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Transformer Monitoring


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....

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...

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

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Case Study: Rapid Changes in Bushing Health

Introduction
Continuous online monitoring of bushings provides real-time information which can result in the early detection of a possible failure.

Challenge: A Major Alarm
A prominent U.S. utility was looking for a way to improve system reliability for their 138kV assets. They researched and reviewed options available on the market that included affordable bushing monitoring. After review, the utility chose to pilot the Dynamic Ratings’ C50 Transformer Monitor to see if it was worth the...

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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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