MPC
Project Details

Title:	An Intelligent Transportation Systems Approach to Railroad Infrastructure Performance Evaluation
Principal Investigators:	Pan Lu and Raj Bridgelall
University:	North Dakota State University
Status:	Completed
Year:	2016
Grant #:	DTRT13-G-UTC38 (MAP21)
Project #:	MPC-505
RH Display ID:	153160
Keywords:	fatalities, inspection, maintenance of way, nondestructive tests, railroad crashes, railroad tracks, rolling stock, sensors

Abstract

The method developed in this research will not rely on adapting sensor configurations and will require only a data upload capability. The new sensors will compress and upload their geo-tagged inertial data periodically to a centralized processor. Remote algorithms will combine and process the data from multiple train traversals to identify fault symptoms, rank their severity, classify fault types, and localize their position. Fault classification will enable asset managers to allocate the appropriate specialists to scrutinize the fault location.

Project Deliverables

• [Final Report] Intelligent Transportation Systems Approach to Railroad Infrastructure Performance Evaluation: Track Surface Abnormality Identification with Smartphone-Based App — MPC-19-384

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