Diagnostic software for insulating fluid test data. Push beyond conventional paradigms to a more correct interpretation.
Under normal operation, transformers do not generate significant amounts of dissolved gas in oil. When they do, something is wrong. A condition has developed within the transformer generating heat, which is then damaging oil or paper insulation. The dissolved gases are symptoms of that underlying problem — not the problem itself. Conventional DGA treats these symptoms with simple concentration limits. Delta-X Research treats the root cause.
Using simple gas concentrations and rates-of-change to detect faults has resulted in understating or, worse, missing problems. Delta-X Research's approach applies fault energy indices, accounts for gas loss, and uses statistical methods to provide a more reliable detection signal.
Once a fault is detected, understanding what type it is guides the maintenance response. Delta-X Research uses the 4-Simplex method — plotting five hydrocarbon gases — which provides more reliable fault type identification than the Duval pentagon, eliminating the ambiguity caused by projecting 5-dimensional data onto a 2-dimensional plot.
This is where Reliability-based DGA makes its most important contribution. R-DGA compares a transformer's fault energy index against a statistical model built from real transformer failure data, producing two risk measures: Cumulative Severity (CSEV) and Hazard Factor (HF).
The percentage of gassing transformers in the failure dataset that would fail before this transformer at its current rate of gas production. A CSEV of 80% means 80% of the transformers in the comparison group would fail first.
The probability that this transformer will fail within the next year if it continues producing gas at the current rate. A concrete, actionable number for risk management.
IEEE and IEC standards acknowledge that DGA interpretation is — in their own words — ‘more of an art than a science.’ Delta-X Research has spent 30+ years working to change that. R-DGA provides maintenance teams with statistically grounded, failure-data-informed risk assessment. No more guesswork. No more unnecessary false alarms. Just the information you need to make confident decisions.
The science behind TOA is published in peer-reviewed journals and presented at leading industry conferences including CIGRE, IEEE, and NETA. Dr. Jim Dukarm has been advancing DGA methodology since 1988.
Explore White PapersFounded in Victoria, BC in 1992, Delta-X Research has spent more than 30 years advancing the science and practice of dissolved gas analysis for transformer asset management. This article traces the development of R-DGA methodology, the TOA software platform, Monitor Watch, and the role of peer-reviewed research in grounding a commercial analytical tool in validated science.
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.
Three major analytical approaches dominate transformer DGA interpretation: Rogers Ratios, IEC 60599 key gas ratios, and Reliability-based DGA. This article explains the design purpose, theoretical basis, and known limitations of each method, and how they work together in a comprehensive diagnostic framework.
