Predict Equipment Maintenance with Vision AI
See how vision AI catches equipment problems before they become failures.
Add a continuous inspection layer to every electrical asset with vision AI for transformer and switchgear inspection. Built for the fleets where a transformer that fails is a replacement measured in years, the assets are outdoors aging in weather, and the inspection cadence is however often a truck can roll. Whether you're building transformers and switchgear, operating substations, or running data center electrical rooms, Roboflow watches every asset continuously, with per-asset records behind every inspection program.
Manufacturing and Assembly:
Substations and Field Assets:
Fleets, Thermal, and Systems Integration:
Bring intelligence to every asset today. Stop asset defects from becoming unplanned outages, lead-time-year replacements, or the failure a camera watched develop with nobody watching the camera.
What is transformer and switchgear inspection with Vision AI?
Transformer and switchgear inspection with vision AI uses computer vision models to inspect electrical assets in the factory and the field: assembly, wiring, and torque verification during manufacturing, oil leaks, corrosion, and bushing condition on in-service assets, continuous analog gauge reading, and thermal anomaly detection from IR feeds. Models trained on your actual assets watch continuously, with per-asset records that support NERC compliance programs and asset management documentation.
Can Vision AI monitor outdoor electrical assets?
The substation is the outdoor hard case: assets decades old and no two alike, lighting that swings from dawn glare to night rain, and the difference between a rain streak and an oil weep deciding whether a crew rolls. Deep-learning models trained on your actual assets, sites, and seasons learn each asset's normal appearance across conditions, flag the stain that grows, the corrosion that spreads, and the needle that moves, hold that judgment through weather a rule-based system false-alarms on, and route uncertain changes to an engineer instead of guessing, between every truck roll instead of on them.
Does this replace DGA and partial discharge monitoring?
No. Dissolved gas analysis keeps owning oil chemistry, partial discharge monitors keep their electrical role, and SCADA keeps the telemetry it already carries. Vision AI adds the layer none of them see: the oil stain spreading under a radiator, corrosion climbing a bushing, the analog gauge that never got wired into telemetry, and the hot connection an IR feed shows but nobody reviews. Chemistry, electrical signatures, telemetry, and visual findings land in the same per-asset record, which is what a failure investigation actually needs.
Can it integrate with our SCADA, historians, and asset systems?
Yes. Roboflow Inference exposes a standard API and supports common industrial protocols, so inspection events flow into your existing systems: SCADA and HMI platforms like Ignition and AVEVA, historians, asset management and EAM platforms, and MES and ERP platforms like SAP and Oracle, through REST, MQTT, OPC UA, and direct database writes. Alarm-level integration raises a flag the moment a change is detected, and every event carries asset, site, imagery, and disposition, with a full record behind every audit and every investigation.
