File(s) not publicly available

Track inspections using drones and machine vision

conference contribution
posted on 11.03.2020, 00:00 by Dwayne Nielsen, Steven Moore, S Sanjar, R Goulart
The desire for continual safety improvements and increases in economic efficiency are the catalysts driving research into alternative approaches to conduct visual track inspections. This paper discusses the feasibility of using a small (under 7kg), unmanned, remotely piloted aircraft (drone) to capture track images for the automatic identification of track defects using machine vision technology in a specific and challenging geographic environment. The drone was equipped with a high-resolution camera and a precision GPS system, and followed the track geometry using predetermined waypoints. Images were taken at different heights above the track and at different times of the day (to account for shadows). The machine vision system used was trained to recognise missing sleeper clips from these track images. This paper presents the research results with a discussion on the machine vision approaches applied and camera specifications. Broader issues associated with using drone technology to conduct track inspections in desert regions are also discussed.

Funding

Category 3 - Industry and Other Research Income

History

Editor

Larsson-Kraik PO; Ahmadi A

Start Page

307

End Page

312

Number of Pages

6

Start Date

12/06/2019

Finish Date

14/06/2019

ISBN-13

9780911382716

Location

Narvik, Norway

Publisher

International heavy haul association

Place of Publication

Virginia Beach, VA.

Full Text URL

Peer Reviewed

Yes

Open Access

No

Author Research Institute

Centre for Railway Engineering

Era Eligible

Yes

Name of Conference

International Heavy Haul Association STS Conference (IHHA 2019)

Exports