February 26, 2024Applied SciencesOpen Access

A Method for Matching Information of Substation Secondary Screen Cabinet Terminal Block Based on Artificial Intelligence

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WCWeiguo CaoSoutheast University ZCZhong ChenAnhui Jianzhu University CWCongying WuNanchang University

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Implication

Computational framework demonstrates automated terminal block matching for substation secondary screen cabinets, indicating improved efficiency and lower maintenance costs.

Key Points

Automated matching pairs schematic diagrams with physical terminal blocks in substation cabinets, resolving maximum common subgraph alignment without manual labeling.
Object detection networks extract component features while Neo4j database topologies support an enhanced branch-and-bound method via deep Q-network optimization.
Computational integration of multi-modular graph convolutional network models enables rapid verification, highlighting potential reductions in substation labor overhead.

Cite This Study

Cao et al. (2024) studied this question.

synapsesocial.com/papers/68e778d3b6db6435876ed404 https://doi.org/10.3390/app14051904

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Implication

Computational framework demonstrates automated terminal block matching for substation secondary screen cabinets, indicating improved efficiency and lower maintenance costs.

A Method for Matching Information of Substation Secondary Screen Cabinet Terminal Block Based on Artificial Intelligence

Discussion

Member takes

Implication

Key Points

Cite This Study

A Method for Matching Information of Substation Secondary Screen Cabinet Terminal Block Based on Artificial Intelligence

Discussion

Member takes

Implication

Key Points

Cite This Study

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