Transformer Maintelligence AI-transformer diagnostics tool

Example

Analyzing DGA reports to detect gas concentrations that indicate specific types of transformer faults.

Scenario

In a scenario where a transformer exhibits elevated levels of acetylene, the AI would suggest possible overheating or arcing, prompting immediate inspections and specific maintenance actions to prevent catastrophic failures.

Example

Utilizing FRA data to assess mechanical integrity and identify issues like winding displacements or core movement.

Scenario

For a transformer with altered frequency response curves, the AI compares historical data to pinpoint deviations, suggesting potential mechanical disturbances that require targeted repair to ensure operational stability.

Example

Providing specific maintenance strategies based on the identified issues and their predicted impacts on transformer longevity.

Scenario

If a transformer shows signs of minor oil contamination, the AI might recommend oil purification over a complete oil change, considering both cost effectiveness and environmental impact.

Example

Evaluating the financial implications of various repair or replacement options based on predicted transformer life extension and failure risks.

Scenario

When faced with a decision on whether to repair or replace a transformer with core damage, the AI assesses downtime costs, repair costs, and the probability of future failures to recommend the most economical solution.