Future Work

• Wisden A wireless data acquisition system that
  provides
• Reliable data collection
• Supports high sampling rate
• Data synchronization
• Future work
• Adaptive rate allocation scheme
• Integrating wavelet based compression
• Power efficiency
• Wisden version 0.1 available at
• http//enl.usc.edu/
• Thank you