Project 1.06: Progressive Fault Identification and Prognosis of Railway Tracks Based on Intelligent Inference

October 1, 2018

Progressive Fault Identification and Prognosis of Railway Tracks Based on Intelligent Inference

1.6

Project Information
Downloadable Documents

Project Summary

The objectives of this project are to synthesize novel sensors integrated with physics-informed data analytics to monitor the railway track for enhanced reliability and durability. New active sensing mechanisms will be developed, to enable autonomous detection and identification. New physics-informed statistical inference algorithms will be formulated, to realize highly accurate fault diagnosis and prognosis. Direct collaboration with industry partners will be carried out.

Principal Investigator

Dr. Jiong Tang

Institution:

University of Connecticut

Project Status

Completed

Project Cost

$277,440

Start Date

10/01/2018

Project Type

Base-funded

End Date

06/30/2022

Agency ID

69A3551847101

Sponsors:

Office of the Assistant Secretary for Research and Technology, University Transportation Centers Program, Department of Transportation, University of Connecticut.

Implementation of Research Outcomes:

The formulation of high-frequency finite element analysis with piezoelectric actuation has been shared with Sperry Rail Service and partially utilized by Sperry to facilitate wave propagation analysis in Sperry probe.

Impacts and Benefits of Implementation:

Impacts and benefits of the research have yet to be realized upon the recent completion of the work.