Improvement on the eddy current measurement for rail flaw detection and signal processing

MTU Project Information


NuRail Project IDNURail2020-MTU-R18
Project TitleImprovement on the eddy current measurement for rail flaw detection and signal processing
UniversityMichigan Technological University
Project ManagerPasi Lautala
Principal InvestigatorQingli Dai
PI Contact Informationptlautal@mtu.edu
Funding Source(s) and Amounts Provided (by each agency or organization)$27,930 NURail, $22,470 Michigan Tech
Total Project Cost$50,400
Agency ID or Contract Number
Start Date2020-01-01
End Date2020-08-31
Location
Brief Description of Research ProjectThe eddy-current technology is capable for high-speed and non-contact measurement of surface defects or cracks in rail track. The current commercially available eddy-current technology for rail track examination can only indicate approximate positions with defects by showing the processed signals (not the original-live sensor signals). Furthermore, the precise crack depth, geometry and location determination cannot be obtained from the current available equipment. Hence this exploratory study aims to improve the eddy-current technology for more precise measurement of the rail defects. Also the vision techniques can be combined to confirm the damage geometry on rail. To improve rail defect detection with eddy currents, this study aims to enhance the accuracy of the eddy current sensor and build the correlation between the defect type and measured signal. The detailed study objectives are to: (1) measure the crack depth with eddy current signal in frequency domain by correlating the crack depth and orientation with measurement frequency, (2) implement sensor array for surface mapping of crack geometry sizes, and (3) combine the eddy-current signal with a video signal in the developed LabVIEW program for the further confirmation of crack type and surface geometry. For the eddy current signal processing, the signal live data will be used to extract the impedance and phase angle changes with crack depth and orientation. The surface mapping of crack surface geometry will be conducted with 4 channel sensor array measurement data. The success of this study can enhance the examination accuracy and improve its efficiency for identifying defect depth and direction.
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Completedyes
Final ReportNURail2020-MTU-R18 Final Report.pdf