1. How is crack detection accuracy achieved?
AI detection accuracy refers to the rate at which the system correctly detects and classifies defects from inspection imagery. RIEJIAN AI is trained on over 200,000 crack defect samples. Cracks are the hardest type of apparent defect to detect on concrete bridges, yet accuracy exceeds 90%; routine defects such as honeycomb, spalling and exposed rebar have more obvious features and achieve even higher accuracy. Accuracy relies on both “imaging + algorithm”: on the imaging side, a 100MP medium-format camera with telephoto lens and dual stabilization clearly captures 0.1mm-level cracks from a safe distance; on the algorithm side, a mature AI model automatically detects and labels, followed by professional engineer review.
2. Key factors affecting detection accuracy
| Factor | Impact | Description |
|---|---|---|
| Training samples | Determines baseline model capability | 200,000+ crack samples are the premise of 90% accuracy |
| Imaging quality | Determines detectable detail | 100MP + telephoto + stabilization ensure clear imaging |
| Shooting distance | Determines resolution | Greater distance means less detail; maintain designed distance |
| Lighting conditions | Affects contrast | Dark areas such as T-beams and girder soffits need fill light or parameter adjustment |
| Defect characteristics | Affects detection difficulty | Cracks hardest; honeycomb, spalling relatively easier |
3. Can accuracy be even higher?
Yes. Camera technology supports detection at 0.05mm or even smaller scales, but there is an engineering trade-off: each time resolution doubles, operational efficiency drops by about four times. Engineering practice therefore uses 0.1mm as the routine standard; when higher accuracy is needed, shorten the distance for targeted re-capture.
4. Applicable conditions and scenarios
- Routine bridge inspection: automatic full-bridge collection along preset routes, standardized output of detection + review
- High-precision verification: shorten distance for targeted re-capture of suspected fine cracks
- Periodic inspection scoring: detection results mapped to members, participating in technical condition evaluation
5. Notes
Apparent interference such as water stains and dirt may affect determination, and areas with complex interference require manual review; detection accuracy refers to detecting and classifying visible cracks, not diagnostic conclusions about structural defects.