When an electrical discharge or localized overheating occurs inside a transformer, the oil and paper insulation decompose, producing gases that dissolve in the oil. DGA reads these gases the way a doctor reads a blood test: an early diagnosis without opening up the patient.
How Does the Analysis Work?
An oil sample is taken using a method that prevents air from entering, and it is sent to a laboratory where the dissolved gases are extracted and their concentrations measured in parts per million (ppm). The results are then interpreted by comparing them to reference limits and to how quickly they increase from one sample to the next.
What the Main Gases Indicate
| Gas | Most Likely Indication |
|---|---|
| Hydrogen H₂ | Partial Discharge |
| Acetylene C₂H₂ | High-energy electrical arc — the most dangerous indicator |
| Ethylene C₂H₄ | Severe oil overheating (above approximately 300°C) |
| Methane and Ethane CH₄ / C₂H₆ | Low to moderate overheating |
| CO and CO₂ | Degradation of the paper (cellulose) insulation of the windings |
Important Points in Interpretation
- The rate of increase between samples is more important than the absolute value of a single sample.
- Standard interpretation methods such as Rogers' ratios and the Duval triangle are used to determine the likely fault type.
- A sudden rise in acetylene is a serious alarm requiring urgent action, not just monitoring.
- A concerning DGA result combined with a Buchholz relay alarm = take the transformer out of service and investigate immediately.
Sample answer: Acetylene is generated at extremely high temperatures that are usually produced only by an electrical arc inside the transformer, making it the most dangerous fault gas. A noticeable rise calls for taking the transformer out of service or intensifying urgent monitoring, taking another sample to confirm, and correlating it with the other gases and with additional checks such as Buchholz and electrical tests before deciding to return it to service.
Interpreting a single isolated DGA sample. Sound diagnosis is based on the time trend and comparison of successive samples, since a value that has been stable for years is very different from the same value that has doubled within a month.
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