湖北民族大学学报（自然科学版）2026，Vol.44Issue(1)：62-68,7.DOI:10.13501/j.cnki.42-1908/n.2025.12.022
基于超曲空间几何结构感知的轴承多模态故障诊断方法
Bearing Multimodal Fault Diagnosis Method Based on Hyperspace Geometric Structure Perception
摘要
Abstract
To address the issue that bearing fault diagnosis methods were often sensitive to outliers and struggle to fully capture the underlying geometric structure of the multimodal data,a bearing multimodal fault diagnosis method based on hyperspace geometric structure perception(HGSP)was proposed.Firstly,the original multimodal features were uniformly mapped into a hyperspace constructed using the Poincaré ball model,enabling the characterization of latent nonlinear structural relationships among data.Then,a structure-preserving strategy based on cosine similarity was designed to perceive intra-modal semantic consistency and enhance inter-modal feature fusion.Finally,the method took into account the geometric differences and directional similarities among multi-modal data.It enhanced the robustness against outliers and the ability to perceive the geometric structure of the data,significantly improving the separability of fault categories and the diagnostic accuracy.Experiments were conducted on the Paderborn University(PU)bearing dataset and the self-developed experimental platform roadheader dataset.Compared with the locality preserving canonical correlation analysis(LPCCA)method,the average recognition accuracy of the HGSP method on the PU dataset was improved by 2.00 percentage points,and by 1.83 percentage points on the roadheader dataset.The results indicated that the method can effectively enhance the discriminability of fault categories and demonstrate practical value in bearing fault diagnosis.关键词
故障诊断/特征提取/超曲空间/余弦相似度/典型相关分析理论/多模态数据Key words
fault diagnosis/feature extraction/hyperspace/cosine similarity/canonical correlation analysis theory/multimodal data分类
机械制造引用本文复制引用
秦子倪,朱彦敏..基于超曲空间几何结构感知的轴承多模态故障诊断方法[J].湖北民族大学学报（自然科学版）,2026,44(1):62-68,7.基金项目
国家自然科学基金项目(52504161,52374155) （52504161,52374155）
安徽省自然科学基金项目(2308085MF218) （2308085MF218）
安徽省高等学校自然科学研究项目(2024AH050399) （2024AH050399）
淮南市指导性科技计划项目(2023142,2023147) （2023142,2023147）
安徽理工大学青年基金项目(QNZD202202). （QNZD202202）
