---
title: "CWRU bearing data: research papers using this data"
description: "From Nov 2023 to Oct 2026, 23 archived papers mentioned CWRU bearing data in their title, abstract or keywords (the search of earlier months' full texts is still under way), most of them in Feb 2024 (2)."
url: https://scholar4ai.com/datasets/cwru-bearing-data
markdown_url: https://scholar4ai.com/datasets/cwru-bearing-data.md
license: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/)
share_text: "From Nov 2023 to Oct 2026, 23 archived papers mentioned CWRU bearing data in their title, abstract or keywords (the search of earlier months' full texts is still under way), most of them in Feb 2024 (2). (as of 2026-11-05)"
data_url: https://scholar4ai.com/data/rankings.json
updated: 2026-11-05T06:02:37+09:00
window: 2026-10-07 to 2026-11-05
source: OpenAlex (CC0)
---

# CWRU bearing data

[Browse dataset profiles](https://scholar4ai.com/datasets/directory/page/2.md)

Bearing, engine, battery and process data used to compare fault-diagnosis and remaining-life models.

- data category: Industrial fault and prognostics benchmarks
- 0 papers in the last 7 days
- Names searched for: CWRU, Case Western Reserve University bearing

Most-used data: https://scholar4ai.com/rankings/datasets.md · All Industrial fault and prognostics benchmarks datasets: https://scholar4ai.com/datasets/industrial-fault-and-prognostics-benchmarks.md



## Key findings

- From Nov 2023 to Oct 2026, 23 archived papers mentioned CWRU bearing data in their title, abstract or keywords (the search of earlier months' full texts is still under way), most of them in Feb 2024 (2).
- No paper of the tracked journals mentioned CWRU bearing data in the last 30 days (2026-10-07 to 2026-11-05).
- From 2017 to 2026 (so far), CWRU bearing data was mentioned in 30 papers in the tracked journals, most of them in AI (29) and operations research (1).
- 6 of them were published in 2025, against 0 in 2017.
- Since 2023, the institutions with the most of these papers were Chinese University of Hong Kong (2), Hanoi University of Science and Technology (2) and Harbin Institute of Technology (2).
- The journals publishing most of them were Artificial Intelligence Review (4), Neural Networks (3) and Applied Intelligence (3).
- The most-cited of them is “Autoencoders and their applications in machine learning: a survey” (Artificial Intelligence Review, 2024), with 613 citations.
- Papers use CWRU bearing data most often with ImageNet (5), CIFAR-10 / CIFAR-100 (4) and MNIST / Fashion-MNIST (4); it has 3 partners in the code and data network, in the group around ImageNet, CIFAR-10 / CIFAR-100, MNIST / Fashion-MNIST.

## Mentions over 36 months

*Papers mentioning it by publication month, Nov 2023 to Oct 2026 (titles, abstracts and keywords; the full texts of earlier months are still being searched)*

| Trend | Nov 23–Oct 24 | Nov 24–Oct 25 | Nov 25–Oct 26 | 36 months |
|---|---:|---:|---:|---:|
|  | 9 | 8 | 6 | 23 |

## Papers per year

*Papers per publication year and category*

| Category | 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 | 2024 | 2025 | 2026 (so far) |
|---|---:|---:|---:|---:|---:|---:|---:|---:|---:|---:|
| [AI](https://scholar4ai.com/categories/ai.md) | 0 | 0 | 0 | 0 | 3 | 4 | 1 | 10 | 6 | 5 |
| [Operations Research](https://scholar4ai.com/categories/operations-research.md) | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
| All categories | 0 | 0 | 0 | 0 | 3 | 4 | 1 | 10 | 6 | 6 |

## Where the papers come from

*Journals with the most papers, since 2023*

| # | Journal | Papers |
|---:|---|---:|
| 1 | [Artificial Intelligence Review](https://scholar4ai.com/journals/artificial-intelligence-review.md) | 4 |
| 2 | [Neural Networks](https://scholar4ai.com/journals/neural-networks.md) | 3 |
| 3 | [Applied Intelligence](https://scholar4ai.com/journals/applied-intelligence.md) | 3 |
| 4 | [Knowledge-Based Systems](https://scholar4ai.com/journals/knowledge-based-systems.md) | 3 |
| 5 | [Neural Computing and Applications](https://scholar4ai.com/journals/neural-computing-and-applications.md) | 2 |
| 6 | [IEEE Transactions on Neural Networks and Learning Systems](https://scholar4ai.com/journals/ieee-transactions-on-neural-networks-and-learning-systems.md) | 2 |
| 7 | [IEEE Transactions on Pattern Analysis and Machine Intelligence](https://scholar4ai.com/journals/ieee-transactions-on-pattern-analysis-and-machine-intelligence.md) | 1 |
| 8 | [Knowledge and Information Systems](https://scholar4ai.com/journals/knowledge-and-information-systems.md) | 1 |
| 9 | [Journal of Heuristics](https://scholar4ai.com/journals/journal-of-heuristics.md) | 1 |
| 10 | [Cognitive Computation](https://scholar4ai.com/journals/cognitive-computation.md) | 1 |

*Institutions with the most papers, since 2023*

| # | Institution | Papers |
|---:|---|---:|
| 1 | [Chinese University of Hong Kong](https://scholar4ai.com/institutions/chinese-university-of-hong-kong.md) | 2 |
| 2 | Hanoi University of Science and Technology | 2 |
| 3 | [Harbin Institute of Technology](https://scholar4ai.com/institutions/harbin-institute-of-technology.md) | 2 |
| 4 | [Politecnico di Milano](https://scholar4ai.com/institutions/politecnico-di-milano.md) | 2 |
| 5 | Trường Đại học Khoa học và Công nghệ Hà Nội | 2 |
| 6 | Agency for Science, Technology and Research | 1 |
| 7 | [Amazon (United States)](https://scholar4ai.com/companies/amazon-united-states.md) | 1 |
| 8 | Baylor College of Medicine | 1 |
| 9 | Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine | 1 |
| 10 | [City University of Hong Kong](https://scholar4ai.com/institutions/city-university-of-hong-kong.md) | 1 |

*Countries with the most papers, since 2023*

| # | Country | Papers |
|---:|---|---:|
| 1 | China | 11 |
| 2 | Spain | 4 |
| 3 | United States | 3 |
| 4 | Australia | 2 |
| 5 | United Kingdom | 2 |
| 6 | Hong Kong | 2 |
| 7 | India | 2 |
| 8 | Iran | 2 |
| 9 | Italy | 2 |
| 10 | Vietnam | 2 |

*Keywords with the most papers, since 2023*

| # | Keyword | Papers |
|---:|---|---:|
| 1 | bearing fault diagnosis | 6 |
| 2 | CWRU bearing dataset | 5 |
| 3 | rotating machinery | 5 |
| 4 | [few-shot learning](https://scholar4ai.com/keywords/few-shot-learning.md) | 4 |
| 5 | [domain adaptation](https://scholar4ai.com/keywords/domain-adaptation.md) | 3 |
| 6 | fault diagnosis | 3 |
| 7 | [data augmentation](https://scholar4ai.com/keywords/data-augmentation.md) | 2 |
| 8 | mechanical fault diagnosis | 2 |
| 9 | predictive maintenance | 2 |
| 10 | [unsupervised learning](https://scholar4ai.com/keywords/unsupervised-learning.md) | 2 |

## Most-cited papers

*Most-cited papers since 2017*

| # | Citations | Per month | Title | Journal | Published | Authors |
|---:|---:|---:|---|---|---|---|
| 1 | 613 | 18.5 | [Autoencoders and their applications in machine learning: a survey](https://doi.org/10.1007/s10462-023-10662-6) | [Artificial Intelligence Review](https://scholar4ai.com/journals/artificial-intelligence-review.md) | 2024-02-03 | Kamal Berahmand, Fatemeh Daneshfar, Elaheh Sadat Salehi et al. |
| 2 | 139 | 5.1 | [Small data challenges for intelligent prognostics and health management: a review](https://doi.org/10.1007/s10462-024-10820-4) | [Artificial Intelligence Review](https://scholar4ai.com/journals/artificial-intelligence-review.md) | 2024-07-23 | Chuanjiang Li, Shaobo Li, Yixiong Feng et al. |
| 3 | 117 | 4.3 | [Breaking the data barrier: a review of deep learning techniques for democratizing AI with small datasets](https://doi.org/10.1007/s10462-024-10859-3) | [Artificial Intelligence Review](https://scholar4ai.com/journals/artificial-intelligence-review.md) | 2024-08-02 | Ishfaq Hussain Rather, Sushil Kumar, Amir H. Gandomi |
| 4 | 112 | 1.7 | [Residual wide-kernel deep convolutional auto-encoder for intelligent rotating machinery fault diagnosis with limited samples](https://doi.org/10.1016/j.neunet.2021.04.003) | [Neural Networks](https://scholar4ai.com/journals/neural-networks.md) | 2021-04-09 | Daoguang Yang, Hamid Reza Karimi, Kangkang Sun |
| 5 | 110 | 1.9 | [Self-supervised signal representation learning for machinery fault diagnosis under limited annotation data](https://doi.org/10.1016/j.knosys.2021.107978) | [Knowledge-Based Systems](https://scholar4ai.com/journals/knowledge-based-systems.md) | 2021-12-21 | Huan Wang, Zhiliang Liu, Yipei Ge et al. |

## Used together with

Papers use CWRU bearing data most often with ImageNet (5), CIFAR-10 / CIFAR-100 (4) and MNIST / Fashion-MNIST (4); it has 3 partners in the code and data network, in the group around ImageNet, CIFAR-10 / CIFAR-100, MNIST / Fashion-MNIST.

*What papers use CWRU bearing data together with (at least 3 papers; lift 1 = chance)*

| Used with | Type | Papers using both | Lift |
|---|---|---:|---:|
| [ImageNet](https://scholar4ai.com/datasets/imagenet.md) | Dataset | 5 | 3.4 |
| [CIFAR-10 / CIFAR-100](https://scholar4ai.com/datasets/cifar-10-cifar-100.md) | Dataset | 4 | 4.6 |
| [MNIST / Fashion-MNIST](https://scholar4ai.com/datasets/mnist-fashion-mnist.md) | Dataset | 4 | 5.8 |

The whole network: https://scholar4ai.com/code/network.md

## Cite this page

Scholar4AI. (2026). CWRU bearing data. Journal and Conference Research Rankings. Retrieved November 5, 2026, from https://scholar4ai.com/datasets/cwru-bearing-data

```bibtex
@misc{scholar4ai-datasets-cwru-bearing-data,
  author = {{Scholar4AI}},
  title = {CWRU bearing data},
  year = {2026},
  howpublished = {\url{https://scholar4ai.com/datasets/cwru-bearing-data}},
  urldate = {2026-11-05},
  note = {Journal and Conference Research Rankings; data from OpenAlex (CC0); licensed CC BY-NC 4.0}
}
```

License: CC BY-NC 4.0 (https://creativecommons.org/licenses/by-nc/4.0/).