Nolan, Shane (2017) Development of a low cost, remotely accessible condition monitoring system for a power transformer. [USQ Project]
Abstract
This project investigates the asset management strategies and condition monitoring techniques applied to power transformers. A low cost, remotely accessible condition monitoring system is designed, built, installed and tested to minimise the need for regular visual inspections.
Transformers are critical components in a power station. Continuous online monitoring of partial discharge, transformer hot spots and insulating oil is now available, however a visual inspection remains one of the simplest techniques available for assessing transformer health. Whilst effective, visual inspections are time consuming, expose personnel to being in proximity of energised high voltage equipment, and the quality of inspections varies depending on the skill or training of the person conducting the inspection.
An extensive literature review was conducted on power transformer asset management strategies, condition monitoring techniques, and applications of the low cost Raspberry Pi computer. The assembled system consists of a Raspberry Pi 2 Model B computer and modified Python programs. A Pi-camera is used to monitor oil level gauges, a FLIR Lepton thermal camera for identifying transformer hot spots and a moisture sensor for monitoring the silica gel condition in the breather. Remote access was achieved via Wi-Fi and a laptop.
A low cost, remotely accessible condition monitoring system can potentially replace visual inspections. Benefits include reduced labour costs, better data quality and increased safety by minimising personnel working in proximity of energised high voltage equipment.
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| Item Type: | USQ Project |
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| Item Status: | Live Archive |
| Additional Information: | Bachelor of Engineering (Honours) (Power) |
| Faculty/School / Institute/Centre: | Historic - Faculty of Health, Engineering and Sciences - School of Mechanical and Electrical Engineering (1 Jul 2013 - 31 Dec 2021) |
| Supervisors: | Thorpe, David; Bowtell, Les |
| Date Deposited: | 08 Sep 2021 06:02 |
| Last Modified: | 31 Jan 2023 01:40 |
| URI: | https://sear.unisq.edu.au/id/eprint/40788 |
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