PRONOSTIA Bearing Dataset

该数据集名为Pronostia，包含了在不同负载和旋转速度下测试的滚动轴承运行至失效的数据集。通过加速度计和热电偶收集的数据能够反映设备的健康状况。为了便于机器学习模型输入，加速度计数据被转换成了对数梅尔频谱图，并且在预处理步骤中对其质量进行了提升。该数据集规模包含17个运行至失效的数据集，其任务旨在估算健康指标以及预测轴承的退化情况。

This dataset, named Pronostia, contains run-to-failure datasets of rolling bearings tested under various loads and rotational speeds. Data collected via accelerometers and thermocouples can reflect the health status of the equipment. To facilitate input for machine learning models, the accelerometer data was converted into log-Mel spectrograms, and its quality was enhanced during the preprocessing step. This dataset includes 17 run-to-failure cases, with the tasks aiming to estimate health indicators and predict the degradation of rolling bearings.