LiDAR Foreign Body Detection via Point Cloud Segmentation
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Solution Overview
Problem
Existing foreign body detection systems using fixed-point three-dimensional LiDAR scanners struggle to accurately detect small foreign objects on vast runways due to low point cloud density, which can lead to missed detections and safety risks, especially when aircraft takeoffs and landings are frequent, limiting the time available for scanning.
Innovation Solution
A foreign body detection system that includes a point cloud acquisition mechanism using a fixed-point three-dimensional LiDAR scanner to generate high-density point clouds by aligning the point clouds with known three-dimensional shape data, allowing for the detection of foreign bodies based on deviation analysis from the aligned data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If a fixed-point three-dimensional LiDAR scanner is used to scan a vast runway, then the scanning coverage is large, but the point cloud density becomes low resulting in inability to detect small foreign bodies
Solution Approach 1:
The patent divides the vast runway into multiple smaller scanning regions and performs separate high-density scans on each region. By segmenting the large monitoring area into smaller sub-regions, the system can maintain high point cloud density in each segment while collectively covering the entire runway, thus resolving the contradiction between large scanning coverage and high measurement precision.
2Measurement precision
If the LiDAR scanner scans the entire runway at high density, then small foreign bodies can be detected, but the scanning time becomes too long to operate between aircraft takeoffs and landings
Solution Approach 1:
The patent segments the runway into multiple scanning regions and scans them sequentially or in parallel, significantly reducing the time required for each individual scan while maintaining high detection accuracy. This segmentation approach allows the system to complete full runway inspection within the limited time window between aircraft operations.
Solution Approach 2:
The system performs repeated scanning of the same region multiple times and combines the point cloud data through alignment and integration. This periodic scanning approach increases the effective point cloud density over time while keeping individual scan durations short, enabling high-precision detection without excessive total scanning time.
3Measurement precision
If the LiDAR scanner operates at high scanning density, then small foreign bodies can be detected, but the processing time and computational load increase significantly
Solution Approach 1:
The patent processes point cloud data from each scanning region separately before combining them. This segmentation of data processing reduces the computational load for each processing step compared to handling all data simultaneously, while still achieving high detection accuracy through the integrated result of multiple processed segments.
Solution Approach 2:
The system performs preliminary alignment and filtering of point cloud data from each scanning region before final integration. This preliminary processing prepares the data in advance, reducing the computational complexity of the final foreign body detection step and overall processing time.
4Adaptability or versatility
If a mobile inspection device is used to patrol the runway, then flexible inspection is possible, but the device obstructs aircraft takeoffs and landings
Solution Approach 1:
Instead of using a mobile device that moves through the runway environment, the patent employs a fixed-point LiDAR scanner that remains stationary. This inverted approach - making the scanner fixed rather than mobile - eliminates the obstruction problem while maintaining inspection capability through the fixed scanner's ability to cover the entire runway via multiple scanning operations.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances the reliability and speed of foreign body detection on vast runways by narrowing the scanning range while ensuring the monitoring target is included, allowing for efficient inspection even during busy airport operations.
Implementation Method 1
a point cloud acquisition means for acquiring a point cloud by controlling a fixed-point three-dimensional LiDAR scanner in such a way that the fixed-point three-dimensional LiDAR scanner performs scanning in a scanning range including a monitoring target
Data Source
AI summary
A foreign body detection system includes a first point cloud acquisition unit and a second point cloud acquisition unit as a point cloud acquisition means, an alignment unit, and a foreign body detection unit. The point cloud acquisition means acquires a point cloud by controlling a first fixed-point three-dimensional LiDAR scanner in such a way that the first fixed-point three-dimensional LiDAR scanner performs scanning in a scanning range including a monitoring target in a scanning range and generates a point cloud. The alignment unit aligns the point cloud and known three-dimensional shape data about the monitoring target with each other. The foreign body detection unit detects a foreign body in contact with the monitoring target, based on the point cloud and the aligned three-dimensional shape data.