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State diagnosis technology of metal enclosed gas insulation equipment based on Apriori algorithm in cloud computing environment

Jiayi Wang et al.

International Journal of Environment and Pollution2026https://doi.org/10.1504/ijep.2026.152506article
ABDC C
Weight
0.50

What the paper says

In recent years, with the increasing failure rate of gas-insulated switchgear (GIS), there has been a growing need for people to understand the most common insulator issues.Therefore, real-time monitoring of its operating status is crucial to ensure the safe and reliable operation of power lines.This study proposes the use of Apriori algorithm (CFSA-AA) for cloud based fault state analysis to predict discharge faults, mechanical faults, and abnormal mechanical vibrations in metal enclosed GIS.This data is sourced from the Kaggle repository used for VSB power line fault detection.This study summarises GIS abnormal heating faults, including circuit breakers, isolating switches, shell grounding, and disc insulator bolts.The experimental results show that compared with other

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https://doi.org/https://doi.org/10.1504/ijep.2026.152506

Or copy a formatted citation

@article{jiayi2026,
  title        = {{State diagnosis technology of metal enclosed gas insulation equipment based on Apriori algorithm in cloud computing environment}},
  author       = {Jiayi Wang et al.},
  journal      = {International Journal of Environment and Pollution},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1504/ijep.2026.152506},
}

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State diagnosis technology of metal enclosed gas insulation equipment based on Apriori algorithm in cloud computing environment

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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