Case Study · Power Transmission
Smarter Health Monitoring for Power Transformers
How a transmission utility can move from periodic inspections to continuous, data-driven condition awareness.
Industry
Power Transmission
Focus
Transformer health monitoring
Challenge
Periodic, not continuous checks
Headline result
50% faster fault detection
The Challenge
A snapshot in time, not a continuous view.
Transformer health is managed through periodic inspections and manual record-keeping, valuable, but only a moment-in-time picture.
01
Snapshot, not a trend
Periodic inspections and oil tests capture a moment in time, not the gradual changes that precede a failure.
02
Scattered records
SCADA readings, oil tests and maintenance logs sit in separate systems, with no single view.
03
Tribal knowledge
Judging which transformer needs attention first still sits with a handful of senior engineers.
What was needed
A continuous, connected view of transformer health.
- Trends tracked across SCADA, oil-test and maintenance data, not just point-in-time checks.
- Risk-ranked priorities any engineer can act on, not just a few experts.
Our Approach
Connecting and strengthening the utility's existing practices, in four steps.
Bring the data together
SCADA and online monitoring readings, DGA results, maintenance history and inspection records are consolidated into one view. Additional sensors can be added to the most critical units.
Establish a health baseline
Each transformer is assessed against its own history and operating conditions: more useful than comparing every unit against one fixed threshold.
Detect early warning signs
AI and ML models look for gradual changes and unusual patterns across multiple parameters, such as a rising gas trend combined with higher operating temperature.
Turn insight into action
Findings are presented through simple dashboards and risk-ranked asset views. The final decision always stays with the engineers.
The goal is not to replace the utility's existing practices, it's to connect and strengthen them. The final decision always stays with the engineers.
Results
Measurable operational gains
25%
Reduction in unplanned downtime
50%
Faster fault detection time
25%
Shorter repair time (MTTR)
50%
Less manual monitoring effort
Benefits
Predictive, condition-based asset management
Better Visibility
Continuous view of the health of every critical transformer, not just a snapshot at test time.
Clearer Prioritisation
Risk-ranked asset views make it obvious which transformer needs attention first.
Stronger Decision Support
Shared, visible insight for engineers and asset managers, not knowledge held by a few experts.
Less Unplanned Downtime
Earlier warning of developing issues, supporting safer, more reliable grid operations.
Want to explore what this could look like for your transformer fleet?
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