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Research on Fault Diagnosis of Bearing Sample Imbalance Based on HCAB-SMOTE
编号：153 访问权限：仅限参会人 更新：2025-11-10 16:14:40 浏览：42次 张贴报告

报告开始：暂无开始时间（Asia/Shanghai）

报告时间：暂无持续时间

所在会场：[暂无会议] [暂无会议段]

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摘要
To addresses the issue of scarce samples and sample imbalance in marine bearing fault diagnosis, which leads to low diagnostic efficiency, and proposes a fault diagnosis method based on HCAB-SMOTE (Hybrid Clustering Boundary Synthetic Minority Over-sampling Technique). The method first extracts impact-related features from the original vibration signals; then, it utilizes HCAB-SMOTE to intelligently over-sample minority class fault samples, effectively alleviating the classifier bias problem caused by sample imbalance. Experiments were conducted using a simulated experimental dataset to compare the performance of four sampling methods, original data, SMOTE, Borderline-SMOTE, and HCAB-SMOTE, across SVM. The results indicate that in the SVM classifier, HCAB-SMOTE outperforms traditional oversampling methods in multiple key performance metrics, particularly in its ability to identify minority classes, proving its effectiveness and superiority in ship bearing fault diagnosis.
关键词
Marine bearings; HCAB-SMOTE; sample imbalance; fault diagnosis;
报告人
Yan Zhijia
postgraduate Guangdong Ocean university

稿件作者
Yan Zhijia Guangdong Ocean university
LIAO ZHIQIANG Guangdong Ocean University
Cai Renchao Guangdong Ocean University
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重要日期

  • 会议日期

    11月21日

    2025

    至

    11月23日

    2025

  • 10月20日 2025

    初稿截稿日期

  • 11月23日 2025

    注册截止日期

主办单位
IEEE Instrumentation and Measurement Society
South China University of Technology
承办单位
South China University of Technology
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