The Methodology for Evaluating the Operating State of SF6 HVCBs Based on IDDA

TL;DR

This paper introduces a new method to evaluate the operational state of SF6 high-voltage circuit breakers using an integrated data-driven analysis model.

Contribution

The novelty lies in introducing the relative degradation weight metric and an optimized fuzzy inference system for improved evaluation accuracy.

Findings

The proposed model achieves higher evaluation accuracy compared to existing methods.

The optimized fuzzy inference system improves processing speed for continuous indicators.

The method provides a reliable basis for prioritizing maintenance sequences in HVCB components.

Abstract

To enhance the precision of evaluating the operational status of SF6 high-voltage circuit breakers (HVCBs) and devise judicious maintenance strategies, this study introduces an operational state assessment method for SF6 HVCBs grounded in the integrated data-driven analysis (IDDA) model. The relative degradation weight (RDW) is introduced as a metric for quantifying the relative significance of distinct indicators concerning the operational condition of SF6 HVCBs. A data-driven model, founded on critical factor stability (CFS), is formulated to convert environmental indicators into quantitative computations. Furthermore, an optimized fuzzy inference (OFI) system is devised to streamline the system architecture and enhance the processing speed of continuous indicators. Ultimately, the efficacy of the proposed model is substantiated through validation, and results from instance analyses underscore that the presented approach not only attains heightened accuracy in assessment compared to extant analytical methodologies but also furnishes a dependable foundation for prioritizing maintenance sequences across diverse components.

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