Data for a publication - Bearing Fault Datasets 核心 · 已核验

doi:10.5281/zenodo.19329597

This dataset consists of acceleration signals obtained either from a simplified virtual prototype of the CWRU test rig modelled in the multibody simulation software Adams, or from measured signals published online at [1] by Case Western Reserve University (CWRU). Only a subset of the CWRU measurements was selected to form the experimental dataset, as specified in [2].

The signals were pre-processed by removing the linear trend, extracting the signal envelope, resampling to 6 kHz and per-signal normalising to [0, 1] interval. Next, the signals were segmented into 0.1 s windows (600-sample vectors). Variable overlap was used to mitigate class imbalance. The resulting segments were batched in groups of 8. The dataset is already partitioned into training, validation, and test subsets. The datasets were prepared using the TensorFlow framework and are provided as instances of the tf.data.Dataset class. The tensors use the variable format dtype=tf.float64, users may convert it to tf.float32 to improve computational performance.

The dataset consists of two parts: a simulated part and an experimental part.

The simulated part is structured for the domain adaptation network described in [1] and contains two types of labels: class labels and domain labels. Each data segment is associated with a 5-element label vector. The first three elements are one-hot encoded class labels in the order {"Healthy", "IR", "OR"}, and the last two elements are one-hot encoded domain labels in the order {"Simulation", "Experiment"}. Since all segments in this subset belong to the simulation (source) domain, the domain label is always [1, 0].

The experimental part consists of a labelled dataset and an unlabelled dataset. Both contain the same data segments but differ in the class-label portion of the label vectors. As in the simulated part, each segment is associated with a 5-element label vector, where the first three elements correspond to the class labels {"Healthy", "IR", "OR"} and the

落地页

https://zenodo.org/doi/10.5281/zenodo.19329597

许可证

CC-BY-4.0 (判读置信:inferred)

国内可访问性

国内直连:可达 (2026-07-11 检测) 代理通道:可达 (2026-07-11 检测)
检测口径:lychee 双通道单轮探测;「直连超时」表示检测窗口内未完成,系慢或不稳定证据,不构成封锁证据。

发布年份

2026

发布方

Zenodo

设备类型

rolling_bearing

PHM 任务

domain_adaptation

故障工况