A new AI-driven diagnostic platform could help gas operators identify liquid carryover and mist breakthrough in pipelines before they cause equipment damage or disruption.
PhaseVu AI combines live plant data with visual footage from inside gas pipelines to identify operating conditions linked to separator and filter performance.
The technology analyses factors including flow, pressure, temperature, differential pressure and liquid levels alongside video data. This creates a model of normal operating conditions for individual facilities.
It is designed to provide earlier warnings when conditions begin to change, while replacing fixed alarm thresholds with settings that adapt to operating conditions.
Liquid and mist carryover can contribute to measurement errors, compressor damage, process disruption and gas quality issues.
The platform is intended to help operators identify potential problems, investigate their causes and take corrective action before failures occur.
In one study, the system identified separator liquid level as a factor contributing to increased carryover. Lowering the level subsequently improved separator performance.
