Induction Cooker Ceramic Panel Crack Identification Dataset
#image classification #defect detection #industrial detection #quality control #safety monitoring
- 5000 records
- 1.5G
- JPG/PNG/JSON
- CATL
MOBIUSI INC
Updated:2026-05-09
AI Analysis & Value Prop
In the current industrial field, the crack problem of induction cooker ceramic panels poses a threat to product safety, leading to potential explosion risks. Existing detection methods mostly rely on manual inspection, which is inefficient and prone to errors. This dataset aims to provide high-quality crack image data to train machine learning models, automating the detection process and improving detection efficiency and accuracy. The dataset contains 5000 crack images taken with high-resolution cameras in actual production environments, ensuring the data is authentic and reliable. Quality control measures include multiple rounds of annotation, consistency checks, and expert reviews to ensure the accuracy of the annotations. Data is stored in JPG format for easy loading and processing.
Dataset Insights
Sample Examples
8babceee**.jpg|1080*1440|435.77 KB
c0bd3574**.jpg|1080*1892|169.05 KB
53eaa464**.jpg|1080*1408|155.18 KB
4f8e3098**.jpg|1080*1411|203.55 KB
29e38c4c**.jpg|1080*1386|216.17 KB
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| crack_presence | boolean | Determines the presence of cracks on the ceramic panel as a boolean value. |
| crack_location | string | The specific location of cracks on the ceramic panel, such as the upper left corner, lower right corner, etc. |
| crack_length | float | The length of the crack, measured in millimeters. |
| crack_width | float | The width of the crack, measured in millimeters. |
| crack_depth | float | The depth of the crack, measured in millimeters. |
| crack_type | string | The type of crack, such as surface crack, through crack, etc. |
| image_quality | string | The quality rating of the image, such as clear, blurred, etc. |
| lighting_conditions | string | Description of lighting conditions when the image was taken, such as natural light, artificial light, etc. |
| panel_color | string | The color of the ceramic panel of the induction cooker. |
| background_clarity | string | Description of the clarity of the background, such as clear, blurred, etc. |
Compliance Statement
| Authorization Type | Proprietary - Commercial AI Training License (No Redistribution) |
| 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 main purpose of the electromagnetic stove ceramic panel crack recognition dataset?
- The dataset is mainly used for recognizing and detecting cracks on ceramic panels of electromagnetic stoves to assist in quality inspection and product maintenance.
- Which industrial applications is this dataset suitable for?
- This dataset is suitable for industrial automation inspection, product quality control, and smart manufacturing.
- Why is crack detection on electromagnetic stove ceramic panels important?
- Detecting cracks on the ceramic panels of electromagnetic stoves helps prevent safety hazards, ensures product quality, and reduces maintenance costs.
- What types of images are included in the dataset?
- The dataset includes normal images of electromagnetic stove ceramic panels as well as anomalous images with cracks.
- How can this dataset be used to improve the safety of electromagnetic stove products?
- By training detection models to recognize cracks, issues can be identified early, thereby enhancing the safety of electromagnetic stove products.
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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Induction Cooker Ceramic Panel Crack Identification Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/d1d116f913f6339b5ca6fd4af13676de},
urldate={2025-09-15},
keywords={induction cooker, ceramic panel, crack identification, industrial detection, dataset},
version={1.0}
}Using this in research? Please cite us.
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