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Quiz dotyczący sztucznej inteligencji w inspekcji infrastruktury mostowej i drogowej

Sprawdza wiedzę na temat częstotliwości inspekcji mostów w USA, segmentacji pęknięć i odległości próbkowania gruntu oraz narzędzi podziemnych, takich jak georadar i termografia.

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Pytanie 1 z 8

Under the US National Bridge Inspection Standards, how often do most highway bridges typically receive a routine inspection?

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Odpowiedzi i wyjaśnienia pojawiają się w miarę rozwiązywania quizu.

  1. Under the US National Bridge Inspection Standards, how often do most highway bridges typically receive a routine inspection?
    • Every 6 months
    • Every 5 years
    • Every 24 months
    • Only after an accident
  2. Why is crack detection usually treated as a segmentation task instead of simple object detection?
    • Practitioners need crack length and width, which requires pixel-level outlines
    • Segmentation needs no training data
    • Object detection cannot run on drones
    • Cracks are always perfectly rectangular
  3. What is ground sampling distance?
    • The distance a drone flies between batteries
    • The depth ground-penetrating radar can reach
    • The spacing between bridge piers
    • The real-world size represented by one image pixel
  4. Which tools does the guide name for revealing deterioration inside concrete decks?
    • Dashcams and GPS
    • Ground-penetrating radar and infrared thermography
    • Laser profilers and roughness indexes
    • Strain gauges only
  5. Which of these is a common source of false positives for crack-detection models?
    • Exposed rebar
    • Potholes
    • Stains, joints, shadows and formwork marks
    • Corrosion on steel
  6. In this guide, what is a digital twin of a bridge?
    • A model of the asset linked to its inspection history and sensor data
    • A second bridge built next to the first
    • A backup copy of the inspector's notes
    • A drone that follows the inspector
  7. Why can't a crack image alone determine how serious the crack is?
    • Cameras cannot capture cracks
    • All cracks are equally dangerous
    • Images are too large to analyze
    • Seriousness depends on the crack's location, the type of member and the loads it carries
  8. Which technique helps with the severe class imbalance in crack segmentation?
    • Using only color images
    • Dice or focal loss functions
    • Flying the drone higher
    • Removing all images that contain cracks