Steering Rod Detection Dataset
#Object Detection #Image Classification #Steering System Maintenance #Operational Error Prevention
- 5000 records
- 1.5G
- JPG/PNG/JSON
- CATL
MOBIUSI INC
Updated:2026-04-16
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.
Dataset Insights
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
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. |
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 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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Verified for Enterprise UseCite this Work
@dataset{Mobiusi2025,
title={Steering Rod Detection Dataset},
author={MOBIUSI INC},
year={2025},
url={https://www.mobiusi.com/datasets/79708fbcf8004130853e5d17d4ce3d9c},
urldate={2025-08-28},
keywords={Steering Rod Dataset,Industrial Image Dataset,Object Detection for Industry,Maintenance Data},
version={1.0}
}Using this in research? Please cite us.
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