Processed subset used in our STR-DDPM experiments on the Paderborn bearing dataset

This repository provides the processed experimental subset used in our paper, “STR-DDPM: Residual-domain diffusion-based data augmentation with seasonal-trend-residual decomposition for few-shot motor fault diagnosis”, derived from the publicly available Paderborn bearing dataset. Only the subset and operating conditions used in this study are included here. The original MATLAB files were reorganized and converted into CSV format for our experimental pipeline. This record is intended to support reproducibility of the associated paper and does not replace the complete original public dataset. The original Paderborn bearing dataset is publicly available from the official Bearing Data Center of Paderborn University. According to the official dataset information, the data include synchronously measured motor currents and vibration signals, as well as additional operating-condition variables, and are provided as MATLAB files. The dataset is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License. Non-commercial academic use is allowed, citation of the original source is required, and commercial use requires contacting the original author. Users should therefore comply with the original dataset terms when reusing this processed subset.本仓库提供了我们在论文“STR-DDPM：面向少样本电机故障诊断的结合季节-趋势-残差分解的残差域扩散数据增强”中使用的经过预处理的实验子集，该子集源自公开可用的帕德博恩轴承数据集（Paderborn bearing dataset）。 本仓库仅收录本研究使用的子集与运行工况数据。原始MATLAB文件已完成重组，并转换为适配本实验流程的CSV格式。本数据集旨在支撑相关论文的可重复性研究，并非完整原始公开数据集的替代版本。 原始帕德博恩轴承数据集可从帕德博恩大学官方轴承数据中心公开获取。根据该数据集的官方说明，其包含同步采集的电机电流与振动信号，以及额外的运行工况变量，且以MATLAB文件格式提供。该数据集采用知识共享署名-非商业性使用4.0国际许可协议（Creative Commons Attribution-NonCommercial 4.0 International License）进行授权。非商业学术使用允许且需标注原始来源，商业使用则需联系原作者。因此，用户在复用此预处理子集时，需遵守原始数据集的使用条款。