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Home/Industrial & Manufacturing/Steering Rod Detection Dataset

Steering Rod Detection Dataset

#Object Detection #Image Classification #Steering System Maintenance #Operational Error Prevention

Records: 5000 records
Size: 1.5G
Format: JPG/PNG/JSON
Provider: MOBIUSI INC
Updated: v1.02026-11-05

AI Analysis & Value Prop

The current state of the industrial sector faces challenges such as equipment failures and operational errors that can lead to significant downtime and safety hazards. Existing solutions often lack precision in detecting issues early, leading to reactive rather than proactive maintenance strategies. This dataset aims to address the specific technical problem of accurately detecting steering rod anomalies and preventing operational errors, thereby enhancing maintenance workflows. The data is collected through high-resolution cameras in controlled industrial environments, ensuring consistency and quality. Quality control measures include multi-round annotations, consistency checks, and expert reviews to guarantee high accuracy in labeling. The data is stored in JPG format organized in a structured directory based on timestamps and labels, facilitating easy access and processing.

Overview

Dataset Insights

Preview

Sample Examples

4835acf8**.png|1400*1355|1.82 MB

969ed866**.png|1400*1806|2.56 MB

559ebf80**.png|1400*1033|1.51 MB

1eefe895**.png|1400*1726|1.78 MB

503285d0**.png|1400*2786|2.49 MB

Schema

Technical Specifications

Field	Type	Description
file_name	string	File name
quality	string	Resolution
steering_rod_presence	boolean	Whether the tie rod is marked as present in the image.
rod_position	string	Detailed description of the tie rod position in the image.
damaged_status	boolean	Whether the tie rod shows obvious damage or deformation.
corrosion_level	string	The corrosion degree of the tie rod marked as slight, moderate, severe, etc.
rod_material	string	The type of material used for the steering rod in the image.
paint_quality	string	The integrity and quality of the coating on the steering rod surface.
anomaly_detection	boolean	Indicates whether there are any anomalies in the image related to the steering rod.
bolt_presence	boolean	Whether there are connecting bolts near the steering rod.

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 is the Steering Tie Rod Detection Dataset?: The Steering Tie Rod Detection Dataset is an object detection dataset focused on the industrial sector, aiming to improve maintenance efficiency and safety of steering systems.

Which fields is the Steering Tie Rod Detection Dataset suitable for?: This dataset is suitable for the industrial sector, especially scenarios involving maintenance and inspection of steering systems.

What are the benefits of using the Steering Tie Rod Detection Dataset?: Using this dataset can improve the accuracy of detection algorithms, making maintenance and diagnostics of steering systems more efficient and safe.

What type of data does this dataset contain?: The Steering Tie Rod Detection Dataset contains image data for training and testing object detection models.

Why is steering tie rod detection important in the industrial sector?: Accurate detection and maintenance of steering tie rods are directly related to the proper operation and safety of machinery, making it crucial in the industrial sector.

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Cite this Work

@dataset{Mobiusi2025,
  title={Steering Rod Detection Dataset},
  author={MOBIUSI INC},
  year={2025},
  url={https://www.mobiusi.com/datasets/79708fbcf8004130853e5d17d4ce3d9c?dataset_scene_id=2},
  urldate={2025-08-28},
  keywords={Steering Rod Dataset,Industrial Image Dataset,Object Detection for Industry,Maintenance Data},
  version={1.0}
}

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