Poster
1
Indirect Wireless/Powerles Infrastructures Health Monitoring 1 Ahmed El-Hattab, 2 Nasim Uddin, 3 Euge Obrien, 4 Yang Wang 1 Ph.D. Candidate, 2,3 Professor 1&2 Department of Civil, Construction and Environmental Engineering University of Alabama at Birmingham (UAB) 3 University College Dublin ,Irland 4 Georgia Institute of Technology Introduction • The United States infrastructures have an average age varies from 40 to 100 years regarding the type of the infrastructure [1]. • The latest grading shows that the infrastructure status lies between Mediocre to Poor condition [1]. • The estimated spent budget for enhancing the infrastructure performance by 2013 was about 3.6 trillion dollars. • With this vast amount of spending, the infrastructures show to be non resilient to natural hazards [2]. • The transportation infrastructure represent more than 61.24% of the total infrastructure inventory in the US. • This research will introduce a Wireless/Powerless monitoring network to asses the structural health condition of the bridges on the transportation network Problem Statement • Most of current monitoring technique are based upon direct instrumentation on the bridge structure which limits the number of inspected bridges. • The instrumentation requires a continuous source of energy which is on of the major bottleneck in the SHM technologies • The cabled instrumentation as micron optics are efficient, however, the instrumentation and maintenance if the system represents one of the major issues with this technology , therefore, it is essential to switch to a monitoring network easier in the instrumentation and in the maintenance. Objective • Investigate a new inspection approach using an indirect measurements from an inspection vehicle to identify the deterioration in the bridge structures. • Validate the approach theoretically and through a full scale field test. • Investigate the efficiency of a new Wireless monitoring network (Martlet). • The Martlet The Martlet platform is a multi-functioning wireless sensing network, which was co-developed by the Research Team[1] with motherboard able to simultaneously sample analog signals from multiple sensors through different accessory sensor boards. Methodology/Results Drive-By bridge Inspection Theoretical Investigation • The concept is based on tracking the change of the induced displacement due to structural degradation of the bridge. • This will be achieved by subtracting the healthy bridge displacement from the damaged one • The bridge displacement is calculated using the instrumentation from the inspection vehicle as follows Full scale filed test verification • Here in the approach will be investigated using a full scale Filed test. • The full scale filed test uses the Wireless Martlet monitoring network • The network allows to collect a synchronized information fro the bridge and the vehicle simultaneously. • The Bridge Instrumentation is illustrated in the following figures • The vehicle is instrumented with the same platform, the following figure illustrates the instrumentation of the vehicle and the vehicle properties • The vehicle measurements are used to extract the dynamic properties of the inspection truck. Then an equivalent theoretical model is used to estimate the change in the bridge displacement • Powerless Radio Frequency Identifier (RFID) • This technology is based on using a fully passive/power free antenna sensor to detect the crack propagation as illustrated in the following figures Conclusion • The Indirect instrumentation for an inspection truck shows a processing results in predicting the structural degradation. • The Martlet Wireless Platform shows to an efficient alternative network for conventional monitoring networks • For an artificial damage, the adopted approach is working, however a further investigation is needed to validate is for more representative damage scenarios • The RFID antenna sensors shows a processing results in tracking the deterioration in structures, specifically steel structures through monitoring fatigue crack growth Acknowledgements This research is partially sponsored by the National Center for Transportation Systems Productivity and Management (NCTSPM) through US DOT (#DTRT12GUTC12), and Georgia DOT (#RP14-30). Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect the view of the sponsors. In addition to the support provided by the National Since of Foundation (NSF) Award-CMMI-1100742 for developing a : Next Generation Bridge Weigh in Motion System (BWIM) for Infrastructure Safety. References 1. Engineers ASoC Report card for America's infrastructure. In, 2005. American Society of Civil Engineers, 2. NIST (2008) Strategic Plan for the National Earthquake Hazards Reduction Program: Fiscal Years 2009–2013. Gaithersburg, Md.: NIST. IONAL CENTER FOR TRANSPORTATION SYSTEM PRODUCTIVITY AND MANAGEMENT Martlet mother-board (6x6 cm 2 , 20g) Integrated accelerometer board Strain gage board Sensor board with a displacement sensor Theoretical Vehicle Bridge Interaction Model Accelerat ion histories Modified Vehicle model Change in bridge displacement due to induced damage Station ary Server Integrated acceleromet er board Strain gage board Sensor board with a displacement sensor 21.34 m Emitters 35' 35' Truckdriving through 1 2 3 4 5 Receivers 1 2 3 4 5 4@ 8'9" laser emitter laser receiver installed on the bridge 10.67 m 10.67 m 4 girders @ 2.67 m 10.67 m Body Accelerome ter Silicon Designs 2012-002 accelerome ter Wireles s Antenna Gyroscopic Accelerometer Scenario # 1 Inspection truck Only Scenario # 2 Inspection truck With Pass. Veh. Scenario # 3 Inspection truck With Fully loaded truck m s kR I s D1 D2 u F u R u s .. kF m F m R .. F ront Axle Rear Axle Axle #1 & #2 Axle #3 P 1 P 2 P 2 ' P 1 ' W ireless Reader Antenna Sensor Interrogation R esponse Electrom agnetic frequency ( f ) R esponse Pow er Original Deformed R esonance frequency shift Pow erlevel change m b cb kb m s ks u b u s .. .. Bridge m b cb kb m s ks u b u s .. .. m c f r Accelerom eter#3 W eight=67.39 kN W eight=48.05 kN W eight=46.71 kN 4.67 m 1.40 m 3.30 m Accelerom eter#2 A ccelorom eter#1 Accelerom eter#4 & gyroscopic accelerometer A xle #3 A xle #2 A xle #1 m s kR I s D1 D2 u F u R u s .. kF m F m R .. F ront Axle Rear Axle Axle #1 & #2 Axle #3
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Transcript of Poster
Indirect Wireless/Powerles Infrastructures Health Monitoring 1Ahmed El-Hattab, 2Nasim Uddin, 3Euge Obrien, 4Yang Wang
1Ph.D. Candidate, 2,3Professor1&2 Department of Civil, Construction and Environmental Engineering
University of Alabama at Birmingham (UAB)3 University College Dublin ,Irland4 Georgia Institute of Technology
Introduction• The United States infrastructures have an average
age varies from 40 to 100 years regarding the type of the infrastructure [1].
• The latest grading shows that the infrastructure status lies between Mediocre to Poor condition [1].
• The estimated spent budget for enhancing the infrastructure performance by 2013 was about 3.6 trillion dollars.
• With this vast amount of spending, the infrastructures show to be non resilient to natural hazards [2].
• The transportation infrastructure represent more than 61.24% of the total infrastructure inventory in the US.
• This research will introduce a Wireless/Powerless monitoring network to asses the structural health condition of the bridges on the transportation network
Problem Statement• Most of current monitoring technique are based
upon direct instrumentation on the bridge structure which limits the number of inspected bridges.
• The instrumentation requires a continuous source of energy which is on of the major bottleneck in the SHM technologies
• The cabled instrumentation as micron optics are efficient, however, the instrumentation and maintenance if the system represents one of the major issues with this technology , therefore, it is essential to switch to a monitoring network easier in the instrumentation and in the maintenance.
Objective• Investigate a new inspection approach using an indirect
measurements from an inspection vehicle to identify the deterioration in the bridge structures.
• Validate the approach theoretically and through a full scale field test.
• Investigate the efficiency of a new Wireless monitoring network (Martlet).
• The Martlet The Martlet platform is a multi-functioning wireless sensing network, which was co-developed by the Research Team[1] with motherboard able to simultaneously sample analog signals from multiple sensors through different accessory sensor boards.
• Investigate the feasibility of using a Passive (Power Free) monitoring technology
Methodology/ResultsDrive-By bridge Inspection
Theoretical Investigation • The concept is based on tracking the change of the induced displacement due to structural degradation of the bridge. • This will be achieved by subtracting the healthy bridge displacement from the damaged one • The bridge displacement is calculated using the instrumentation from the inspection vehicle as follows
Full scale filed test verification • Here in the approach will be investigated using a full scale Filed test.• The full scale filed test uses the Wireless Martlet monitoring network • The network allows to collect a synchronized information fro the bridge and the vehicle simultaneously. • The Bridge Instrumentation is illustrated in the following figures
• The vehicle is instrumented with the same platform, the following figure illustrates the instrumentation of the vehicle and the vehicle properties
• The vehicle measurements are used to extract the dynamic properties of the inspection truck. Then an equivalent theoretical model is used to estimate the change in the bridge displacement
•
Powerless Radio Frequency Identifier (RFID)• This technology is based on using a fully passive/power free antenna sensor to detect the crack propagation as illustrated in
the following figures
Conclusion• The Indirect instrumentation for an inspection truck
shows a processing results in predicting the structural degradation.
• The Martlet Wireless Platform shows to an efficient alternative network for conventional monitoring networks
• For an artificial damage, the adopted approach is working, however a further investigation is needed to validate is for more representative damage scenarios
• The RFID antenna sensors shows a processing results in tracking the deterioration in structures, specifically steel structures through monitoring fatigue crack growth
AcknowledgementsThis research is partially sponsored by the National Center for Transportation Systems Productivity and Management (NCTSPM) through US DOT (#DTRT12GUTC12), and Georgia DOT (#RP14-30). Any opinions, findings, and conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect the view of the sponsors.
In addition to the support provided by the National Since of Foundation (NSF) Award-CMMI-1100742 for developing a : Next Generation Bridge Weigh in Motion System (BWIM) for Infrastructure Safety.
References
1. Engineers ASoC Report card for America's infrastructure. In, 2005. American Society of Civil Engineers,
2. NIST (2008) Strategic Plan for the National Earthquake Hazards Reduction Program: Fiscal Years 2009–2013. Gaithersburg, Md.: NIST.
NATIONAL CENTER FOR TRANSPORTATION SYSTEM PRODUCTIVITY AND MANAGEMENT
ms
kR
I s
D1D2
uFuR
us..
kF
mFmR
..
Front AxleRear AxleAxle #1 & #2 Axle #3
Martlet mother-board (6x6 cm2, 20g)
Integrated accelerometer board
Strain gage board Sensor board with a displacement sensor
P1 P2
P2'P1'
Wireless Reader Antenna Sensor
Interrogation
ResponseElectromagnetic frequency ( f )
Response Power
OriginalDeformed
Resonance frequency shift
Power level change
mb
cbkb
ms
ks
ub
us
..
..
Bridge
Theoretical Vehicle Bridge Interaction Model
Acceleration histories
mb
cbkb
msks
ub
us
..
..
mcf r
Modified Vehicle model
Change in bridge displacement due to induced damage
Stationary Server
Integrated accelerometer board
Strain gage board
Sensor board with a displacement sensor
21.34 m
Emitters
35' 35'
Truck driving through
1 2 3 4 5
Receivers 1 2 3 4 5
4@8'9"
laser emitter
laser receiver installed on the bridge
10.67 m 10.67 m
4 gi
rder
s @ 2
.67
m10
.67
m
Body Accelerometer
Silicon Designs 2012-002 accelerometer
Wireless Antenna
Gyroscopic Accelerometer
Accelerometer #3
Weight=67.39 kNWeight=48.05 kNWeight=46.71 kN4.67 m1.40 m
3.30 m
Accelerometer #2Accelorometer #1
Accelerometer #4& gyroscopicaccelerometer
Axle #3Axle #2Axle #1
ms
kR
I s
D1D2
uFuR
us..
kF
mFmR
..
Front AxleRear AxleAxle #1 & #2 Axle #3 Scenario # 1
Inspection truckOnly
Scenario # 2 Inspection truckWith Pass. Veh.
Scenario # 3 Inspection truckWith Fully loaded truck
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