A Wireless Sensor Network For Structural Monitoring (Wisden)
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Transcript of A Wireless Sensor Network For Structural Monitoring (Wisden)
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UNIVERSITY OFSOUTHERN CALIFORNIA
Embedded Networks Laboratory
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A Wireless Sensor Network For Structural Monitoring
(Wisden)
Collaborators: Ning Xu, Krishna Kant Chintalapudi, Deepak Ganesan, Alan Broad, Ramesh Govindan, Deborah Estrin,
Jeongyeup Paek, Nupur Kothari
Sumit Rangwala
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UNIVERSITY OFSOUTHERN CALIFORNIA
Embedded Networks Laboratory
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BackgroundBackground• 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
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MotivationMotivation• Are wireless sensor
networks an alternative?
• Why WSN?– Scalable
» Finer spatial sampling
– Rapid deployment
• Wisden– Wireless multi-hop data
acquisition system
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ChallengesChallenges• 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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Embedded Networks Laboratory
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Wisden ArchitectureWisden Architecture
Challenges Architectural Component
Description
Reliable data delivery
Reliable Data Transport
Hybrid hop-by-hop and end-to-end error recovery
High data rate Compression Silence suppression
Wavelet based compression
Data Synchronization
Data Synchronization
Residence time calculation in the network
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Embedded Networks Laboratory
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Reliable Data TransportReliable 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
NACK
Retransmission
NACK
Retransmission
NACK
Retransmission
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Reliable Data Transport (cont.)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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CompressionCompression• 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
Quiescent Period
Event Quiescent Period
Compression No Compression
Compression
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Compression For Low LatencyCompression 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
Wavelet Decomposition
Quantization, Thresholding, Run length coding
Sink
Flash Storage
To sink on demand
Reliable Data Transport
Event
Low resolution components
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Embedded Networks Laboratory
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Data SynchronizationData 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
S
q AAq
A
q A +
q B
Bq
B
TA=T-(qA + qB) TC=T-(qC + qD)
qC C
qC
qC + q
D DqD
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Embedded Networks Laboratory
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ImplementationImplementation• 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 ScenarioDeployment Scenario11
• 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 SetupSeismic 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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Embedded Networks Laboratory
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Results: Frequency ResponseResults: Frequency Response
• Low frequency modes captured• High frequency modes lost
– Artifact of compression scheme we used
Power spectral density: Wisden node Power spectral density: Wired node
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Results: Packet Reception and LatencyResults: 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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Embedded Networks Laboratory
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Four Seasons BuildingFour 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 ResponseResults: Frequency Response
• Dominant frequency captured• Noise
– Sampling differences, force balanced accelerometer much more sophisticated, packet losses
Power spectral density: Wisden Node Power spectral density: Wired Node
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Embedded Networks Laboratory
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Results: Packet ReceptionResults: Packet Reception• Packet reception
– High data loss» Due to a bug
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Embedded Networks Laboratory
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Conclusions and Future WorkConclusions 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