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Transformer Monitoring


Advancements in Dissolved Gas Analysis: NEI & Gassing Events

One of the most important steps when looking at DGA data is to decide whether the data support the existence of a fault that is actively breaking down the insulation before you try to use a triangle, pentagon, or gas ratio method to identify a fault type. Otherwise, you are diagnosing random...

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...

Power Transformer Failures

Electric utilities maximize utilization of their assets, while maintaining reliability. Power transformers are typically reliable, but have been known to fail suddenly and/or prematurely. Transformer failures are both costly and can leave customers dissatisfied, harming the reputation of a utility....

Transformer Monitoring

Using Transformer Monitoring Via the IoT to Combat Electricity Theft

According to the annual Emerging Markets Smart Grid: Outlook 2015 study by the Northeast Group, LLC, the world loses US$89.3 billion annually to electricity theft, with the top 50 emerging market countries losing $58.7 billion annually compared with $30.6bn in the rest of the world, including the largest industrialized economies.

In one of the more widely publicized cases recently, B.C. Hydro in Canada estimates that it was losing about 850 gigawatt hours per year due to...

Related Articles


Transformer testing and failure analysis

Power Transformer Failures

Electric utilities maximize utilization of their assets, while maintaining reliability. Power transformers are typically reliable, but have been known to fail suddenly and/or prematurely. Transformer failures are both costly and can leave customers dissatisfied, harming the reputation of a utility....

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...

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...


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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