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Transformer Monitoring




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...

Transformer Monitoring

Hydrogen Gas in Transformer Oil

Why event-based fault type identification is better than a sample-by-sample approach

Introduction

Fault type identification is an important step in dissolved gas analysis (DGA). When a significant amount fault gas production is detected in a transformer, we want to know what kind of physical condition could be responsible for the gassing. Knowing the type of fault can help to identify the nature and location of the problem in the transformer. That in turn can also suggest what physical inspections or tests may be warranted in order...

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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...

Smart Transformers: Enhancing Grid Efficiency and Reliability

The evolving demands of modern power grids necessitate the adoption of advanced technologies that can provide enhanced efficiency, reliability, and flexibility. Smart transformers are at the forefront of this technological revolution, offering a range of capabilities that significantly improve the...

Conductive Glues

Electrically conductive pastes in high-voltage transformers BY LISA RINALDO, Prohm-tect As with other components of North American infrastructure such as wastewater and stormwater systems, much of the continent’s electrical grid faces long-term problems. Aging facilities, rising energy...


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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