Transformer Core Structure Recognition Dataset
#Object Detection #Image Classification #Quality Inspection #Core Lamination Offset Detection
- Records
- 5000 records
- Size
- 1.2G
- Format
- JPG/PNG/JSON
- Provider
MOBIUSI INC- Updated
- v1.02026-11-05
AI Analysis & Value Prop
The current industrial sector faces significant challenges in ensuring the quality and alignment of transformer core structures during manufacturing. The existing solutions often fall short in accuracy and efficiency, leading to increased costs and production delays. This dataset aims to address the technical issue of precise identification of core structures and their quality status, which is critical for enhancing the reliability of transformers. Data collection was conducted using high-resolution cameras in factory environments, ensuring diverse lighting conditions and angles. Quality control measures include multi-round annotations, consistency checks among annotators, and expert reviews to validate the data. The dataset is organized in a JPEG format, structured with clear labeling for each image. Each image is accompanied by metadata detailing the core structure characteristics and quality assessments.
Overview
Dataset Insights
Preview
Sample Examples
c2bf7a9f**.jpg|1080*1440|160.87 KB
31e465bd**.jpg|1024*768|92.29 KB
522139c6**.jpg|1422*800|179.02 KB
e7e591f3**.jpg|1067*800|66.21 KB
Schema
Technical Specifications
| Field | Type | Description |
|---|---|---|
| file_name | string | File name |
| quality | string | Resolution |
| transformer_core_type | string | The specific structural type of the transformer core. |
| defect_presence | boolean | Whether detected defects are present in the image. |
| defect_type | string | The type of detected defect, such as cracks or corrosion. |
| defect_location | string | The location of the defect in the image, such as coordinates or area description. |
| core_material | string | The material used for the transformer core. |
| core_orientation | string | Information about the orientation of the transformer core in the image |
| annotation_confidence | float | Confidence score for labels assigned either manually or by algorithm |
| image_brightness | float | The overall brightness value of the image |
| image_contrast | float | The contrast value of the image |
Trust
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
FAQ
Frequently Asked Questions
- What types of images are included in the Transformer Core Structure Recognition Dataset?
- This dataset includes high-resolution industrial images for detecting transformer core structures and identifying defects.
- How does this dataset assist in industrial quality control?
- By providing detailed image data on transformer core structures and potential defects, this dataset can enhance detection precision and efficiency, thereby improving quality control processes in industrial settings.
- What are the practical applications of using the Transformer Core Structure Recognition Dataset?
- This dataset can be used to develop automated defect detection systems, improve production line efficiency, reduce human error, and extend equipment lifespan.
- Does this dataset include annotation information?
- Yes, the dataset includes detailed annotation information to identify and analyze different structural elements and defect features of transformer cores.
- How can the reliability of the Transformer Core Structure Recognition Dataset be assessed?
- The dataset is derived from reliable industrial environments, and the images and annotations have been professionally verified to ensure data accuracy and reliability.
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Cite this Work
@dataset{Mobiusi2025,
title={Transformer Core Structure Recognition Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/503df0d27dc3257d8538c2b981219502?dataset_scene_id=2},
urldate={2025-08-28},
keywords={Transformer Dataset,Core Structure Recognition,Industrial Quality Control,Image Dataset,Machine Learning},
version={1.0}
}Using this in research? Please cite us.
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