Wind Turbine Blade Surface Damage Inspection and Defect Recognition Dataset

#Surface defect object detection #Defect image classification #Defect region localization #Annotation parsing #Inspection image quality screening #Scheduled blade inspections #Drone-based blade imaging #Wind farm defect review #Blade maintenance work order triage #Remote inspection platform integration

3264
0.1GB
piece
CATL
MOBIUSI INC

Updated:2026-11-04

AI Analysis & Value Prop

This dataset is designed for surface inspection of wind turbine blades. It includes blade image records and corresponding annotation file paths, along with category IDs, image dimensions, and format information to support image and annotation management. The data can be used to train and evaluate blade surface damage recognition models, supporting defect screening, inspection assistance, and image analysis in wind turbine maintenance workflows.

Dataset Insights

Sample Examples

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Technical Specifications

Field	Type	Description
file_name	string	File name
quality	string	Resolution
image_id	string	A unique identifier for the image record.
image_path	string	The file path or location of the image.
label_path	string	The file path or location of the annotation file associated with the image.
category_id	array	The identifier for the category assigned to the image or annotation.
image_width	number	The image width, typically measured in pixels.
image_format	string	The image file format.
image_height	number	The image height, typically measured in pixels.

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 does the dataset include?: It includes image-related records for blade surface inspection, annotation file paths, category IDs, and fields for image width, height, and format. Image records can be linked with annotations using the corresponding paths and record information.

Are the defect categories and dataset size specified?: The available information does not specify defect category names, sample counts, or image resolution ranges. Check the product details or sample files before use to confirm the category definitions, dataset size, and file specifications.

Which model tasks is the data suitable for?: It can support visual tasks such as blade surface defect classification, object detection, and defect region localization, as well as inspection image screening and model evaluation. The available tasks depend on the annotation types and category structure in the annotation files.

How can I obtain the data, and what are the licensing terms?: The delivery method, permitted uses, and commercial licensing terms are governed by the product page and its license. Before deployment or redistribution, confirm that the license covers your intended use and verify which image and annotation files are included.

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Cite this Work

@dataset{Mobiusi2026,
  title={Wind Turbine Blade Surface Damage Inspection and Defect Recognition Dataset},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/01bed9451b60946e7884afd1763de2d2},
  urldate={2026-11-03},
  keywords={wind turbine blade defect dataset,blade inspection images,surface damage recognition,wind turbine defect detection,wind turbine maintenance data,blade image annotations,wind energy visual AI,blade defect detection model},
  version={1.0}
}

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