报告详情
SAGECN: A Spectral-and-GraphSAGE Enhanced Convolutional Network for Robotic Arm Fault Diagnosis
编号：21
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更新：2025-06-13 18:26:43 浏览：45次
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摘要
Modern industrial robotic systems often operate under dynamic working conditions. Motors in the robotic arm are prone to faults and lead to system instability and performance degradation. Existing fault diagnosis approaches typically rely on static signal features or fixed thresholds, limiting their ability to capture temporal dynamics and structural dependencies. These methods treat sensor channels independently and lack mechanisms to model the temporal evolution and inter-signal correlations, which are critical for detecting subtle and localized fault patterns. This paper proposes a Spectral-and-GraphSAGE Enhanced Convolutional Network (SAGECN) that combines a Graph Convolutional Network and Graph Sample and Aggregate for robotic motor fault diagnosis. Firstly, sensorial time series data is converted into a path graph using a sliding window mechanism to preserve temporal continuity. Then, a multi-stage GNN encoder is constructed by stacking Graph Convolutional Networks (GCN) and Graph Sample and Aggregate (GraphSAGE) layers, enabling the extraction of both global and local structural features. Finally, top-k pooling is applied for hierarchical node selection and graph-level representation learning. Experimental results on a public fault-injected motor dataset demonstrate that the proposed model achieves superior performance in classification accuracy and generalization compared with traditional graph-based methods.
关键词
Motor fault diagnosis,Industrial robotics,Path graph,Graph neural network,Time-series modeling
报告人
Weixia Hao
Student Beihang University (Beijing University of Aeronautics and Astronautics)稿件作者
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重要日期
-
会议日期
08月01日
2025
至08月04日
2025
-
06月23日 2025
初稿截稿日期
主办单位
中国机械工程学会设备智能运维分会
承办单位
新疆大学
联系方式
- Mrs. Yanruqiang
- ya******@xjtu.edu.cn
历届会议
-
2025年08月01日 中国 wulumuqi
2025 International Conference on Equipment Intelligent Operation and Maintenance -
2023年09月21日 中国 Hefei
第一届（国际）设备智能运维大会
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