A transformer gas-sensitive material screening method and device and a storage medium
By constructing a dual-model architecture that combines a global prediction model and an engineering sub-model, the path dependence and resource waste problems in material screening for transformer fault gas detection are solved, enabling efficient and reliable screening and verification of gas-sensitive materials, and improving the accuracy and R&D efficiency of transformer fault detection.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- CHONGQING UNIV
- Filing Date
- 2026-05-26
- Publication Date
- 2026-07-21
AI Technical Summary
In the detection of fault gases in transformers, existing technologies for screening gas-sensitive materials struggle to balance the overall understanding of the material space with the needs of engineering applications, resulting in path dependence and resource waste.
A dual-model architecture combining a global prediction model and an engineering sub-model is constructed. Through feature contribution analysis and engineering rule constraints, hierarchical scheduling of material exploration and verification is achieved, reducing path dependency risk and improving the interpretability and engineering applicability of screening results.
This effectively reduces path dependence risks in the material screening process, enhances the integrity of material spatial cognition and the engineering reliability of screening results, controls the input of verification resources, and improves the R&D efficiency and detection accuracy of transformer fault gas detection materials.
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