26 / 2025-05-08 15:05:37
An Intelligent Detection Method for Equipment Based on SVDD
rolling bearing,fault diagnosis,feature enhancement,anomaly detection,intelligent detection
Final Paper
Jia Chen / Beijing University of Technology
Kun Zhang / Beijing University of Technology
Miaorui Yang / Beijing University of Technology
Long Zhang / East China Jiaotong University
Chaoyong Ma / Beijing University of Technology
Yonggang Xu / Beijing University of Technology
To address the spectral discrepancies in vibration signals caused by rolling bearing faults, an intelligent detection method based on SVDD is proposed. The method utilizes spectrum data from normal operating conditions to train a high-dimensional hypersphere model, determining the radius and center. Anomalies are identified by computing the distance between test spectrum and the hypersphere center. For the test spectrum classified as anomalous, a dimension-wise contribution analysis in the high-dimensional space is performed to adaptively generate a weighting vector, enhancing fault-related frequency components while suppressing normal vibrations and noise. The proposed method requires only healthy state data for both anomaly detection and feature enhancement, and demonstrates effective diagnostic performance and strong application potential in both simulation signals and experimental gearbox bearing signals.
Important Date
  • Conference Date

    Aug 01

    2025

    to

    Aug 04

    2025

  • Aug 20 2025

    Draft paper submission deadline

Sponsored By
中国机械工程学会设备智能运维分会
Organized By
新疆大学