AI ENHANCED INSPECTION VS TRADITIONAL
- Aspect
- Defect Detection
- Accessibility
- Efficiency & Cost
- Data Quality
- Digital Integration
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- AI-assisted analysis with manual verification ensures precise and comprehensive issue identification.
- UAVs can easily reach various parts of a bridge, supported by digital twin simulation for full inspection coverage.
- Low learning and operating costs, easy to use, and highly efficient—single-person operation supported.
- Captures high-resolution images and sub-millimeter-level measurements using professional cameras and positioning tech.
- Digital twin integration enables 3D analysis and centralized defect management for data-driven maintenance decisions.
- Manual inspections are affected by varying skills and responsibility levels, leading to misjudgments and missed defects.
- High piers and complex bridge components are hard to reach, resulting in blind spots.
- Inspection vehicles are expensive, inefficient, and pose operational safety concerns.
- Traditional methods lack complete, high-resolution, and precise data collection.
- Inspection results are hard to visualize, verify, or integrate into management systems.
OUR DRONE BRIDGE INSPECTION WORKFLOW
STEP1: DIGITAL TWIN MODELING
As part of the fist-time bridge inspection, a centimeter-level precision reality 3D model is created to achieve a digital twin. This model serves two primary purposes: firstly, as a digital base map for the 3D visualization management of defect data, allowing for the display and management of all identified defects on the model; secondly, it provides a basis for flight path planning for autonomous drone inspections.
Considering the structure and characteristics of bridges, Riebo independently developed AeroMapPro flight planning software which can significantly reduce the number of flight paths and aerial photos while ensuring the pass rate of aerial triangulation and model quality, thereby greatly improving modeling efficiency.
Real-world testing has shown that using Riebo's M-series cameras in conjunction with AeroMapPro for bridge 3D modeling, the entire modeling task for a 500-meter bridge, from data acquisition to model generation, takes less than two hours.
STEP2: ROUTE PLANNING
According to the bridge inspection standards of various countries, the most stringent requirement is to detect concrete cracks with a width of 0.1mm, therefore necessitating that the drone flies close to the structure for photography. To ensure flight safety and guarantee complete image coverage, precise flight path planning is essential.
The inspection module in AeroMapPro allows for precise flight path planning based on high-accuracy 3D models. It not only supports automatic route generation but also enables users to dynamically adjust various parameters during operation, significantly improving the efficiency of flight path planning.
STEP3: DATA ACQUISITION
The acquisition of inspection image data is carried out by a drone equipped with the professional inspection camera SF10. Field operations can be completed with just one person, one vehicle, and a single set of acquisition equipment.
The SF10 is a high-precision camera developed by Riebo based on the needs of the inspection industry. This camera utilizes a combination of a medium format image sensor (11276 x 9200 pixels) and a 120mm ultra-telephoto lens with a hundred-million-pixel resolution, enabling sub-millimeter level detection accuracy for 0.1mm cracks. It also integrates a high-precision three-axis gimbal (dynamic control accuracy ≤ 0.002°) to ensure exposure stability, providing clear and reliable defect detection data for bridges and other infrastructure.
STEP4: DATA PROCESSING
Data processing is performed using the Skyscanner software that comes standard with Riebo cameras. It supports exporting inspection data by flight or in batches, enabling efficient management of large datasets. This software can embed geographic location information into the photos, achieving high-precision coordinate correction. Furthermore, it calculates the field of view of the images based on the drone and camera's attitude information, providing data support for the precise localization of subsequent defect points.
STEP5: AI-POWERED DEFECT IDENTIFICATION
Leveraging advanced Convolutional Neural Network (CNN) deep learning algorithms, high-resolution inspection imagery enables accurate and efficient AI-powered defect recognition. The specific process is divided into two main phases:
Model Training and Crack Identification: By annotating the collected image data and training the convolutional neural network model, the system is enabled to rapidly identify crack defects within the images. As the model undergoes continuous optimization and training data accumulates, the system's recognition accuracy will progressively improve.
Image Processing and Precise Measurement: For images where defects have been identified, the system will perform processing steps such as enhancement, noise reduction, image segmentation, and edge detection. This ultimately generates crack segmentation result maps and pixel-level measurement data. Employing a deep learning-based optimized segmentation algorithm ensures high-precision segmentation results and measurement accuracy, even in the presence of fine cracks, complex backgrounds, or artificial marking interference.
Furthermore, this system can also identify other common bridge defects, including weld cracks in steel structures, corrosion, loose bolts, and voids.
STEP6: INTELLIGENT INSPECTION MANAGEMENT
Addressing the challenges of traditional bridge inspections, such as non-intuitive result presentation, inefficient process management, and insufficient data utilization, Riebo Technology has innovatively developed the Tongtu Intelligent Inspection Management System. This system breaks through the limitations of traditional paper-based reports, achieving closed-loop digital management of the entire inspection process. Its main functions include:
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End-to-End Integrated Management: Integrates core processes such as personnel scheduling, data acquisition, defect identification, and location analysis to build a standardized inspection workflow.
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3D Visualization Display: Intuitively presents the overall condition of the bridge and the spatial distribution of defects through the digital twin model.
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Intelligent Data Analysis: Supports historical defect comparison, trend prediction, and multi-dimensional statistics to deeply mine data value.
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Customized Report Output: Automatically generates inspection reports compliant with industry standards, significantly improving work efficiency.
This system effectively solves industry challenges such as data silos, supervision difficulties, and low reusability of results in traditional inspections, providing intelligent decision support for infrastructure management and maintenance.
TYPES OF BRIDGES WE INSPECT
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Highway BridgesThese high-traffic structures require regular inspection to ensure structural integrity and safety. Drones can efficiently scan underdeck areas and hard-to-reach joints without traffic disruption.
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Railway BridgesRail bridges demand high-precision inspection due to vibration, load impact, and remote locations. UAVs enable close-range imaging without the need for track shutdown.
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Cable-Stayed & Suspension BridgesLarge-scale cable structures are complex and difficult to access manually. Drones provide aerial views of cables, towers, and deck elements for stress analysis and damage detection.
FAQs About Bridge Inspection with Drones
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How does the camera ensure precise focusing?Our camera uses laser rangefinder autofocus, which measures target distance in real time and accurately adjusts the lens to ensure sharp focus under varying distances and lighting conditions.
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What is the smallest crack it can detect?The minimum focusing distance is 2 meters, enabling image capture with a resolution of 0.05 mm.
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What weather conditions are suitable for operation?Drone inspection should be conducted in favorable weather—no rain or snow, low wind speeds, adequate lighting, good visibility, and moderate temperatures—to ensure flight safety and data quality.
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Can the underside of a bridge be used for 3D modeling?Yes. With our high-resolution camera, autonomous navigation technology, and specialized flight planning software, high-quality images can be captured even under bridges where lighting is low and GPS signals are weak—meeting the requirements for accurate 3D reconstruction.
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Can the camera capture clear images in poorly lit areas inside a bridge?Yes. Our camera is equipped with an automatic auxiliary lighting system, enabling proper exposure at a distance of 6 meters even at night.
