基于增强感知数据的牵引变压器健康评价方法及应用
李宇杰1陈学锋2段然1刘海波1虞雪林2
Health Assessment Method and Application for Traction Transformers Based on Enhanced Perception Data
LI Yujie1CHEN Xuefeng2DUAN Ran1LIU Haibo1YU Xuelin2
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作者信息:1.北京市地铁运营有限公司供电分公司, 100082, 北京;
2.上海玖道信息科技股份有限公司, 200050, 上海
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Affiliation:1.Beijing Subway Operation Co., Ltd. Power Supply Branch, 100082, Beijing, China;
2.Shanghai Jiudao Information Technology Co., Ltd., 200050, Shanghai, China
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关键词:
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Key words:
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DOI:10.16037/j.1007-869x.20250604
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中图分类号/CLCN:TM922.73
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栏目/Col:车辆制造与列车控制
摘要:
[目的]针对牵引变压器传统健康评价依赖单一传感器数据、难以全面感知设备状态的问题,提出一种基于增强感知数据的健康评价方法,旨在通过多源异构数据融合实现全面精准的状态评估。[方法]通过设计多模态感知层与数据融合架构,融合电气量、非电气量等多源数据;结合层次分析法及G1赋权法,确定指标权重及量化方法,构建健康评价模型。以地铁变压器为对象进行现场应用,部署增强感知系统并开展健康评价。[结果及结论]基于增强感知数据的健康评价方法不仅能可靠地判别设备整体健康水平,更能揭示个体间的细微状态分化及其潜在的故障模式,评价结果与设备实际运行表现及物理退化机制相符。
Abstracts:
[Objective] Addressing the limitation issue of traditional traction transformer relying on single-sensor data, which hinders comprehensive state perception, an enhanced perception data-based health assessment method is proposed. It is aimed to achieve holistic and precise condition evaluation through multi-source heterogeneous data fusion. [Method] Multi-modal sensing layer and data fusion architecture are designed to integrate electrical parameters, non-electrical parameters, and other multi-source data. Combining the AHP (analytic hierarchy process) and G1 weighting methods, indicator weights and quantification approaches are determined to construct a health assessment model. Using on-site application of metro transformers as object, the enhanced perception system is deployed and health assessment is conducted. [Result & Conclusion] The health assessment method based on enhanced perception data not only reliably determines the overall health status of equipment but also reveals subtle state differentiation among individual units and their potential failure modes. The evaluation results align with actual operational performance and physical degradation mechanisms of the equipment.
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