In the electric power industry

various mechanical faults of disconnector for in gas insulated switchgear (GIS) are often due to the stress variation of the driving mechanisms and conductive parts. The early manifestation of this kind of stress variation is mainly clogging defect. The identification and quantification of these clogging in GIS disconnector is of significant importance in preventing severe equipment failures. However

GIS disconnector faces challenges in identifying and quantifying the clogging defects due to the discrete nature of mechanical states resulting from industrial operational conditions. This limitation hampers the ability of maintenance personnel to effectively perceive the mechanical condition of GIS disconnector and predict potential failures. In this paper

the power curve of the driving motor under normal mechanical conditions of GIS disconnector is used as the refere; nce curve. The multi-window slope-based feature point identification method is adopted

the analysis of the switch’s operational physical processes is combined to segment the power curve of the motor. Within each segment of the switch’s operation

the Fréchet distance analysis is adopted to identify clogging defects of GIS disconnector. Furthermore

these defects are quantified by using the Fréchet distance between the standard curve and the operational curve. Finally

the effectiveness of the proposed technological approach is validated through experiments on a ZF12B-126 model GIS disconnector. The experiments demonstrate that the method adopted in this paper is sensitive to the identification of clogging defects during the early stages of its development.