Strain-based Fatigue Crack Monitoring of Steel Bridges using Wireless Elastomeric Skin Sensors

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General Information
Study Number: TPF-5(328)
Lead Organization: Kansas Department of Transportation
Contract Start Date: Sep 01, 2015
Solicitation Number: 1372
Partners: KS, MN, NC, OK, PADOT, TX
Status: Closed
Est. Completion Date: Aug 31, 2019
Contract/Other Number:
Last Updated: Oct 31, 2019
Contract End Date: Aug 31, 2018
Financial Summary
Contract Amount:
Total Commitments Received: $490,000.00
100% SP&R Approval: Approved
Contact Information
Lead Study Contact(s): David Behzadpour
David.Behzadpour@ks.gov
Phone: 785-291-3847
FHWA Technical Liaison(s): Justin Ocel
justin.ocel@dot.gov
Phone: 202-493-3080
Organization Year Commitments Technical Contact Name Funding Contact Name Contact Number Email Address
Kansas Department of Transportation 2014 $40,000.00 Mark Hurt David Behzadpour 785-291-3847 David.Behzadpour@ks.gov
Kansas Department of Transportation 2015 $40,000.00 Mark Hurt David Behzadpour 785-291-3847 David.Behzadpour@ks.gov
Kansas Department of Transportation 2016 $10,000.00 Mark Hurt David Behzadpour 785-291-3847 David.Behzadpour@ks.gov
Minnesota Department of Transportation 2015 $25,000.00 Nancy Daubenberger Lisa Jansen 651-366-3779 lisa.jansen@state.mn.us
Minnesota Department of Transportation 2016 $25,000.00 Nancy Daubenberger Lisa Jansen 651-366-3779 lisa.jansen@state.mn.us
Minnesota Department of Transportation 2017 $25,000.00 Nancy Daubenberger Lisa Jansen 651-366-3779 lisa.jansen@state.mn.us
North Carolina Department of Transportation 2015 $25,000.00 Brian Hanks Neil Mastin 919 707 6661 jmastin@ncdot.gov
North Carolina Department of Transportation 2016 $25,000.00 Brian Hanks Neil Mastin 919 707 6661 jmastin@ncdot.gov
North Carolina Department of Transportation 2017 $25,000.00 Brian Hanks Neil Mastin 919 707 6661 jmastin@ncdot.gov
Oklahoma Transportation 2015 $25,000.00 Wes Kellog Ron Curb (405)420-9163 rcurb@odot.org
Oklahoma Transportation 2016 $25,000.00 Wes Kellog Ron Curb (405)420-9163 rcurb@odot.org
Oklahoma Transportation 2017 $25,000.00 Wes Kellog Ron Curb (405)420-9163 rcurb@odot.org
Pennsylvania Department of Transportation 2015 $10,000.00 Guozhou Li Heather Sorce 717-214-9508 hsorce@pa.gov
Pennsylvania Department of Transportation 2016 $25,000.00 Guozhou Li Heather Sorce 717-214-9508 hsorce@pa.gov
Pennsylvania Department of Transportation 2017 $25,000.00 Guozhou Li Heather Sorce 717-214-9508 hsorce@pa.gov
Pennsylvania Department of Transportation 2018 $25,000.00 Guozhou Li Heather Sorce 717-214-9508 hsorce@pa.gov
Texas Department of Transportation 2015 $30,000.00 Lianxiang Du Ned Mattila 512-416-4727 ned.mattila@txdot.gov
Texas Department of Transportation 2016 $30,000.00 Lianxiang Du Ned Mattila 512-416-4727 ned.mattila@txdot.gov
Texas Department of Transportation 2017 $30,000.00 Lianxiang Du Ned Mattila 512-416-4727 ned.mattila@txdot.gov

Study Description

Fatigue cracks have been a major issue for steel bridges in the nation. State DOTs currently rely on a two-year inspection period to examine steel bridges for detecting fatigue crack activities. However, human inspection is time consuming, labor intensive, cost inefficient, and prone to error. Although Nondestructive Evaluation (NDE) techniques can improve inspection accuracy, the lack of autonomy and continuity in the inspection process still limits its ability to capture critical crack development in a timely fashion. After all, these cracks may occur between scheduled inspection periods and therefore can lead to catastrophic failure of steel bridges.

Measuring strain-induced crack development is an effective way of monitoring fatigue cracks. However, due to the randomness of crack paths, traditional strains sensors, such as metal foil strain gauges, are small and can only be deployed in a small and localized region, limiting their capability of detecting these cracks. Moreover, the limited ductility of these foil gauges leads to breakage under excessive strain, typical during crack formation. Meanwhile, a traditional wired monitoring approach imposes high cost to the overall system due to bulky data acquisition units and expensive cabling work, especially for long-span bridges. The centralized management scheme limits its flexibility and continuous monitoring capability due to potential data inundation.

Objectives

The main objective of this proposed research is to provide state DOTs a practical and cost-effective long-term fatigue crack monitoring methodology using a wireless elastomeric skin sensor network. This research is intended to demonstrate the value-added of fatigue crack monitoring of steel bridges using wireless skin sensors over the traditional bridge inspection in the following ways:

(1) The ability to collect objective information regarding fatigue crack activity under in-service loading of bridges in a continuous manner, improving the assessment, safety, and reliability of fractural-critical bridges, and providing early warning regarding evolving internal defects.

(2) The ability to improve prioritization of bridge repairs (condition-based maintenance) and retrofit for fatigue cracks so as to maximize the effectiveness of limited resources.

(3) The ability to better assess the effectiveness of various fatigue repair and retrofit techniques for steel bridges through long-term crack monitoring.

Scope of Work

The proposed research consists of three phases of tasks from the development and validation of the basic crack sensor (Phase I), design, implementation, and small scale validation of the wireless data acquisition system and the autonomous sensor network operation strategies (Phase II), to the robustness, large scale, and long-term full scale validation tests of the integrated wireless crack sensor network system (Phase III).

Phase I tasks: Crack sensor

1. Crack sensor fabrication: Fatigue crack sensors will be developed by fabricating the skin sensors tailored to fatigue crack detection. The thickness of these sensors will be 40 µm to enhance the mechanical robustness under harsh environment.

2. Small scale validation: Tests will be designed and carried out to validate the crack detection capability of the crack sensor. The test setup will consist of a pre-notched steel member subjected to fatigue loading. The fatigue testing facility at the University of Kansas will also be used to perform tensile fatigue tests and bending fatigue tests. An off-the-shelf data acquisition system will be adopted to measure the capacitance change of the sensors under crack development. Metal foil gauges will be used to provide reference measurement for validation.

Phase II tasks: Wireless crack sensor network

3. Wireless data acquisition (DAQ) system: A wireless data acquisition system will be developed for measuring capacitance change of the elastomeric skin sensor. The Imote2 smart sensor platform is selected because of its fully tested software package, which serves as the foundation of this integrated wireless skin sensor network system. The Imote2 sensor can measure voltage inputs between -5 V and +5 V using a stackable data acquisition (DAQ) board. An interface board between the elastomeric skin sensor and the Imote2 DAQ board will be developed to convert capacitance change into voltage signals.

4. Data quality assessment: The quality of data collected by the integrated wireless sensing system will be evaluated. Focus will be placed on the noise level and resolution. The goal is to make sure the integrated system has adequate resolution and low noise level to capture the strain change associated with fatigue crack activity.

5. Crack detection algorithm: Algorithms will be developed to process the measured strain data to reveal the crack activities underneath the skin sensor. Various sensor patterns will be investigated based on typical scenarios of fatigue cracks. Data fusion strategies combining on-board and in-network data processing will be implemented and tested for detecting active fatigue cracks as well as the propagation direction of these active cracks. The goal is to be able to make decisions using the smart sensors by locally combining and processing data measured at different locations without transmitting raw data back to the base station.

6. Autonomous sensor network: Software will be designed to enable autonomous operation of the sensor network. Practical issues such as triggering of the sensor network, sleep-cycling to conserve energy, energy harvesting methods such as solar panels, and other energy efficient operation issues, etc. will be addressed in this task.

7. Small scale system validation: The integrated system will be validated using the small scale pre-notched steel beam from Task 2 of Phase I.

Phase III tasks: Large/full scale validation

8. Robustness test: The robustness of both hardware and software will be tested. Mechanical robustness against external impact on the elastomeric skin sensors, long term stability of the electrical signal generated by the crack sensor, and fault tolerance of the software for autonomous operation will be tested.

9. Large scale validation: A network of crack sensors will be deployed on the existing large scale steel girder test bridge at the University of Kansas, which is a 30-ft long, three-girder bridge that includes realistic fatigue sensitive details. The

Comments

This project is broken out into three Phases for a total cost of $495,000. Iowa DOT is funding Phase One and part of Phase Two for a cost of $92,150.

We are looking for 4-5 other states to committ $25,000-30,000 per year for three years to do all three phases.

We have requested 100% SPR Funding

Documents Attached
Title File/Link Type Privacy Download
Final report TPF-5(328) _FinalReport.pdf Final Report Public
TPF-5(328) Waiver Approval Waiver Approval - Solicitation#1372.pdf Memorandum Public
TPF-5(328) Closeout Letter TPF-5(328) Closeout Memo.pdf Memorandum Public
Acceptance Letter Acceptence Letter.pdf Other Public
TPF-5(328) Closeout Funding Spreadsheet TPF-5(328) Closeout Funding Spreadsheet.pdf Other Public
Dec 2015 Quarterly Report SPR_quarterly_report_TPF-5(328) 01-29-16.pdf Quarterly Progress Report Public
June 2016 Quarterly Report SPR_quarterly_report_TPF-5(328) 07-29-16.pdf Quarterly Progress Report Public
March 2016 Quarterly Report SPR_quarterly_report_TPF-5(328) 04-30-16.pdf Quarterly Progress Report Public
September 2015 Quarterly Report SPR_quarterly_report_TPF-5(328) 09-30-15.pdf Quarterly Progress Report Public
Quarterly Reports Sept 2016 SPR_quarterly_report_TPF-5(328) 10-28-16.pdf Quarterly Progress Report Public
Quarterly Report Dec 2016 SPR_quarterly_report_TPF-5(328) 01-31-2017.pdf Quarterly Progress Report Public
Quarterly Report March 2017 SPR_quarterly_report_TPF-5(328) 04-30-2017.pdf Quarterly Progress Report Public
Quarterly Report June 2017 SPR_quarterly_report_TPF-5(328) 07-31-2017.pdf Quarterly Progress Report Public
Quarterly Report Sept 2017 SPR_quarterly_report_TPF-5(328) 10-30-2017.pdf Quarterly Progress Report Public
Quarterly Report Dec 2017 SPR_quarterly_report_TPF-5(328) 1-31-2018 - revised.pdf Quarterly Progress Report Public
Quarterly Report March 2018 SPR_quarterly_report_TPF-5(328) 04-24-2018.pdf Quarterly Progress Report Public
Quarterly Report June 2018 SPR_quarterly_report_TPF-5(328) 07-13-2018.pdf Quarterly Progress Report Public
Quarterly Report Sept 2018 SPR_quarterly_report_TPF-5(328) 09-30-2018.pdf Quarterly Progress Report Public

Strain-based Fatigue Crack Monitoring of Steel Bridges using Wireless Elastomeric Skin Sensors

General Information
Study Number: TPF-5(328)
Lead Organization: Kansas Department of Transportation
Contract Start Date: Sep 01, 2015
Solicitation Number: 1372
Partners: KS, MN, NC, OK, PADOT, TX
Status: Closed
Est. Completion Date: Aug 31, 2019
Contract/Other Number:
Last Updated: Oct 31, 2019
Contract End Date: Aug 31, 2018
Financial Summary
Contract Amount:
Total Commitments Received: $490,000.00
100% SP&R Approval:
Contact Information
Lead Study Contact(s): David Behzadpour
David.Behzadpour@ks.gov
Phone: 785-291-3847
FHWA Technical Liaison(s): Justin Ocel
justin.ocel@dot.gov
Phone: 202-493-3080
Commitments by Organizations
Organization Year Commitments Technical Contact Name Funding Contact Name Contact Number Email Address
Kansas Department of Transportation 2014 $40,000.00 Mark Hurt David Behzadpour 785-291-3847 David.Behzadpour@ks.gov
Kansas Department of Transportation 2015 $40,000.00 Mark Hurt David Behzadpour 785-291-3847 David.Behzadpour@ks.gov
Kansas Department of Transportation 2016 $10,000.00 Mark Hurt David Behzadpour 785-291-3847 David.Behzadpour@ks.gov
Minnesota Department of Transportation 2015 $25,000.00 Nancy Daubenberger Lisa Jansen 651-366-3779 lisa.jansen@state.mn.us
Minnesota Department of Transportation 2016 $25,000.00 Nancy Daubenberger Lisa Jansen 651-366-3779 lisa.jansen@state.mn.us
Minnesota Department of Transportation 2017 $25,000.00 Nancy Daubenberger Lisa Jansen 651-366-3779 lisa.jansen@state.mn.us
North Carolina Department of Transportation 2015 $25,000.00 Brian Hanks Neil Mastin 919 707 6661 jmastin@ncdot.gov
North Carolina Department of Transportation 2016 $25,000.00 Brian Hanks Neil Mastin 919 707 6661 jmastin@ncdot.gov
North Carolina Department of Transportation 2017 $25,000.00 Brian Hanks Neil Mastin 919 707 6661 jmastin@ncdot.gov
Oklahoma Transportation 2015 $25,000.00 Wes Kellog Ron Curb (405)420-9163 rcurb@odot.org
Oklahoma Transportation 2016 $25,000.00 Wes Kellog Ron Curb (405)420-9163 rcurb@odot.org
Oklahoma Transportation 2017 $25,000.00 Wes Kellog Ron Curb (405)420-9163 rcurb@odot.org
Pennsylvania Department of Transportation 2015 $10,000.00 Guozhou Li Heather Sorce 717-214-9508 hsorce@pa.gov
Pennsylvania Department of Transportation 2016 $25,000.00 Guozhou Li Heather Sorce 717-214-9508 hsorce@pa.gov
Pennsylvania Department of Transportation 2017 $25,000.00 Guozhou Li Heather Sorce 717-214-9508 hsorce@pa.gov
Pennsylvania Department of Transportation 2018 $25,000.00 Guozhou Li Heather Sorce 717-214-9508 hsorce@pa.gov
Texas Department of Transportation 2015 $30,000.00 Lianxiang Du Ned Mattila 512-416-4727 ned.mattila@txdot.gov
Texas Department of Transportation 2016 $30,000.00 Lianxiang Du Ned Mattila 512-416-4727 ned.mattila@txdot.gov
Texas Department of Transportation 2017 $30,000.00 Lianxiang Du Ned Mattila 512-416-4727 ned.mattila@txdot.gov

Study Description

Study Description

Fatigue cracks have been a major issue for steel bridges in the nation. State DOTs currently rely on a two-year inspection period to examine steel bridges for detecting fatigue crack activities. However, human inspection is time consuming, labor intensive, cost inefficient, and prone to error. Although Nondestructive Evaluation (NDE) techniques can improve inspection accuracy, the lack of autonomy and continuity in the inspection process still limits its ability to capture critical crack development in a timely fashion. After all, these cracks may occur between scheduled inspection periods and therefore can lead to catastrophic failure of steel bridges.

Measuring strain-induced crack development is an effective way of monitoring fatigue cracks. However, due to the randomness of crack paths, traditional strains sensors, such as metal foil strain gauges, are small and can only be deployed in a small and localized region, limiting their capability of detecting these cracks. Moreover, the limited ductility of these foil gauges leads to breakage under excessive strain, typical during crack formation. Meanwhile, a traditional wired monitoring approach imposes high cost to the overall system due to bulky data acquisition units and expensive cabling work, especially for long-span bridges. The centralized management scheme limits its flexibility and continuous monitoring capability due to potential data inundation.

Objectives

The main objective of this proposed research is to provide state DOTs a practical and cost-effective long-term fatigue crack monitoring methodology using a wireless elastomeric skin sensor network. This research is intended to demonstrate the value-added of fatigue crack monitoring of steel bridges using wireless skin sensors over the traditional bridge inspection in the following ways:

(1) The ability to collect objective information regarding fatigue crack activity under in-service loading of bridges in a continuous manner, improving the assessment, safety, and reliability of fractural-critical bridges, and providing early warning regarding evolving internal defects.

(2) The ability to improve prioritization of bridge repairs (condition-based maintenance) and retrofit for fatigue cracks so as to maximize the effectiveness of limited resources.

(3) The ability to better assess the effectiveness of various fatigue repair and retrofit techniques for steel bridges through long-term crack monitoring.

Scope of Work

The proposed research consists of three phases of tasks from the development and validation of the basic crack sensor (Phase I), design, implementation, and small scale validation of the wireless data acquisition system and the autonomous sensor network operation strategies (Phase II), to the robustness, large scale, and long-term full scale validation tests of the integrated wireless crack sensor network system (Phase III).

Phase I tasks: Crack sensor

1. Crack sensor fabrication: Fatigue crack sensors will be developed by fabricating the skin sensors tailored to fatigue crack detection. The thickness of these sensors will be 40 µm to enhance the mechanical robustness under harsh environment.

2. Small scale validation: Tests will be designed and carried out to validate the crack detection capability of the crack sensor. The test setup will consist of a pre-notched steel member subjected to fatigue loading. The fatigue testing facility at the University of Kansas will also be used to perform tensile fatigue tests and bending fatigue tests. An off-the-shelf data acquisition system will be adopted to measure the capacitance change of the sensors under crack development. Metal foil gauges will be used to provide reference measurement for validation.

Phase II tasks: Wireless crack sensor network

3. Wireless data acquisition (DAQ) system: A wireless data acquisition system will be developed for measuring capacitance change of the elastomeric skin sensor. The Imote2 smart sensor platform is selected because of its fully tested software package, which serves as the foundation of this integrated wireless skin sensor network system. The Imote2 sensor can measure voltage inputs between -5 V and +5 V using a stackable data acquisition (DAQ) board. An interface board between the elastomeric skin sensor and the Imote2 DAQ board will be developed to convert capacitance change into voltage signals.

4. Data quality assessment: The quality of data collected by the integrated wireless sensing system will be evaluated. Focus will be placed on the noise level and resolution. The goal is to make sure the integrated system has adequate resolution and low noise level to capture the strain change associated with fatigue crack activity.

5. Crack detection algorithm: Algorithms will be developed to process the measured strain data to reveal the crack activities underneath the skin sensor. Various sensor patterns will be investigated based on typical scenarios of fatigue cracks. Data fusion strategies combining on-board and in-network data processing will be implemented and tested for detecting active fatigue cracks as well as the propagation direction of these active cracks. The goal is to be able to make decisions using the smart sensors by locally combining and processing data measured at different locations without transmitting raw data back to the base station.

6. Autonomous sensor network: Software will be designed to enable autonomous operation of the sensor network. Practical issues such as triggering of the sensor network, sleep-cycling to conserve energy, energy harvesting methods such as solar panels, and other energy efficient operation issues, etc. will be addressed in this task.

7. Small scale system validation: The integrated system will be validated using the small scale pre-notched steel beam from Task 2 of Phase I.

Phase III tasks: Large/full scale validation

8. Robustness test: The robustness of both hardware and software will be tested. Mechanical robustness against external impact on the elastomeric skin sensors, long term stability of the electrical signal generated by the crack sensor, and fault tolerance of the software for autonomous operation will be tested.

9. Large scale validation: A network of crack sensors will be deployed on the existing large scale steel girder test bridge at the University of Kansas, which is a 30-ft long, three-girder bridge that includes realistic fatigue sensitive details. The

Comments

This project is broken out into three Phases for a total cost of $495,000. Iowa DOT is funding Phase One and part of Phase Two for a cost of $92,150.

We are looking for 4-5 other states to committ $25,000-30,000 per year for three years to do all three phases.

We have requested 100% SPR Funding

Title File/Link Type Private
Final report TPF-5(328) _FinalReport.pdf Final Report Public
TPF-5(328) Waiver Approval Waiver Approval - Solicitation#1372.pdf Memorandum Public
TPF-5(328) Closeout Letter TPF-5(328) Closeout Memo.pdf Memorandum Public
Acceptance Letter Acceptence Letter.pdf Other Public
TPF-5(328) Closeout Funding Spreadsheet TPF-5(328) Closeout Funding Spreadsheet.pdf Other Public
Dec 2015 Quarterly Report SPR_quarterly_report_TPF-5(328) 01-29-16.pdf Quarterly Progress Report Public
June 2016 Quarterly Report SPR_quarterly_report_TPF-5(328) 07-29-16.pdf Quarterly Progress Report Public
March 2016 Quarterly Report SPR_quarterly_report_TPF-5(328) 04-30-16.pdf Quarterly Progress Report Public
September 2015 Quarterly Report SPR_quarterly_report_TPF-5(328) 09-30-15.pdf Quarterly Progress Report Public
Quarterly Reports Sept 2016 SPR_quarterly_report_TPF-5(328) 10-28-16.pdf Quarterly Progress Report Public
Quarterly Report Dec 2016 SPR_quarterly_report_TPF-5(328) 01-31-2017.pdf Quarterly Progress Report Public
Quarterly Report March 2017 SPR_quarterly_report_TPF-5(328) 04-30-2017.pdf Quarterly Progress Report Public
Quarterly Report June 2017 SPR_quarterly_report_TPF-5(328) 07-31-2017.pdf Quarterly Progress Report Public
Quarterly Report Sept 2017 SPR_quarterly_report_TPF-5(328) 10-30-2017.pdf Quarterly Progress Report Public
Quarterly Report Dec 2017 SPR_quarterly_report_TPF-5(328) 1-31-2018 - revised.pdf Quarterly Progress Report Public
Quarterly Report March 2018 SPR_quarterly_report_TPF-5(328) 04-24-2018.pdf Quarterly Progress Report Public
Quarterly Report June 2018 SPR_quarterly_report_TPF-5(328) 07-13-2018.pdf Quarterly Progress Report Public
Quarterly Report Sept 2018 SPR_quarterly_report_TPF-5(328) 09-30-2018.pdf Quarterly Progress Report Public

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