CBM AI-BASED DIAGNOSIS SERVICE

The distinctive advantage of Gas Insulated Switchgear (GIS) are: compact, low weight, high reliability, safety against touch
contact, low maintenance and long life. To utilize GIS advantages, it is necessary to detect the PD defect types in operation
and analyze the PD source location accurately.

Need for AI-BASED advanced diagnosis for GIS

While there is an increasing demand for GIS with its many advantages such as being airtight and small, it consumes a lot of time and is expensive in case of breakdown. Most GIS accidents are caused by foreign substances (conductive particles, protrusion electrode) and loosened bolts inside the GIS. To prevent GIS accidents in advance, it requires advanced diagnosis to determine whether or not there is a problem in a live wire.

AI-BASED Diagnosis overview

When partial discharge occurs inside GIS, it leads to the generation of electro-magnetic waves in the broadband ranging from several hundred MHz to several GHz and this electromagnetic wave leaks through the insulation spacer or earth wire. It uses high sensitivity internal and external sensors to detect and analyze electromagnetic waves radiating from the defective source inside GIS to diagnose whether or not partial discharge has occurred. Reduce the scale of ripple effect of GIS accidents with early detection of breakdown. Stable operation of the equipment thanks to advanced diagnosis for GIS.

Available services

    • Comparison between noise signals and the internal signals of the GIS sensor

    • Differentiates the PD signal from background noise

    • Identifies background noise sources

    • Proceeds with Precision Diagnosis if a PD signal is detected

    • Analyzes a PD defect type with the evaluation of streamed data

    • Identifies the PD defect type in the PD Pattern Library with Comparative

    • pattern analysis on the consecutive data

    • PD source location can be estimated by Time of Arrival Method.