Gas-insulated equipment is becoming increasingly data-rich, yet asset managers often still lack a consistent basis for translating monitoring, inspection and gas-condition information into actionable maintenance decisions.

This presentation explores how fragmented information from gas-insulated equipment can be contextualised and transformed into meaningful asset intelligence. The focus is not on individual sensors or isolated measurements, but on understanding changes over time, identifying relevant deterioration or gas-loss behaviour, assessing the confidence of available information and supporting decisions at both asset and fleet level. Particular attention is given to the challenges created by mixed fleets, different generations of equipment, varying levels of instrumentation and the transition from SF₆ to alternative insulation gases.

The objective is to demonstrate how a structured, technology-agnostic approach to GIE condition intelligence can help utilities move from data collection towards earlier detection, better prioritisation and more confident maintenance and asset-management decisions.