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Crankshaft Component Detection Dataset

The Crankshaft Component Detection Dataset addresses the current challenges in the industrial sector, particularly in the automotive manufacturing industry, where the inspection of crankshaft components is critical for ensuring quality and performance. Existing solutions often lack the ability to accurately detect defects in complex structures, leading to potential failures in engine performance. This dataset aims to bridge that gap by providing a robust set of annotated images specifically for object detection tasks related to crankshaft components. Data collection involved high-resolution imaging in controlled environments, with advanced cameras capturing various angles and conditions. Quality control measures included multi-round annotations by experts, consistency checks, and thorough reviews to ensure the integrity of the data. The dataset is stored in JPG format, organized systematically to facilitate easy access and utilization.

Technical Specifications

Field Type Description
file_name string File name
quality string Resolution
component_type string The specific type of crankshaft component, such as crankshaft, bearing, flywheel, etc.
defect_type string The type of defect detected in the crankshaft component, such as cracks, deformation, wear, etc.
defect_severity string The severity level of the defect, such as minor, moderate, or severe.
defect_location string Description of the specific location of the defect on the component.
surface_condition string The condition of the component's surface, such as smooth, rough, contaminated, etc.

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

Source & Contact

If you need more dataset details, please visit Mobiusi. or contact us via contact@mobiusi.com

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