Fault Analysis of Vision System on Autonomous Blast Hole Drills

Veivers, Shannon (2018) Fault Analysis of Vision System on Autonomous Blast Hole Drills. [USQ Project]


Rio Tinto has a continually increasing number of autonomous blast hole drills operating on multiple sites in the Pilbara region of Western Australia. The vision system on these drills forms a critical layer of the functional safety system in which they operate. This research project is to objectively analyse fault data in order to ascertain best practice solutions to reduce lost time for repairs and maintenance to the components of this system.

An autonomous blast hole drill operates on a blast pattern in an active mining environment. These drills need to be able to interact safely with other production machines, support vehicles and personnel on foot at all times. The vision system is used by a remote operator in Perth in conjunction with an object detection system to safely operate.

By analysing historical fault data and interviewing support personnel, common fault modes and patterns can be identified. In depth analysis will be performed on each type of failure, the probable causes, repair options and failings in the current processes.

Targeting these common fault modes reveals two areas of improvement and their respective solutions. Low complexity hardware faults of gears or motors and software configuration faults on the PTZ cameras. By delivering a hand-held configuration tool to resolve the configuration problems for any user hardware and software issues.

The PTZ camera configuration tool dramatically reduces the repair time simply by reducing the complexity of the task. Also, by taking ownership and responsibility of low complexity repairs, the time and cost savings can be significant, especially in remote mining environments.

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Item Type: USQ Project
Item Status: Live Archive
Additional Information: Bachelor of Engineering (Honours) (Instrumentation Control & Automation Engineering)
Faculty/School / Institute/Centre: Current - Faculty of Health, Engineering and Sciences - No Department (1 Jul 2013 -)
Supervisors: Phythian, M.; Kellow, M.
Date Deposited: 29 Aug 2022 04:01
Last Modified: 29 Aug 2022 23:26
Uncontrolled Keywords: autonomous blast hole drills; fault data; analysis
URI: https://sear.unisq.edu.au/id/eprint/40668

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