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Transformer Monitoring



Zensol new instrument for OLTC testing

According to CIGRE A2.34, the dynamic resistance measurement or DRM (OFFLINE) is a test that offers diagnostics for several diverter or selector switch malfunctions such as: contact problems, broken springs, broken transition resistors, poor contact pressure, inadequate transition time, momentary...

Advancements in Dissolved Gas Analysis: Data Quality

IntroductionThere is more to DGA interpretation than comparing the latest gas concentrations to limits in a table or plotting them in a triangle or pentagon to identify the apparent fault type. We have found that the whole DGA history of a transformer must be considered when interpreting its most...

Transformer Monitoring

hydrocarbon gas emission

Advancements in Dissolved Gas Analysis: Risk Assessment

In general, the purpose of periodic screening with DGA for power transformers is risk assessment. Is any transformer likely to fail in service? If so, how severe is the problem? Previous articles in this series have described ways to improve DGA interpretation. In this article we provide a glimpse of what modern statistics can say about risk assessment, after the previous steps are performed.
Conventional practice with IEEE or IEC guidelines is to compare gas...

Related Articles


hydrocarbon gas emission

Advancements in Dissolved Gas Analysis: Data Quality

IntroductionThere is more to DGA interpretation than comparing the latest gas concentrations to limits in a table or plotting them in a triangle or pentagon to identify the apparent fault type. We have found that the whole DGA history of a transformer must be considered when interpreting its most...

DGA graphs

Advancements in Dissolved Gas Analysis: Accounting for Gas Loss

Dissolved gas analysis (DGA) in transformers is a very successful periodic screening method to identify transformers that may be having problems. It is a symptom-based assessment of health, rather than a condition-based assessment. That is because the gases themselves do not cause failure, but are...

Designing A Safe & Reliable Transformer Maintenance Program

The critical importance of power to every aspect of our world cannot be over-exaggerated. It must be generated and distributed effectively to end users, and any disruption in that process means loss of operations, money, and in extreme cases, life. Therefore, the reliability of power creation and...


The Role of AI and Machine Learning in Predicting Transformer Faults

AI and Machine Learning can predict transformer faults by analyzing dissolved gas data, thermal patterns, and vibration trends to identify insulation degradation, detect anomalies, and prevent costly power transformer failures before they occur. Why AI Integration into Transformer Diagnostics...

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