本项目旨在实现轴承故障的自动分类。通过对原始轴承振动信号进行包络分析、带通滤波、希尔伯特变换及短时傅立叶变换等处理，将其转换为二维图谱，再利用 2D 卷积神经网络对这些图谱特征进行学习，从而实现对轴承故障类型的精准识别，为轴承故障诊断提供高效解决方案。
☆18Aug 25, 2025Updated last year
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