Washing Machine Bearing Abnormal Noise Detection Dataset
#Anomaly Detection #Classification #Regression #Industrial Inspection #Predictive Maintenance #Quality Control
- 5000 records
- 1.2G
- JPG/PNG/JSON
- CC-BY-NC-SA 4.0
MOBIUSI INC
Updated:2026-02-04
AI Analysis & Value Prop
The current industrial landscape faces significant challenges in predictive maintenance, particularly in identifying abnormal noises from machinery components such as motor bearings. Existing solutions often rely on manual inspections, which are time-consuming and prone to human error. This dataset aims to address the need for a reliable method to detect potential anomalies in bearing performance through image analysis. The dataset comprises images captured from various bearings under different operational conditions. Data collection involved using high-resolution cameras in controlled factory environments to ensure consistent lighting and angle. Quality control measures included multiple rounds of labeling by trained technicians, consistency checks, and expert reviews to ensure high accuracy. The images are stored in JPG format, organized into folders based on bearing conditions.
Dataset Insights
Sample Examples
5a76d262**.jpg|800*1067|84.16 KB
23ebfd77**.jpg|1280*1725|115.48 KB
c781f192**.jpg|1080*1440|34.85 KB
3631cc2e**.jpg|800*1067|59.47 KB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| bearing_condition | string | Physical condition of the bearing, such as presence of wear or cracks. |
| anomaly_level | integer | Severity level of bearing anomaly, with higher values indicating more serious issues. |
| detection_confidence | float | Confidence in the model's recognition of bearing anomalies, ranging from 0 to 1. |
| surface_wear | string | Whether the bearing surface exhibits wear. |
| corrosion_presence | boolean | Whether corrosion is present on the bearing. |
| deformation_status | string | Whether the bearing exhibits deformation. |
| oil_leakage | boolean | Whether there is any oil leakage in the bearing. |
| image_clarity | string | The sharpness level of the image, such as high, medium, low. |
| lighting_condition | string | The lighting conditions during filming, such as bright or dim. |
| focus_quality | string | Whether the image is in clear focus. |
Compliance Statement
| Authorization Type | CC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike) |
| Commercial Use | Requires exclusive subscription or authorization contract (monthly or per-invocation charging) |
| Privacy and Anonymization | No PII, no real company names, simulated scenarios follow industry standards |
| Compliance System | Compliant with China's Data Security Law / EU GDPR / supports enterprise data access logs |
Frequently Asked Questions
- What is the Washing Machine Bearing Noise Detection Dataset?
- The Washing Machine Bearing Noise Detection Dataset is an image dataset used to identify potential anomalies in motor bearings to help prevent noise during machine operation.
- Which field is the Washing Machine Bearing Noise Detection Dataset mainly applied to?
- This dataset is mainly applied in the industrial field to monitor the operational status of washing machine motor bearings.
- What type of dataset is this?
- This dataset is an Object Detection dataset that uses images to identify anomalies in bearings.
- Why use the Washing Machine Bearing Noise Detection Dataset?
- Using this dataset can help identify bearing anomalies in advance, reducing the risk of noise and damage caused by bearing failures in washing machines.
- How does this dataset help in identifying bearing anomalies?
- The dataset provides labeled image data for training machine learning models to automatically detect and identify potential anomalies in bearings.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Washing Machine Bearing Abnormal Noise Detection Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/35307358a56cc60be7386a0bfcd42c85?dataset_scene_id=2},
urldate={2025-08-28},
keywords={Washing Machine Dataset,Bearing Noise Detection,Industrial Anomaly Detection,Predictive Maintenance Dataset},
version={1.0}
}Using this in research? Please cite us.
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