Advanced diagnostic software for insulating fluid test data, including dissolved gas analysis, for high-voltage apparatus. Learn from our experts.
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Delta-X Research has published a comprehensive guide to DGA interpretation — covering what DGA is, how to read reports critically, and how to make sound judgements about transformer risk. Available as a free PDF download.
A multi-part series on key advancements in dissolved gas analysis.
January 2021
What modern statistics can say about transformer risk assessment once DGA interpretation has been improved.
November 2020
Data quality is essential for effective DGA. Trend evaluation and short-term change assessment require accurate, low-variability measurements.
September 2020
Detection of carbon oxide gases indicates paper insulation deterioration — here's how to interpret the CO/CO2 ratio.
July 2020
Three case histories demonstrating how R-DGA catches problems that conventional methods miss.
The science behind R-DGA is published in peer-reviewed journals and presented at industry conferences. Explore our white papers for the technical underpinning of Transformer Oil Analyst.
View White PapersTechnical deep-dives and research updates from the Delta-X Research team.
Sean Casey is representing Delta-X Research at the IEEE Rural Electric Power Conference, connecting with rural and municipal utility engineers on how Reliability-based DGA helps smaller utility operations manage transformer health analytics, identify early fault indicators, and prioritise fleet maintenance with limited internal resources.
Delta-X Research's Kayla Whitesel presented at Energy Technology Live / the Distributed Energy Show in the UK, explaining why Reliability-based DGA provides a more scientifically rigorous foundation for transformer maintenance decisions than conventional interpretation methods.
Kayla Whitesel attended PowerTest 2026, NETA's annual electrical testing conference, connecting with the electrical testing and power systems community on DGA methodology, transformer condition assessment, and how Reliability-based DGA fits within broader condition-based maintenance programmes.
