Please note: The algorithm descriptions in English have been automatically translated. Errors may have been introduced in this process. For the original descriptions, go to the Dutch version of the Algorithm Register.
Crack detection flood defences
- Publication category
- Other algorithms
- Impact assessment
- Field not filled in.
- Status
- In development
General information
Theme
Begin date
Contact information
Link to publication website
Responsible use
Goal and impact
- Inspecting the condition of our flood defences more efficiently and cost-effectively.
- The consequences are minimal for residents, citizens and businesses (ingelanden).
Considerations
Advantages:
- Reduced inspection burden
- More targeted deployment of personnel
- Uniform working method
- More detailed inspection
Disadvantages:
- Technical limitations, weather-dependent
- Dam with trees more difficult to inspect
- Editable process (no real-time editing of drone images yet)
Human intervention
- This digital tool remains parallel to the current work process.
- The algorithm is not autonomous, is a tool for administrators.
- Training data is carefully reviewed by in-house experts.
Risk management
- Situations labelled as a crack are always checked afterwards by an experienced inspector (fault positive labelled).
- All flood defences are periodically physically checked by an experienced inspector to prevent falsely negatively labelled cracks.
- Based on new insights, the algorithm is continuously improved and monitored.
Legal basis
The Water Act sets safety standards for flood defences, both primary and regional.
Operations
Data
Drone imagery, water mapping
Technical design
The area to be scanned is first mapped using a drone. The drone takes photos, which are then merged into an ortho-mosaic. This orthomozaic is divided into smaller segments, each of which is analysed by a segmentation algorithm to detect cracks.
To monitor the growth, size, length and width of cracks, each pixel is recorded whether it is part of a crack. These pixels can be related to coordinates making it possible to calculate all these monitoring values. Detecting the pixels of cracks is done specifically using a U-net segmentation algorithm. This algorithm is fed with images where the cracks are labelled by polygons drawn around the cracks.
External provider
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