1. How is data quality ensured?
Automatic routes unify shooting parameters at generation time per detection accuracy: overlap satisfies stitching and modeling requirements, resolution matches defect detection accuracy, and shooting angle is perpendicular to the member surface. Full automation avoids manual operation differences and ensures data standardization.
2. Requirements for AI detection imagery
| Parameter | Requirement | Role |
|---|---|---|
| Image sharpness | Meets detection accuracy | Ensures fine defects are discernible |
| Overlap | Satisfies stitching standard | Ensures no defect omission |
| Shooting angle | Perpendicular to member surface | Reduces distortion misjudgment |
3. Requirements for 3D modeling
The collected imagery simultaneously satisfies the input standards of oblique photography and LiDAR modeling; overlap and coverage are sufficient to support full-element 3D reconstruction, achieving “one collection for both detection and modeling.”
4. Applicable conditions and scenarios
- Routine full-bridge automatic inspection data collection
- Projects needing simultaneous model and defect detection output
- Multi-period standardized data accumulation
5. Notes
For special bridges needing denser collection, waypoints should be explicitly added to the route to avoid insufficient coverage from default parameters under extreme structures.