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Embedded Networks Laboratory
Embedded Sensing of Structures : A Reality Check
Krishna Kant Chintalapudi, Jeongyeup Paek, Nupur Kothari, Sumit Rangwala, Ramesh Govindan, Erik Johnson
Jeongyeup Paek
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Embedded Networks Laboratory
Goals of the Talk
• Original vision
• Where are we today?
• Where are we heading?– Is the original vision still meaningful?
“ Millions of tiny sensors embedded in concrete
detect damages in buildings and bridges ”
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Embedded Networks Laboratory
Agenda• Introduction to Structural Health Monitoring
• Requirements of SHM Applications
• WISDEN - a wireless sensor network data acquisition system
• NetSHM – a programmable sensor network for SHM applications
• Speculations about the future
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Embedded Networks Laboratory
What Is Structural Health Monitoring (SHM)?
• Structural integrity assessment for buildings, bridges, offshore oil rigs, aerospace structures etc.
• Goals of SHM:
– Detection “is there damage?”
– Localization “where is the damage?”
– Quantification “how severe?”
– Prognosis “future prediction”
• Why SHM?
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Embedded Networks Laboratory
SHM Basics
• Measure and analyze structural vibrations induced due to heavy winds or earthquakes, etc
• Principles behind structural algorithms can be illustrated by strings
– Structural response is composed of several harmonics - modes
– Mode = < Frequency, Mode Shape>
• Damages alter the structural properties and hence the modes
• Structural response is measured by using sensors (accelerometers, strain gauges) at several locations in the structure
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Embedded Networks Laboratory
Sensor Networks for SHM
• Current SHM– Bi-annual visual inspections (most common)
• Limitations of human accessibility and error• Catastrophic failure between inspections
– Expensive wired data acquisition systems• Extremely high installation, cabling, and maintenance cost
• Wireless Sensor Network based SHM system– Flexible, fast and low cost deployments
– No cabling cost!!
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Embedded Networks Laboratory
Agenda• Introduction to Structural Health Monitoring
• Requirements of SHM Applications
• WISDEN - a wireless sensor network data acquisition system
• NetSHM – a programmable sensor network for SHM applications
• Speculations about the future
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Embedded Networks Laboratory
Existing SHM Techniques
Damage Detection Damage Localization
Time
SeriesModal
FrequencyMode Shape
Neural Networks
Time Domain
Frequency Domain
Changes in ARMA coefficients
Changes in modal frequencies
Changes in mode shape
Train neural networks with data
Reconstruct a structural model from data
Reconstruct structural model using mode shapes
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Embedded Networks Laboratory
Basic Requirements for SHM Applications
• Reliable Delivery– SHM applications are loss-intolerant, sensors need to transmit data
reliably
• Time Synchronization– Data from various sensors should be time-synchronized to within 100
micro-sec for damage localization.
• High Data Rates– A hundred tri-axial sensors sampling at 500Hz can generate a data rate
of 5Mbps.
• Dense Sensing– The larger the number of sensors the better the performance
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Embedded Networks Laboratory
Importance of In-Network Processing
• Sensor networks are expected to last for several months or even a year without human intervention
• With high data rate radio communication and sensing, nodes will typically not last more than few days.
• In-network processing can lead to long lived SHM systems by reducing communication overhead
• Most SHM techniques can leverage local computation at node to minimize radio communication– ARMA coefficient for time series based damage detection
– FFT for modal frequency shift based damage detection
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Embedded Networks Laboratory
Agenda• Introduction to Structural Health Monitoring
• Requirements of SHM Applications
• WISDEN - a wireless sensor network data acquisition system
• NetSHM – a programmable sensor network for SHM applications
• Speculations about the future
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Embedded Networks Laboratory
Wisden
• First step– Replace the existing wired data acquisition system
• Wisden– Wireless sensor network based data acquisition system
– Allows continuous sampling and reliable logging of time-synchronized structural response data
• Advantages– Flexibility
• Nodes self-organize into a multi-hop network.• Nodes can be inserted in and out of the network dynamically
– Low time and cost of installation
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Embedded Networks Laboratory
Wisden overview• Three components of Wisden
– Reliability• Over multiple hops with end-to-end and hop-by-hop recovery
– Time-synchronization• Novel low-overhead residence time based approach
– Data compression• Necessary at the source nodes to relieve bandwidth bottleneck and reduce
communication overhead.• Onset detection – transmit only relevant data
“A Wireless Sensor Network for Structural Monitoring”, Ning Xu, Sumit Rangwala, Krishna Chintalapudi, Deepak Ganesan, Alan Broad, Ramesh Govindan, Deborah Estrin, In Proceedings of the ACM Conference on Embedded Networked Sensor Systems, Nov.2004
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Embedded Networks Laboratory
Onset Detection
• Why transmit data when nothing is happening?• Detect onset of events at the sensor and transmit only when
something is happening
“A Wireless Sensor Network for Structural Health Monitoring: Performance and Experience”, Jeongyeup Paek, Krishna Chintalapudi, John Caffrey, Ramesh Govindan, Sami Masri, In Proceedings of the IEEE Workshop on Embedded Networked Sensors, May.2005
Data not transmitted during quiescent period
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Embedded Networks Laboratory
Deployment Experiences (1)
• Seismic Structure
– Structural vibrations are highly damped, last less than a second• Higher sampling rates are needed to collect enough samples for analysis
(>200Hz)
– Platform limitations (such as EEPROM access latencies) proved to be the obstacles for high sampling rates
– After the development of onset-detection and careful re-engineering, Wisden was able to achieve 200Hz
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Embedded Networks Laboratory
Deployment Experiences (2)
• Four Seasons Building
– Communication environment was very lossy • Avg. delivery rate 81% and worst case of 30%• The path lengths were often 2-3 hops and sometimes even higher• Frequent route changes occurred due to the variability of the wireless links
– Rate control and hop-by-hop retransmissions were required
– Does not scale • As number of nodes grows, the bandwidth bottleneck becomes significant• Leads to our next step hierarchical system: NetSHM
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Embedded Networks Laboratory
Agenda• Introduction to Structural Health Monitoring
• Requirements of SHM Applications
• WISDEN - a wireless sensor network data acquisition system
• NetSHM – a programmable sensor network for SHM applications
• Speculations about the future
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Embedded Networks Laboratory
NetSHM
• NetSHM is the next step to WISDEN.
• A sensor network system that Structural engineers can program in higher level language such as Matlab/C
• An SHM engineer should be able to write and test variety of algorithms without having to understand the underlying sensor network details
• The system should be evolvable – we should not need to rewrite applications when the technology evolves
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Embedded Networks Laboratory
Architecture of NetSHM
• Two-level Hierarchy– For scalability, a higher more
endowed layer is required to manage the aggregate data rates generated by the motes.
• Isolate application code from wireless sensor network details– Wireless sensor network provides
a generic task interface• getSamples(startTime, noSamples,
sampFreq, axis)• getFFTSamples(startTime,noSamp
les,sampFreq,axis,fftSize)
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Embedded Networks Laboratory
What does code isolation buy us?
• Reusability – Application programmers can use the generic task interface and
write many different SHM applications. – Basic SHM library functions can be provided on motes: FFT,
auto-correlation, ARMA coefficient estimation, spectral estimation etc.
• Evolvability– If a new mote comes along with greater processing power, just
add new functionality, no need to rewrite application.
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Embedded Networks Laboratory
Application on NetSHM
function shifts = getModalShiftsFromBuilding()
% create a group for sensorsgidSensors = NetSHMCreateGroup([1,2,3,4]);
%create a group for actuatorsgidActuators = NetSHMCreateGroup([5]);
%actuate after 22 secondsNetSHMCmdActuate(gidActuators,22);
%collect structural response starting 20 seconds from now,% 4000 samples at 200Hz,along x-axis only,samples = NetSHMCmdGetSamples(gidSensors,20,200,1,4);
%find modal frequenciesmodes = findModes(samples);
%read original modesload OriginalModes;shifts = findModalFreqShifts(modes,OriginalModes);
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Embedded Networks Laboratory
The Stacks
SHM Application(in C or Matlab)
API in C API in Matlab
Tasking Library
Reliable CommunicationTime Sync.
Routing
Tasking
Reliable Communication Time
SyncRouting
Driver for Sensing / Actuation
Gateway node stack Mote-class node stack
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Embedded Networks Laboratory
Deployment• Building Details
– 48 inches high, 4 floors, 60 lbs– Floors –1/2 x 12 x 18 aluminum
plates– steel 1/2 x 1/8 inch steel
columns– 5.5 lb/inch spring braces– 4 actuators on the top floor– 8 motes, 2/floor– dual axis, 200Hz, 2 starGates
• 4 Test Cases– braces from floor 4 removed – braces from floor 3 removed– braces from floor 2 removed– braces from floor 2 and 4
removed
ActuatorsSensors
Motes
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Embedded Networks Laboratory
Agenda• Introduction to Structural Health Monitoring
• Requirements of SHM Applications
• WISDEN - a wireless sensor network data acquisition system
• NetSHM – a programmable sensor network for SHM applications
• Speculations about the future
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Embedded Networks Laboratory
Limitations of Wireless Sensor Network based SHM today
• Hundreds of nodes per structure
• Limited lifetime – Couple of days with continuous sampling– Up to couple of months with scheduled monitoring
• Limited in-network processing– Platform limitations (eg. mica2, micaz)
• Memory (FFT, ARMA, etc)
• Processing (floating point, etc)
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Embedded Networks Laboratory
What next?
• Vision of millions of embedded sensors in concrete seems a bit too farfetched– Energy, form factor, communication, etc
• Within the next few years, NetSHM like systems will encourage SHM engineers to migrate to sensor network systems
• Most of the data processing will migrate into the sensors within the next five years with the advent of improved sensor platforms
• We believe that the wired sensing will be almost entirely replaced by wireless networks within the next ten years
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